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The elongation behavior formed the main biomechanical difference between native and acellular human scalp samples with elastic modulus and ultimate tensile strength being similar when comparing the two.Aging is an irreversible process. This research aims to study the anti-aging effects of GRCP, a compound preparation made by Ganoderma lucidum and Rhodiola rosen, in aging rats. Rats were subcutaneously injected with 400 mg/kg of D-galactose daily, and aging could be induced after 8 weeks. The aging rats were treated with GRCP. This experiment was divided into 6 groups. Rats were randomly divided into the model group, positive control group, low-dose GRCP group (25 mg/kg body weight), medium-dose GRCP group (50 mg/kg body weight), and high-dose GRCP group (100 mg/kg body weight), healthy and normal rats were used as blank controls. After the end, the results show that the use of GRCP at a dose of 100 mg/kg is the best treatment for improving aging rats. Rats gained weight, spleen and thymus indexes, and splenocyte proliferation improved, and inflammatory cytokine levels decreased. Besides, biochemical indicators show that GRCP can improve the antioxidant enzyme activity and reduce the content of lipofuscin and TGF-β in aging rats (P  less then  0.05). GRCP can also inhibit the activation of the MyD88/NF-κB pathway in rat hippocampus. #link# buy OTX008 seem to suggest that GRCP can be used as a potential natural supplement or functional food to prevent aging.The degradation of air quality is the most concerned issue of our society due to its harmful impacts on human health, especially in cities with rapid urbanization and population growth like Hanoi, the capital of Vietnam. This study aims at developing a new approach that combines data-driven models and interpolation technique to develop the PM10 concentration maps from meteorological factors for the central area of Hanoi. Data-driven models that relate the PM10 concentration with the meteorological factors at the air quality monitoring stations in the study area were developed using the Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) algorithms. Models' performance comparison showed that ANN models yielded better goodness-of-fit indices than MLR models at all stations in the study area with average coefficient of correlation (r) and Nash-Sutcliffe Efficiency Index (NSE) of 0.51 and 0.34 for the former, and 0.7 and 0.49 for the latter. These indices indicates that the ANN-based data-driven models outperformed the MLR-based models. Thus, the ANN-based models and the Inverse Distance Weighting (IDW) interpolation technique were then combined for mapping the monthly PM10 concentration with a spatial resolution of 1 km from global meteorological data. With this combination, the PM10 concentration maps account for both local PM10 concentration and impacts of spatio-temporal variations of meteorological factors on the PM10 concentration. This study provides a promising method to predict the PM concentration with a high spatio-temporal resolution from meteorological data.In the western Indo-Gangetic plains, issues of deterioration in soil, water, and environment quality coupled with low profitability jeopardize the sustainability of the dominant rice-wheat (RW) system. To address these issues, crop diversification and conservation agriculture (CA)-based management hold considerable promise but the adoption of both approaches has been low, and additional evidence generation from a multi-criteria productivity and sustainability perspective is likely required to help drive the change. Compared to prevailing farmers' practice (FP), results suggest that CA-based rice management increased profitability by 13% and energy use efficiency (EUE) by 21% while reducing irrigation by 19% and global warming potential (GWP) by 28%. By substituting CA-based maize for rice, similar mean profitability gains were realized (16%) but transformative improvements in irrigation (- 84%), EUE (+ 231%), and GWP (- 95%) were observed compared to FP. Inclusion of mungbean in the rotation (i.e. maize-wheat-mungbean) with CA-based management increased the system productivity, profitability, and EUE by 11, 25 and 103%, respectively while decreasing irrigation water use by 64% and GWP by 106% compared to FP. Despite considerable benefits from the CA-based maize-wheat system, adoption of maize is not widespread due to uneven market demand and assured price guarantees for rice.Cells obtained from human saliva are commonly used as an alternative DNA source when blood is difficult or less convenient to collect. Although DNA extracted from saliva is considered to be of comparable quality to that derived from blood, recent studies have shown that non-human contaminating DNA derived from saliva can confound whole genome sequencing results. The most concerning complication is that non-human reads align to the human reference genome using standard methodology, which can critically affect the resulting variant genotypes identified in a genome. We identified clusters of anomalous variants in saliva DNA derived reads which aligned in an atypical manner. These reads had only short regions of identity to the human reference sequence, flanked by soft clipped sequence. Sequence comparisons of atypically aligning reads from eight human saliva-derived samples to RefSeq genomes revealed the majority to be of bacterial origin (63.46%). To partition the non-human reads during the alignment step, a decoy of the most prevalent bacterial genome sequences was designed and utilised. This reduced the number of atypically aligning reads when trialled on the eight saliva-derived samples by 44% and most importantly prevented the associated anomalous genotype calls. Saliva derived DNA is often contaminated by DNA from other species. This can lead to non-human reads aligning to the human reference genome using current alignment best-practices, impacting variant identification. This problem can be diminished by using a bacterial decoy in the alignment process.Superconducting stacks and bulks can act as very strong magnets (more than 17 T), but they lose their magnetization in the presence of alternating (or ripple) transverse magnetic fields, due to the dynamic magneto-resistance. This demagnetization is a major concern for applications requiring high run times, such as motors and generators, where ripple fields are of high amplitude and frequency. We have developed a numerical model based on dynamic magneto-resistance that is much faster than the conventional Power-Law-resistivity model, enabling us to simulate high number of cycles with the same accuracy. We simulate demagnetization behavior of superconducting stacks made of 10-100 tapes for up to 2 million cycles of applied ripple field. We found that for high number of cycles, the trapped field reaches non-zero stationary values for both superconducting bulks and stacks; as long as the ripple field amplitudes are below the parallel penetration field, being determined by the penetration field for a single tape in stacks.