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Protected Designation of Origin (PDO) dry-cured hams production is greatly dependent on raw meat quality. This study was performed to identify genetic markers associated with the quality of dry-cured ham. Carcass traits of 229 heavy pigs belonging to three commercial genetic lines were registered (weight, EUROP classification). Phenotypic traits (Semimembranosus muscle ultimate pH, ham weight and lean meat content, adsorbed salt) of the corresponding thighs, undergone PDO ham process in three different plants, were measured, using a fast and non-invasive technology. Green ham weight and lean meat percentage influenced the estimated salt content and the weight loss during salting, even if the processing plant greatly affected the variability of the measured ham traits. The genomic data were obtained with the GeneSeek Genomic Profiler (GGP) 70k HD Porcine Array, using the slaughter day and the sex of the animals in the statistical analyses. The phenotypic traits were associated with the genotypes through GenAbel software. The results showed that 18 SNPs located on nine porcine chromosomes were found to be associated with nine phenotypic traits, mainly related to ham weight loss during salting. New associations were found between markers in the genes Neural Precursor Cell Expressed Developmentally Down-Regulated 9 (NEDD9, SSC7), T-Cell Lymphoma Invasion and Metastasis 2 (TIAM2, SSC1), and the ham quality traits. After validation, these SNPs may be useful to improve the quality of thighs for the production of PDO dry-cured hams.Bone cement is used as a mortar for securing bone implants, as bone void fillers or as spacers in orthopaedic surgery. Antibiotic-loaded bone cements (ALBCs) have been used to prevent and treat prosthetic joint infections by providing a high antibiotic concentration around the implanted prosthesis. High antibiotic concentrations are, on the other hand, often associated with tissue toxicity. Controlling antibiotic release from ALBCS is key to achieving effective infection control and promoting prosthesis integration with the surrounding bone tissue. However, current ALBCs still need significant improvement in regulating antibiotic release. In this review, we first provide a brief introduction to prosthetic joint infections, and the background concepts of therapeutic efficacy and toxicity in antibiotics. We then review the current state of ALBCs and their release characteristics before focusing on the research and development in controlling the antibiotic release and osteo-conductivity/inductivity. [https://www.selleckchem.com/products/paeoniflorin.html selleck chemical] We then conclude by a discussion on the need for better in vitro experiment designs such that the release results can be extrapolated to predict better the local antibiotic concentrations in vivo.A novel 2H-phase transition metal dichalcogenide (TMD)-tantalum selenide (TaSe2) with metallic bandgap structure is a potential photoelectric material. A band structure simulation of TaSe2 via ab initio method indicated its metallic property. An effective multilayered TaSe2 saturable absorber (SA) was fabricated using liquid-phase exfoliation and optically driven deposition. The prepared 2H-TaSe2 SA was successfully used for a dual-wavelength Q-switched fiber laser with the minimum pulse width of 2.95 μs and the maximum peak power of 64 W. The repetition rate of the maximum pulse energy of 89.9 kHz was at the level of 188.9 nJ. The metallic 2H-TaSe2 with satisfactory saturable absorbing capability is a promising candidate for pulsed laser applications.In-class teaching evaluation, which is utilized to assess the process and effect of both teachers' teaching and students' learning in a classroom environment, plays an increasingly crucial role in supervising and promoting education quality. With the rapid development of artificial intelligence (AI) technology, the concept of smart education has been constantly improved and gradually penetrated into all aspects of education application. Considering the dominant position of classroom teaching in elementary and undergraduate education, the introduction of AI technology into in-class teaching evaluation has become a research hotspot. In this paper, we propose a statistical modeling and ensemble learning-based comprehensive model, which is oriented towards in-class teaching evaluation by using AI technologies such as computer vision (CV) and intelligent speech recognition (ISR). Firstly, we present an index system including a set of teaching evaluation indicators combining traditional assessment scales with new values derived from CV and ISR-based AI analysis. Next, we design a comprehensive in-class teaching evaluation model by using both the analytic hierarchy process-entropy weight (AHP-EW) and AdaBoost-based ensemble learning (AdaBoost-EL) methods. Experiments not only demonstrate that the two modules in the model are respectively applicable to the calculation of indicators with different characteristics, but also verify the performance of the proposed model for AI-based in-class teaching evaluation. In this comprehensive in-class evaluation model, for students' concentration and participation, ensemble learning module is chosen with less root mean square error (RMSE) of 8.318 and 9.375. In addition, teachers' media usage and teachers' type evaluated by statistical modeling module approach higher accuracy with 0.905 and 0.815. Instead, the ensemble learning approaches the accuracy of 0.73 in evaluating teachers' style, which performs better than the statistical modeling module with the accuracy of 0.69.Broadband Power Line communication is considered as one of possible communication technologies for the buildings communication infrastructure in the concept of Smart Building. The possible applications where BPL (Broadband over Power Lines) solution can be used for communication in the concept of Smart Building are Power Quality (PQ) measurement, Electric Vehicle or Micro Grids and Distribution Generation (DG). This article should help to determine clear performance possibilities of BPL for an implementation in Smart Building especially due to a large amount of overhead caused by cybersecurity and the protocol overhead. The possibilities of BPL were measured with five different BPL solutions. The results show a sufficient throughput on the application layer for Smart Building application, because, in the literature, various throughput limits are introduced. According to related work, there are missing measurements on the application layer for laboratory conditions as well as compared with real field measurements.