Identifying the generator matrix of a stationary Markov chain using partially observable data.

Given that most states in real-world systems are inaccessible, it is critical to study the inverse problem of an irreversibly stationary Markov chain regarding how a generator matrix can be identified using minimal observations. The hitting-time distribution of an irreversibly stationary Markov chain is first generalized from a reversible case. The hitting-time distribution is then decoded via the taboo rate, and the results show remarkably that under mild conditions, the generator matrix of a reversible Markov chain or a specific case of irreversibly stationary ones can be identified by utilizing observations from all leaves and two adjacent states in each cycle. Several algorithms are proposed for calculating the generator matrix accurately, and numerical examples are presented to confirm their validity and efficiency. An application to neurophysiology is provided to demonstrate the applicability of such statistics to real-world data. This means that partially observable data can be used to identify the generator matrix of a stationary Markov chain.

Abnormalities of the Amygdala in schizophrenia: a real world study.

BACKGROUND: Amygdala plays an important role in schizophrenia (SC), but its mechanisms are still unclear. Therefore, we investigated the relationship between the resting-state magnetic resonance imaging (rsMRI) signals of the amygdala and cognitive functions, providing references for future research in this area. METHODS: We collected 40 drug-naïve SC patients and 33 healthy controls (HC) from the Third People's Hospital of Foshan. We used rsMRI and the automatic segmentation tool to extract the structural volume and local neural activity values of the amygdala and conducted Pearson correlation analysis with the Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) scores. Finally, we compared the clinical data, as well as the volume and functional changes of the amygdala in SC patients before and after treatment. RESULTS: Compared with HC, SC had widespread cognitive impairments, significant abnormalities in left amygdala function, while the reduction in volume of SC was not significant. Further Pearson correlation analysis with Bonferroni correction showed that only Immediate memory (learning) was significantly negatively correlated with fractional amplitude of low-frequency fluctuation (FALFF, r = -0.343, p = 0.001, p' = 0.014 (Bonferroni correction)). When compared and analyzed the data difference of SC before and after treatment, we found that immediate memory and delayed memory of SC showed varying degrees of recovery after treatment (tlearning = -2.641, plearning = 0.011; tstory memory = -3.349, pstory memory = 0.001; tlist recall = -2.071, plist recall = 0.043; tstory recall = -2.424, pstory recall = 0.018). But the brain structure and function did not recover. CONCLUSION: There was significant dysfunction in the amygdala in SC, and after conventional treatment, the function of the amygdala did not improve with the improvement of clinical symptoms and cognitive function.

Attention in Attention Networks for Person Retrieval.

This paper generalizes the Attention in Attention (AiA) mechanism, in P. Fang et al., 2019 by employing explicit mapping in reproducing kernel Hilbert spaces to generate attention values of the input feature map. The AiA mechanism models the capacity of building inter-dependencies among the local and global features by the interaction of inner and outer attention modules. Besides a vanilla AiA module, termed linear attention with AiA, two non-linear counterparts, namely, second-order polynomial attention and Gaussian attention, are also proposed to utilize the non-linear properties of the input features explicitly, via the second-order polynomial kernel and Gaussian kernel approximation. The deep convolutional neural network, equipped with the proposed AiA blocks, is referred to as Attention in Attention Network (AiA-Net). The AiA-Net learns to extract a discriminative pedestrian representation, which combines complementary person appearance and corresponding part features. Extensive ablation studies verify the effectiveness of the AiA mechanism and the use of non-linear features hidden in the feature map for attention design. Furthermore, our approach outperforms current state-of-the-art by a considerable margin across a number of benchmarks. In addition, state-of-the-art performance is also achieved in the video person retrieval task with the assistance of the proposed AiA blocks.

[Triterpenoids from roots of Rosa laevigata].

To study the triterpenoids from the roots of Rosa laevigata. The silica gel column chromatography was used to separate the chemical constituents from the roots of Rosa laevigata Michx. HPLC was used to analyze its purity, chemical and spectroscopy methods were used to determine their structures. 12 constituents were isolated and identified as(2R, 19R)methyl 2-acetyloxy-19- hydroxyl-3-oxo-urs-12-en-28-carboxylate(1), pomonic acid (2), 18, 19-seco, 2α, 3α-dihydroxy-19-oxo-urs-11, 13(18)-dien-28-oic acid(3), swinhoeic acid (4), myrianthic acid(5), 2α, 3ß, 19α-trihydroxy-24-oxo-urs-12-en-oic acid (6), tormentic acid(7), arjunic acid (8), 1ß-hydroxyeuscaphic acid(9), quadranoside Ⅷ (10), alpinoside(11), rubuside B (12). Compounds 1-4, 6, 9, 11-12 were obtained from this plant for the first time. Compounds 2-4, 6, 11-12 were obtained from the genus Rosa for the first time.

[Thinking about evaluation of proprietary Chinese medicines containing toxic herbs during switch process of non-prescription drugs].

To enhance the scientific and fair evaluation about proprietary Chinese medicines containing toxic herbs during the switch process of non-prescription drugs, and to ensure those medicines to be used safely by the public in their self-medication. Combined with current research status of toxic herbs, the experience and knowledge accumulated in the practical work of selection and switch of OTC Chinese medicines for years, thinking about the feasible standards about evaluation and management of proprietary Chinese medicines containing toxic herbs at this stage. Initially established ideas and methods about evaluation of proprietary Chinese medicines containing toxic herbs during the switch process of non-prescription drugs. Basically solved the main problem currently faced by toxic herbs during the OTC switch process of proprietary Chinese medicines, effectively promoted the work on OTC switch, and had the important significance in making consumers use non-prescription drugs conveniently and safely.

[Quantitative determination of anethole in the fruit of Illicium verum from various places of Guangxi province].

The quantitative determination of anethole in the fruit of Illicium verum from various places of Guangxi province were determined by GC. The average recovery rate and the RSD are 102.31%, 1.78% respectively. The content of anethole in the fruit of Illicium verum in various places were all more than 4.5%.

[Studies on the extraction of ingredients from Chinese traditional medicine with CO2 supercritical fluid].

OBJECTIVE: To study the extraction technology with CO2 supercritical fluid in Chinese Traditional Medicine by extracting the anthraquinones ingredients from Salvia miltiorrhiza and Polygonum caspidatum. METHOD: Extractions were made under different pressure, temperature, extraction time, entrainer, and the extracts were analyzied by TLC and HPLC. RESULT: The technology could be used in extraction and isolation. Under certain conditions, different contents of the extracts could be obtained. CONCLUSION: CO2 supercritical fluid is good at extracing low polarity ingredients, and it shows the evident individurity in extraction of Chinese herb. The technological factors in industrial usage must be thought of all over.