Search Results (5)

Pomegranate (Punica granatum), a shrub belonging to the Lythraceae family, has long been recognized for its diverse pharmacological benefits, including potential roles in managing inflammation and diabetes. The present study explored the insulin-secretory and β-cell proliferative properties of the ethanol extract of P. granatum fruit peel (EEPG) and assessed its influence on glucose regulation in high-fat-fed diet-induced obese mice (HFDi-OM) through in vivo and in silico studies. In vitro, EEPG was found to activate cAMP-dependent pathways and regulate K_ATP channels, thereby enhancing glucose-stimulated insulin secretion from BRIN-BD11 β-cells, with partial reliance on extracellular calcium. EEPG promoted β-cell proliferation, as indicated by an increase in Ki-67 positive cells, and displayed inhibitory effects on glucose diffusion and starch hydrolysis, suggesting a capacity to delay carbohydrate digestion and absorption. Furthermore, EEPG demonstrated antioxidant activity by neutralizing free radicals. In an acute test, EEPG (at doses of 150 and 250 mg/5 mL/kg) improved oral glucose tolerance and elevated plasma insulin levels. Long-term oral treatment for 21 days to HFDi-OM led to a significant reduction in fasting blood glucose, body weight, and food and fluid intake. It also enhanced gastrointestinal motility and improved lipid profiles by increasing HDL and lowering total cholesterol, LDL, and triglycerides. The therapeutic properties of EEPG are likely attributed to its rich bioactive components, including flavonoids (quercetin, kaempferol, catechin, and epicatechin) and phenolic acids (ellagic acid), which exhibited strong multi-target binding affinities in in silico molecular docking studies toward SUR1, PDE4, PI3K, and α-amylase, thereby supporting enhanced insulin secretion, β-cell function and glucose homeostasis. Full article

With the aim of achieving the combat technical requirements of super-quick (SQ) initiation and reliable self-destruction (SD) of a small-caliber projectile fuze, this paper describes a high-functional-density integrated (HFDI) inertial switch based on the “ON-OFF” state transition (i.e., almost no terminal ballistic motion). The reliable state switching of the HFDI inertial switch is studied via elastic–plastic mechanics and verified via both simulations and experiments. The theoretical and simulation results indicate that the designed switch can achieve the “OFF-ON” state transition in the internal ballistic system, and the switch can achieve the “ON-OFF” state transition in the simulated terminal ballistic system within 8 μs or complete the “ON-OFF” state transition as the rotary speed sharply decreases. The experimental results based on the anti-target method show the switch achieves the “ON-OFF” state transition on the μs scale, which is consistent with the simulation results. Compared with the switches currently used in small-caliber projectile fuzes, the HFDI inertial switch integrates more functions and reduces the height by about 44%. Full article

The 4G network is not sufficient for achieving the high data requirements of smart city users. The 5G network intends to meet these requirements and overcome other application issues, such as fast data transmission, video buffering, and coverage issues, providing excellent mobile data services to smart city users. To allocate a channel or spectrum to a smart city user for error-free transmission with low latency, the accurate information of the spectrum should be detected. In this study, we determined the range of non-cooperative detection techniques, such as matched filter detection with inverse covariance approach (MFDI), cyclostationary feature detection with inverse covariance approach (CFDI), and hybrid filter detection with inverse covariance approach (HFDI); based on the results of these methods, we provided highly accurate spectrum information for smart city users, enabling sustainable development. To evaluate the performance of the proposed detection techniques, the following parameters are used: probability of detection (P_D), probability of false alarms (P_fa), probability of miss detection (P_md), sensing time, and throughput. The simulation results revealed that the HFDI detection method provided sustainable results at low signal-to-noise ratio ranges and improved channel detection and throughput of approximately 17% and 10%, respectively. Full article

Based on the provincial panel data from 2008 to 2019, this paper constructs a mediating effect model to analyze the impact of China’s agricultural insurance development on the nutritional status of rural residents theoretically and empirically. This study found that agricultural insurance significantly affects the nutritional status of rural residents through two mediators: increased income level and the regional crop diversity. Meanwhile, regional heterogeneity exists in the impact of agricultural insurance on the nutritional status of rural residents. Overall, this paper argues that agricultural insurance should be one of the tools to improve the nutritional status of rural residents in China. Specifically, the design and implementation process of policy-based agricultural insurance should put the nutritional health of rural residents and their complex impact into consideration. Therefore, this paper suggests that even though agricultural insurance can facilitate rural residents’ income stability and generation, relevant stakeholders also need to draw awareness, popularize the importance of nutrition and health, and optimize the supply structure of agricultural products. Full article

Precursore IperSpettrale della Missione Applicativa (Hyperspectral Precursor of the Application Mission, PRISMA) is a new hyperspectral mission by the ASI (Agenzia Spaziale Italiana, Italian Space Agency) mission launched in 2019 to measure the unique spectral features of diverse materials including vegetation and forest disturbances. In this study, we explored the potential use of this new sensor PRISMA for active wildfire characterization. We used the PRISMA hypercube acquired during the Australian bushfires of 2019 in New South Wales to test three detection techniques that take advantage of the unique spectral features of biomass burning in the spectral range measured by PRISMA. The three methods—the CO₂-CIBR (continuum interpolated band ratio), HFDI (hyperspectral fire detection index) and AKBD (advanced K band difference)—were adapted to the PRISMA sensor’s characteristics and evaluated in terms of performance. Classification techniques based on machine learning algorithms (support vector machine, SVM) were used in combination with the visual interpretation of a panchromatic sharpened PRISMA image for validation. Preliminary analysis showed a good overall performance of the instrument in terms of radiance. We observed that the presence of the striping effect in the data can influence the performance of the indices. Both the CIBR and HFDI adapted for PRISMA were able to produce a detection rate spanning between 0.13561 and 0.81598 for CO₂-CIBR and that between 0.36171 and 0.88431 depending on the chosen band combination. The potassium emission index turned out to be inadequate for locating flaming in our data, possibly due to multiple factors such as striping noise and the spectral resolution (12 nm) of the PRISMA band centered at the potassium emission. Full article