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Prolonged use of tight-fitting PPE, e.g., by COVID-19 healthcare workers leads to skin injuries. An important contributor is the shear exerted on the skin due to static friction at the skin-PPE interface. This study aims to develop an optimised wax-oil lubricant that reduces the friction, or shear, in the skin-PPE contact for up to four hours. Lubricants with different wax-oil combinations were prepared using beeswax, paraffin wax, olive oil, and mineral oil. In-vivo friction measurements involving seven participants were conducted by sliding a polydimethylsiloxane ball against the volar forearms to simulate the skin-PPE interface. The maximum static coefficient of friction was measured immediately and four hours after lubricant application. It was found that the coefficient of friction of wax-oil lubricants is mainly governed by the ratio of wax to oil and the thermal stability and morphology of the wax. To maintain long-term lubricity, it is crucial to consider the absorption of oil into the PPE material. The best performing lubricant is a mixture of 20 wt% beeswax, 40 wt% olive oil, and 40 wt% mineral oil, which compared to unlubricated skin, provides 87% (P = 0.0006) and 59% (P = 0.0015) reduction in instantaneous and 4-h coefficient of friction, respectively.

Crop breeding for high nitrogen use efficiency (NUE) or tolerance to low nitrogen fertilization is thought to be an ideal solution to reduce the cost, carbon footprint, and other environmental problems caused by the excess use of nitrogen fertilizers. As a model plant for cereal crops, barley has many advantages, including good adaptability, a short growth period, and high natural stress resistance or tolerance. Therefore, research on improving NUE in barley is not only beneficial for nitrogen-efficient barley breeding but will also inform NUE improvement in other cereal crops. In this review, recent progress in understanding barley’s response to nitrogen nutrition, evaluation of NUE or low-nitrogen tolerance, quantitative trait loci (QTL) mapping and gene cloning associated with improving NUE, and breeding of nitrogen-efficient barley is summarized. Furthermore, several biotechnological tools that could be used for revealing the molecular mechanisms of NUE or breeding for improving NUE in barley are introduced, including GWAS, omics, and gene editing. The latest research ideas in unraveling the molecular mechanisms of improving NUE in other crops are also discussed. Thus, this review provides a better understanding of improving the NUE of barley and some directions for future research in this area.

Prolonged use of tight-fitting PPE, e.g., by COVID-19 healthcare workers leads to skin injuries. An important contributor is the shear exerted on the skin due to static friction at the skin-PPE interface. This study aims to develop an optimised wax-oil lubricant that reduces the friction, or shear, in the skin-PPE contact for up to four hours. Lubricants with different wax-oil combinations were prepared using beeswax, paraffin wax, olive oil, and mineral oil. In-vivo friction measurements involving seven participants were conducted by sliding a polydimethylsiloxane ball against the volar forearms to simulate the skin-PPE interface. The maximum static coefficient of friction was measured immediately and four hours after lubricant application. It was found that the coefficient of friction of wax-oil lubricants is mainly governed by the ratio of wax to oil and the thermal stability and morphology of the wax. To maintain long-term lubricity, it is crucial to consider the absorption of oil into the PPE material. The best performing lubricant is a mixture of 20 wt% beeswax, 40 wt% olive oil, and 40 wt% mineral oil, which compared to unlubricated skin, provides 87% (P = 0.0006) and 59% (P = 0.0015) reduction in instantaneous and 4-hour coefficient of friction, respectively.

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Barley (Hordeum vulgare L.) is an important economic crop for food, feed and industrial raw materials. In the present research, 112 barley landraces from the Shanghai region were genotyped using genotyping-by-sequencing (GBS), and the genetic diversity and population structure were analyzed. The results showed that 210,268 Single Nucleotide Polymorphisms (SNPs) were present in total, and the average poly-morphism information content (PIC) was 0.1642. Genetic diversity and population structure analyses suggested that these barley landraces were differentiated and could be divided into three sub-groups, with morphological traits of row-type and adherence of the hulls the main distinguishing factors between groups. Genotypes with similar or duplicated names were also investigated according to their genetic backgrounds and seed appearances. This study provided valuable information on barley landraces from the Shanghai region, and showed that all these barley landraces should be protected and used for future breeding programs.

The insertion torque of a dental implant is an important indicator for the primary stability of dental implants. Thus, the preoperative prediction for the insertion torque is crucial to improve the success rate of implantation surgery. In this present research, an alternative method for prediction of implant torque was proposed. First, the mechanical model for the insertion torque was established based on oblique cutting process. In the proposed mechanical model, three factors, including bone quality, implant geometry and surgical methods were considered by defined bone-quality coefficients, chip load and insertion speeds, respectively. Then, the defined bone-quality coefficients for cancellous bone with the computed tomography (CT) value of 235~245, 345~355 and 415~425 Hu were obtained by a series of insertion experiments of IS and ITI implants. Finally, the insertion experiments of DIO implants were carried out to verify the accuracy of developed model. The predicted insertion torques calculated by the mechanical model were compared with that acquired by insertion experiments, which were agreed match with the relative error less than 15%. This method reduces the time consumption on establishing the fitting equations for different implants and enhance the predicted accuracy by considering the effects of implants’ geometries and surgical methods.

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