The demand for donkey hides for ejiao, a Traditional Chinese Medicine, has resulted in rapidly increasing prices for donkey hides and donkeys. This has put pressure on donkey populations globally and has implications for donkey welfare and the livelihoods of those who rely on donkeys as working animals. The aim of the research was to explore the feasibility of setting up new donkey farming systems to supply the rising demand for ejiao using a system dynamics model of donkey production. Results show that the size of the initial female breeding herd, reproductive performance, age of reproduction, percentage of female births and average breeding life of donkeys are key variables affecting the time to build up the donkey population to supply the demand for hides, which will be at least ten to fifteen years. The implications of this are (i) prices for donkey hides will continue to increase, (ii) companies producing ejiao will use other ingredients, (iii) China will continue to source donkey hides from around the world, and (iv) there will be continued theft and illegal trade of donkeys and concerns for rural households reliant on donkeys for their livelihoods and adverse impacts on donkey welfare.The increasing prevalence of Alzheimer's disease (AD) has become a global phenomenon presenting serious social and health challenges. For detecting early molecular changes in the disease, several techniques to measure varied species of amyloid beta in the peripheral blood have been recently developed, but the efforts to associate them with cognitive assessments have yet to produce sufficient data.  https://www.selleckchem.com/products/GW501516.html  We prospectively collected participants from the consecutive population who visited our center for brain health screening. In total, 97 participants (FM = 5839) aged 69.4 ± 7.52 were assessed. Participants performed the Korean version of the Consortium to Establish a Registry for Alzheimer's disease (CERAD-K), the clinical dementia rating (CDR), plasma oligomeric amyloid-β (OAβ) level tests, routine blood tests, ApoE genotype, and brain MRI. Among total population, 55.7% had a CDR of 0, and 40.2% had a CDR of 0.5. The results showed that word memory and word recall, and the total scores of the CERAD-K were negatively correlated with the plasma OAβ level. With a cut-off value of 0.78 ng/mL for the OAβ level and a -1.5 standard deviation of age/sex/education adjusted norms for the CERAD-K; naming, word memory, word recall, word recognition, and total score were significantly correlated with the OAβ level. No correlation between the OAβ level and mini-mental status examination was found. Our results demonstrate that the level of plasma OAβ was well correlated with the measure of cognitive function through the CERAD-K in the field data collected from consecutive populations. Studies on longitudinal comparisons with large cohorts will further validate the diagnostic value of plasma OAβ as a useful biomarker for screening AD and predicting progression.We propose a spectrometer-free refractive index sensor based on a graphene plasmonic structure. The spectrometer-free feature of the device is realized thanks to the dynamic tunability of graphene's chemical potential, through electrostatic biasing. The proposed sensor exhibits a 1566 nm/RIU sensitivity, a 250.6 RIU-1 figure of merit in the optical mode of operation and a 713.2 meV/RIU sensitivity, a 246.8 RIU-1 figure of merit in the electrical mode of operation. This performance outlines the optimized operation of this spectrometer-free sensor that simplifies its design and can bring terahertz sensing one step closer to its practical realization, with promising applications in biosensing and/or gas sensing.Human interaction recognition technology is a hot topic in the field of computer vision, and its application prospects are very extensive. At present, there are many difficulties in human interaction recognition such as the spatial complexity of human interaction, the differences in action characteristics at different time periods, and the complexity of interactive action features. The existence of these problems restricts the improvement of recognition accuracy. To investigate the differences in the action characteristics at different time periods, we propose an improved fusion time-phase feature of the Gaussian model to obtain video keyframes and remove the influence of a large amount of redundant information. Regarding the complexity of interactive action features, we propose a multi-feature fusion network algorithm based on parallel Inception and ResNet. This multi-feature fusion network not only reduces the network parameter quantity, but also improves the network performance; it alleviates the network degradation caused by the increase in network depth and obtains higher classification accuracy. For the spatial complexity of human interaction, we combined the whole video features with the individual video features, making full use of the feature information of the interactive video. A human interaction recognition algorithm based on whole-individual detection is proposed, where the whole video contains the global features of both sides of action, and the individual video contains the individual detail features of a single person. Making full use of the feature information of the whole video and individual videos is the main contribution of this paper to the field of human interaction recognition and the experimental results in the UT dataset (UT-interaction dataset) showed that the accuracy of this method was 91.7%.The increasing prevalence of antibiotic resistance is a threat to human health, particularly within vulnerable populations in the hospital and acute care settings. This leads to increasing healthcare costs, morbidity, and mortality. Bacteria rapidly evolve novel mechanisms of resistance and methods of antimicrobial evasion. Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii have all been identified as pathogens with particularly high rates of resistance to antibiotics, resulting in a reducing pool of available treatments for these organisms. Effectively combating this issue requires both preventative and reactive measures. Reducing the spread of resistant pathogens, as well as reducing the rate of evolution of resistance is complex. Such a task requires a more judicious use of antibiotics through a better understanding of infection epidemiology, resistance patterns, and guidelines for treatment. These goals can best be achieved through the implementation of antimicrobial stewardship programs and the development and introduction of new drugs capable of eradicating multi-drug resistant Gram-negative pathogens (MDR GNB).