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Poly-ether-ether-ketone (PEEK), a biomaterial renowned for its mechanical prowess and biocompatibility, is increasingly preferred for medical implants. Its natural bone-like mechanical property, ease of manipulation, and ability to mitigate stress shielding render it a standout replacement for titanium in dental implantology. Adding carbon fiber and graphene to PEEK can further enhance the mechanical properties of PEEK. However, the biological passivity of PEEK hampers its efficacy in bone repair, driving spurring research into surface modifications to enhance its bioactivity. Incorporating metal, inorganic, and organic antimicrobial agents is anticipated to bolster PEEK’s resistance to bacteria, thereby reducing the risk of acute postoperative infections and peri-implantitis. Apart from its antimicrobial activity, researchers have also investigated methods to enhance the osteogenic properties of PEEK. These approaches include surface modification and blending modification. Surface modification includes physical modification, chemical modification, and biologically active substance modification. These methods can further enhance the implant integration and durability, potentially improving patient outcomes. This overview examines PEEK’s processing techniques and highlights recent research achievements in improving its biomechanical, antibacterial, and osteogenic properties. Considering these strides, we argue that modified PEEK holds significant promise as a material for dental implants, charting an encouraging course for its clinical future.

Chinese yam (Dioscorea polystachya Thunb.) is an important root crop. Wilt caused by Fusarium is among the most important emerging diseases on yams. However, there is currently limited information on the molecular epidemiology of Fusarium causing yam wilt. Here, we investigated wilted yam samples from six regions in South-Central China. A total of 117 Fusarium isolates were obtained from diseased tissues of 37 wilted yam plants. These yam plants belonged to two varieties characterized by white and purple fleshy tubers, respectively. Analyses of ef1-α sequences identified that these 117 Fusarium isolates belonged to 11 putative species, with F. aff. commune being the most common (31.6%), followed by F. aff. cugenangense (29.1%), a potential undescribed species Fusarium aff. sp. (11.1%), F. aff. gossypinum (9.4%), F. aff. fujikuroi (8.5%), F. aff. nirenbergiae (6%), and one isolate each (0.85%) of F. aff. asiaticum, F. aff. curvatum, F. aff. odoratissimum, F. aff. solani, and F. aff. verticillioides. Six of these species were recently described as new species within the Fusarium oxysporum species complex (FOSC). Interestingly, 18 of the 37 yam plants were infected by two or more Fusarium species each and there was evidence for differential Fusarium species distributions based on geographic location and/or yam host variety. Multilocus microsatellite genotyping of the 67 FOSC isolates revealed that isolates of the same species from the same diseased plants often belonged to different genotypes. Interestingly, several FOSC microsatellite genotypes were shared among distinct geographic regions, consistent with long-distance dispersal. However, population genetic analyses revealed significant contributions of geographic separation to the overall genetic variation of FOSC with several pairs of geographic populations showing significant genetic differentiations, consistent with differential geographic distribution of the species within FOSC. The implications of our results to the managements of Fusarium wilt in yams were discussed.

The essential oil of Mosla chinensis Maxim cv. Jiangxiangru is known for its antibacterial ability. This study aimed to investigate the chemical composition of Jiangxiangru essential oil and its inhibitory effect on Staphylococcus aureus biofilm formation. Gas chromatography/mass spectrometry (GC–MS) was used to determine the chemical composition of Jiangxiangru essential oil. Subsequently, the eight major chemical components were quantitatively analyzed using GC– MS, and their minimum inhibitory concentration (MIC) values against S. aureus were tested. Biofilm formation was detected by crystal violet semi-quantitative method and silver staining. Of the 59 peaks detected, 29 were identified by GC–MS. Of these peaks, thymol, carvacrol, p-cymene, γ-terpinene, thymol acetate, α-caryophyllene, 3-carene, and carvacryl acetate were present at a relatively higher concentration. The results of the quantitative test showed that thymol, carvacrol, p-cymene, and γ-terpinene were the major components of the essential oil. Among the eight reference substances, only thymol, carvacrol, and thymol acetate had lower MICs compared with the essential oil. Essential oil, carvacrol, carvacryl acetate, α-caryophyllene, and 3-carene showed the better inhibition of S. aureus biofilm formation. When one fourth of the MIC concentrations were used for these substances (0.0625 mg/mL for essential oil, 0.0305 mg/mL for carvacrol, 1.458 mg/mL for carvacryl acetate, 0.1268 mg/mL for α-caryophyllene, and 2.5975 mg/mL for 3-carene), the inhibition rates were over 80%. However, thymol, γ-terpinene, thymol acetate, and p-cymene showed a relatively poor inhibition of S. aureus biofilm formation. When 1× MIC concentrations of these substances were used, the inhibition rates were less than 50%. In conclusion, Jiangxiangru essential oil and its major components, carvacrol, carvacryl acetate, α-caryophyllene, and 3-carene, strongly inhibited biofilm formation in S. aureus.

Although the equivalent fixture error approach used in variation propagation can directly model the process physics regarding how datum-induced, fixture-induced and machine tool-induced errors generate the same error pattern on part features, the developed equivalent fixture error compensation technique did not consider machining-induced variations. Machining-induced variations are often caused by geometric-thermal effects, cutting force-induced variations, and/or cutting-tool wear, etc. Such machining-induced variations are an important factor that influences the part quality. Without considering machining-induced variations, the application of EFE model for error compensation will be limited. In order to overcome this limitation, this paper extends current equivalent fixture error to include machining-induced variations. This paper shows the benefits of the extended model through a case study.

Assembly variations are unavoidable due to parts’ geometrical errors. Statistical variation analysis is an effective method to quantitatively predict product quality in the original design stage. However, traditional methods can’t handle the problem of abnormal distribution of the actual variation variables. Meanwhile, they are underdeveloped in regard to the complex geometrical errors in spatial 3D state. To overcome this problem, firstly, Jacobian-Torsor model is used to build the variation propagation, which is well suited to a complex assembly that contains large numbers of joints and geometric tolerances; secondly, Pearson distribution family is adopted to determine probability distribution pattern and build probability density function. By comparing results of the suggested method to the Monte Carlo method, it is observed that this novel method has the same accuracy, but much higher efficiency. The results also demonstrate that probability distribution types of the parts variations have a significant impact on the final assembling variation.

Textbooks use images, in addition to text, for delivering knowledge, thereby convey attitudes and values of students including those on gender bias. The gender bias presented in textbook images affects in subtle ways the students' learning outcomes, career choices, and how they perceive science. However, prior research has relied on explicit information presented by textbook images of several subjects to investigate gender representation, overlooking the implicit meaning behind images with a very limited attention to science textbooks. Therefore, this study uses the social semiotic framework to analyse the implicit meaning that images convey related to gender representation in Chinese and Egyptian science textbooks. Specifically, four (two for each country) science textbooks of grade nine were coded and analysed. The findings revealed that gender gap still exists in the images of both Chinese and Egyptian science textbooks. Specifically, females were less represented in the textbook images compared to males, and their role was mostly a caring role. Notably, unlike the Chinese females and the common gender stereotype, Egyptian females were represented in a more active and powerful way compared to males. The findings of this study could help in better designing science textbook images to reduce gender bias.