Internet and smartphone addiction have become important social issues. Various studies have demonstrated their association with clinical and psychological factors, including depression, anxiety, aggression, anger expression, and behavioral inhibition, and behavioral activation systems. However, these two addictions are also highly correlated with each other, so the consideration of the relationship between internet and smartphone addiction can enhance the analysis. In this study, we considered the copula regression model to regress the bivariate addictions on clinical and psychological factors. Real data analysis with 555 students (age range 14-15 years; males, N = 295; females, N = 265) from South Korean public middle schools is illustrated. By fitting the copula regression model, we investigated the dependency between internet and smartphone addiction and determined the risk factors associated with the two addictions. Furthermore, by comparing the model fits of the copula model with linear regression and generalized linear models, the best copula model was proposed in terms of goodness of fit. Our findings revealed that internet and smartphone addiction are not separate problems, and that associations between them should be considered. Psychological factors, such as anxiety, the behavioral inhibition system, and aggression were also significantly associated with both addictions, while ADHD symptoms were related to internet addiction only. We emphasize the need to establish policies on the prevention, management, and education of addiction.Chronic low-grade inflammation negatively impacts health and is associated with aging and obesity, among other health outcomes. A large number of immune mediators are present in the digestive tract and interact with gut bacteria to impact immune function. The gut microbiota itself is also an important initiator of inflammation, for example by releasing compounds such as lipopolysaccharides (LPS) that may influence cytokine production and immune cell function. Certain nutrients (e.g., probiotics, ω-3 fatty acids [FA]) may increase gut microbiota diversity and reduce inflammation. Lactobacilli and Bifidobacteria, among others, prevent gut hyperpermeability and lower LPS-dependent chronic low-grade inflammation. Furthermore, ω-3 FA generate positive effects on inflammation-related conditions (e.g., hypertriglyceridemia, diabetes) by interacting with immune, metabolic, and inflammatory pathways. https://www.selleckchem.com/products/stat-in-1.html Ω-3 FA also increase LPS-suppressing bacteria (i.e., Bifidobacteria) and decrease LPS-producing bacteria (i.e., Enterobacteria). Additionally, ω-3 FA appear to promote short-chain FA production. Therefore, combining probiotics with ω-3 FA presents a promising strategy to promote beneficial immune regulation via the gut microbiota, with potential beneficial effects on conditions of inflammatory origin, as commonly experienced by aged and obese individuals, as well as improvements in gut-brain-axis communication.As an important paradigm of spontaneous brain-computer interfaces (BCIs), motor imagery (MI) has been widely used in the fields of neurological rehabilitation and robot control. Recently, researchers have proposed various methods for feature extraction and classification based on MI signals. The decoding model based on deep neural networks (DNNs) has attracted significant attention in the field of MI signal processing. Due to the strict requirements for subjects and experimental environments, it is difficult to collect large-scale and high-quality electroencephalogram (EEG) data. However, the performance of a deep learning model depends directly on the size of the datasets. Therefore, the decoding of MI-EEG signals based on a DNN has proven highly challenging in practice. Based on this, we investigated the performance of different data augmentation (DA) methods for the classification of MI data using a DNN. First, we transformed the time series signals into spectrogram images using a short-time Fourier transfbserved after DA for the two datasets. In addition, the hybrid network CNN-DCGAN outperformed the other classification methods, with average kappa values of 0.564 and 0.677 for the two datasets.Although camelina [Camelina sativa (L.) Crantz] is a good source of protein, antioxidants, and polyunsaturated fatty acids, its antinutritional compounds limit its use in animal feeding. The aim of this study was to verify the effect of feeding laying hens with up to 20% of camelina cake from a breeding line containing a low level of glucosinolates on performance, welfare, and eggshell quality. Two hundred and forty Hy-Line® hens from 18 to 51 weeks of age were divided into three treatments control (C), camelina cake 10% (CAM10), and camelina cake 20% (CAM20). Egg number was recorded daily, while egg weight, feed consumption, and mortality were recorded weekly. At 24 and 43 weeks of hen age, shell resistance to fracture was measured. Our results demonstrate no detrimental effects for CAM10 and CAM20 diets on feed intake, growth performance, and welfare. No difference in egg production was detected among the diets. The significant (p less then 0.05) interaction of diet and age factors suggest that the addition of camelina cake, up to 20%, likely protects the eggshell of older hens. Our findings confirm that camelina cake might be an alternative and sustainable protein source for hens.Thermotolerant vaccines greatly improved the reach and impact of large-scale vaccination programs to eliminate diseases such as smallpox, polio and rinderpest. A recent study demonstrated that the potency of the Nobivac® Canine Rabies vaccine was not impacted following experimental storage at 30 °C for three months. We conducted a study to develop a passive cooling device (PCD) that could store thermotolerant vaccines under fluctuating subambient temperatures. Through a participatory process with local communities in Northern Tanzania, we developed innovative PCD designs for local manufacture. A series of field experiments were then carried out to evaluate the effectiveness of five PCDs for vaccine storage under varying climatic conditions. Following iterative improvement, a final prototype "Zeepot Clay" was developed at the cost of US$11 per unit. During a further field-testing phase over a 12-month period, the internal temperature of the device remained below 26 °C, despite ambient temperatures exceeding 42 °C.