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This research investigates and robustly verifies the impact of expansionary monetary policy actions on green innovation, conducted on a panel covering 133 countries from 1960 to 2018. Overall, we find that such actions have a significantly positive effect on green innovation performance, no matter in the static or dynamic model. A lower degree of central bank independence and poorer property rights protection in developing countries may hinder monetary policies’ effect to be transmitted to green innovation activities smoothly. Moreover, stringent environmental regulation contributes to magnifying the expansionary monetary policy’s positive effect on green innovation, but such a positive moderating effect should be supported by good national governance quality (including better control over corruption, higher efficiency of governments and a complete law system). Accordingly, several policy suggestions are provided.

Weed suppression is an important factor affecting crop yields. Precise identification of weed species will contribute to automatic weeding by applying proper herbicides, hoeing position determination, and hoeing depth to specific plants as well as reducing crop injury. However, the lack of datasets of weeds in the field has limited the application of deep learning techniques in weed management. In this paper, it presented a dataset of weeds in fields, Weed25, which contained 14,035 images of 25 different weed species. Both monocot and dicot weed image resources were included in this dataset. Meanwhile, weed images at different growth stages were also recorded. Several common deep learning detection models—YOLOv3, YOLOv5, and Faster R-CNN—were applied for weed identification model training using this dataset. The results showed that the average accuracy of detection under the same training parameters were 91.8%, 92.4%, and 92.15% respectively. It presented that Weed25 could be a potential effective training resource for further development of in-field real-time weed identification models. The dataset is available at https://pan.baidu.com/s/1rnUoDm7IxxmX1n1LmtXNXw ; the password is rn5h.

The fabrication and mechanical properties of boron carbide/regenerated cellulose composite fibers prepared via the copper ammonia method were investigated. The process involves dissolving cellulose in a copper ammonia solution, incorporating boron carbide powder, and subsequently performing wet spinning to produce composite fibers. The results indicate that the addition of boron carbide significantly alters the surface morphology and color of the fibers, rendering them rougher and darker. EDS analysis confirms the presence and distribution of boron carbide within the composite fibers, while TG analysis reveals enhanced thermal stability with increasing boron carbide content. XRD and FTIR analyses provide detailed insights into the crystal structure and functional groups of the composite fibers, confirming the successful incorporation of boron carbide into the cellulose matrix. Mechanical property evaluations show that smaller boron carbide particles (500 nm) have a more pronounced detrimental effect on the fracture strength of the composite fibers, likely due to agglomeration and the formation of stress concentrations. The post-treatment with glutaraldehyde at optimal concentrations and reaction times can enhance the tenacity of the composite fibers.

Conventional core-shell polymer nanoparticles usually exhibit a rapid release rate with their release kinetics mainly adjusted through changing composition of the polymer shells, limiting their applications for prolonged drug delivery. As a solution to these problems, silica xerogel/polymer core-shell-structured composite nanoparticles have been proposed. Different with our previous work centring on studying process variables, we here focused on investigating the effects of key compositional variables on essential properties of the composite nanoparticles. The drug release profiles ( in vitro ) were well interpreted by the Baker and Lonsdale model on a predicted two-stage basis. The first stage (<1 day) was well controlled from 18.6% to 45.9%; the second stage (1–14 days) was tailored in a range from 28.7 to 58.2% by changing the composition of the silica xerogel cores and polymeric shells. A substantial achievement was reducing the release rate by more than 40 times compared with that of conventional polymer nanoparticles by virtue of the silica xerogel cores. A semi-empirical model was also established in the first attempt to describe the effects of polymer concentration and drug loading capacity on the size of the composite nanoparticles. All these results indicated that the composite nanoparticles are promising candidates for prolonged drug delivery applications.

Atherosclerosis is one of the main underlying causes of cardiovascular diseases (CVD). It is associated with chronic inflammation and intimal thickening as well as the involvement of multiple cell types including immune cells. The engagement of innate or adaptive immune response has either athero-protective or atherogenic properties in exacerbating or alleviating atherosclerosis. In atherosclerosis, the mechanism of action of immune cells, particularly monocytes, macrophages, dendritic cells, and B- and T-lymphocytes have been discussed. Immuno-senescence is associated with aging, viral infections, genetic predispositions, and hyperlipidemia, which contribute to atherosclerosis. Immune senescent cells secrete SASP that delays or accelerates atherosclerosis plaque growth and associated pathologies such as aneurysms and coronary artery disease. Senescent cells undergo cell cycle arrest, morphological changes, and phenotypic changes in terms of their abundances and secretome profile including cytokines, chemokines, matrix metalloproteases (MMPs) and Toll-like receptors (TLRs) expressions. The senescence markers are used in therapeutics and currently, senolytics represent one of the emerging treatments where specific targets and clearance of senescent cells are being considered as therapy targets for the prevention or treatment of atherosclerosis.

Recent studies have shown platelet to lymphocyte ratio (PLR) to be a potential inflammatory marker in cardiovascular diseases. We performed a meta-analysis to systematically evaluate the prognostic role of PLR in acute coronary syndrome (ACS). A comprehensive literature search up to May 18, 2016 was conducted from PUBMED, EMBASE and Web of science to identify related studies. The risk ratio (RR) with 95% confidence interval (CI) was extracted or calculated for effect estimates. Totally ten studies involving 8932 patients diagnosed with ACS were included in our research. We demonstrated that patients with higher PLR level had significantly higher risk of in-hospital adverse outcomes (RR = 2.24, 95%CI = 1.81–2.77) and long-term adverse outcomes (RR = 2.32, 95%CI = 1.64–3.28). Sensitivity analyses confirmed the stability of our results. We didn’t detect significant publication bias by Begg’s and Egger’s test (p > 0.05). In conclusion, our meta-analysis revealed that PLR is promising biomarker in predicting worse prognosis in ACS patients. The results should be validated by future large-scale, standard investigations.

Alzheimer Associated Diabetes Mellitus, commonly known as Type 3 Diabetes Mellitus (T3DM) is a distinct subtype of diabetes with a pronounced association with Alzheimer's disease (AD). Insulin resistance serves as a pivotal link between these two conditions, leading to diminished insulin sensitivity, hyperglycemia, and impaired glucose uptake. The brain, a vital organ in AD context, is also significantly impacted by insulin resistance, resulting in energy deficits and neuronal damage, which are hallmark features of the neurodegenerative disorder. To pave the way for potential therapeutic interventions targeting the insulin resistance pathway, it is crucial to comprehend the intricate pathophysiology of T3DM and identify the overlapped features between diabetes and AD. This comprehensive review article aims to explore various pathway such as AMPK, PPARγ, cAMP and P13K/Akt pathway as potential target for management of T3DM. Through the analysis of these complex mechanisms, our goal is to reveal their interdependencies and support the discovery of innovative therapeutic strategies. The review extensively discusses several promising pharmaceutical candidates that have demonstrated dual drug action mechanisms, addressing both peripheral and cerebral insulin resistance observed in T3DM. These candidates hold significant promise for restoring insulin function and mitigating the detrimental effects of insulin resistance on the brain. The exploration of these therapeutic options contributes to the development of innovative interventions that alleviate the burden of T3DM and enhance patient care. •Type 3 Diabetes Mellitus (T3DM) is a distinct form of diabetes that shows a strong association with Alzheimer's disease (AD), indicating shared underlying mechanism.•This paper explores different therapeutic options targeting AMPK, PPARγ, and cAMP pathway as a potential treatments avenue, focusing on restoring insulin function and addressing both peripheral and cerebral insulin resistance.•Pharmacological drugs targeting both diabetes and Alzheimer's disease demonstrate dual action, offering potential benefits for patients.

A bstract We calculate the thermal correction to the entanglement spectrum for separating a single interval of two dimensional conformal field theories. Our derivation is a direct extension of the thermal correction to the Rényi entropy. Within a low-temperature expansion by including only the first excited state in the thermal density matrix, we approach analytical results of the thermal correction to the entanglement spectrum at both of the small and large interval limit. We find the temperature correction reduces the large eigenvalues in the entanglement spectrum while increases the small eigenvalues in the entanglement spectrum, leading to an overall crossover changing pattern of the entanglement spectrum. Crucially, at low-temperature limit, the thermal corrections are dominated by the first excited state and depend on its scaling dimension ∆ and degeneracy g . This opens an avenue to extract universal information of underlying conformal data via the thermal entanglement spectrum. All of these analytical computation is supported from numerical simulations using 1+1 dimensional free fermion. Finally, we extend our calculation to resolve the thermal correction to the symmetry-resolved entanglement spectrum.

Herpes simplex virus is responsible for numerous ocular diseases, the most common of which is herpetic stromal keratitis. This is a recurrent infection of the cornea that typically begins with a subclinical infection of the cornea that establishes a latent infection of sensory ganglia, most often the trigeminal ganglia. Recurring infections occur when the virus is reactivated from latency and travels back to the cornea, where it restimulates an inflammatory response. This inflammatory response can lead to decreased corneal sensation, scarring, and blindness. The diagnosis of these lesions as the result of a recurrent herpes simplex virus infection can at times be problematic. Currently, herpetic stromal keratitis is diagnosed by its clinical presentation on the slit-lamp examination, but the literature does not always support the accuracy of these clinical findings. Other diagnostic tests such as polymerase chain reaction assay, enzyme-linked immunosorbent assay, immunofluorescent antibody, and viral cultures have provided more definitive diagnosis, but also have some limitations. That said, accurate diagnosis is necessary for proper treatment, in order to prevent serious consequences. Current treatment reduces the severity of lesions and controls further viral spread, but does not provide a cure.

Creep is one of the typical mechanical properties of clay, and studying the creep mechanical properties of clay is of great significance to construction projects in clay sites. This study conducted creep tests on Chengdu clay and found that the soil mass underwent elastic deformation, decay creep deformation, steady-state creep deformation, and accelerated creep deformation. The isochronous stress ratio-logarithmic strain curves and their mathematical models were proposed to thoroughly analyze clay creep mechanical properties. Creep automatic feature points, such as linear elastic extreme point, initial yield point, long-term strength point, and plastic point, were identified on the curve. Considering the hardening and damage effects during creep loading, linear elastic and viscoelastic elements considering the time-dependent damage, a viscoplastic element considering the load hardening effect, and viscoplastic and plastic elements considering the load damage effect were established based on the element model and the Riemann–Liouville fractional derivative. Based on the mechanical properties of the whole clay creep process, the creep mechanical feature points, and the established element model, a clay creep model was proposed considering the hardening and damage effects. The rationality and regularity of the creep model were verified using the creep test data. This research accurately revealed the creep mechanical properties of clay and facilitated soil deformation prediction, thus providing technical guidance and references for construction projects in clay sites.