The influence of Gd-DOTA ratios conjugating PLGA-PEG micelles encapsulated IR-1061 in bimodal over–1000 nm near–infrared fluorescence and magnetic resonance imaging

Multimodal imaging can provide multidimensional information for understanding concealed microstructures or bioprocesses in biological objects. The combination of over–1000 nm near–infrared (OTN–NIR) fluorescence imaging and magnetic resonance (MR) imaging is...

Electronic Guides on Websites of Russian Libraries: Types, Topics, Structure

The problem of a user orientation in modern information resources is raised. The role of electronic guides as a means of multidimensional information search is noted. The authors of the article translate the previously proposed definition of the concept of “electronic bibliographic guide” and reveal its significant features as a polystructural phenomenon. The authors analyze electronic bibliographic guides presented on the websites of federal and central libraries of the subjects of the Russian Federation. Their multidimensional classification is proposed. It takes into account 19 division bases. The results of the proposed study of these resources are presented. The characteristics of electronic guides on the following features are given: the method of access to reflected objects; access mode; language; the breadth of thematic coverage; belonging to a certain field of knowledge; a storage medium; the presence of a printed analogue. The three-part structure of electronic guides is considered, including an introductory article, the main part and auxiliary pointers and/or a search bar. The results and key findings can be used to improve the creation of electronic guides and improve the quality of electronic information resources created in libraries.

Neural encoding of perceived patch value during competitive and hazardous virtual foraging

Natural observations suggest that in safe environments, organisms avoid competition to maximize gain, while in hazardous environments the most effective survival strategy is to congregate with competition to reduce the likelihood of predatory attack. We probed the extent to which survival decisions in humans follow these patterns, and examined the factors that determined individual-level decision-making. In a virtual foraging task containing changing levels of competition in safe and hazardous patches with virtual predators, we demonstrate that human participants inversely select competition avoidant and risk diluting strategies depending on perceived patch value (PPV), a computation dependent on reward, threat, and competition. We formulate a mathematically grounded quantification of PPV in social foraging environments and show using multivariate fMRI analyses that PPV is encoded by mid-cingulate cortex (MCC) and ventromedial prefrontal cortices (vMPFC), regions that integrate action and value signals. Together, these results suggest humans utilize and integrate multidimensional information to adaptively select patches highest in PPV, and that MCC and vMPFC play a role in adapting to both competitive and predatory threats in a virtual foraging setting.

Forecasting the Development of Self-Driving Technology in China by Multidimensional Information

Due to the demand for safety and convenience in traveling, self-driving technology has developed very fast in the past decades. In this paper, a novel technology forecasting model is developed. The topic-based text mining and expert judgment approaches are combined to forecast the technology trends efficiently and accurately. To improve the reliability of the results, multidimensional information including scientific papers, patents, and industry data is considered. Then, the model is utilized to forecast the development trends of self-driving technology in China. Data ranging from 2002 to 2019 are adopted with proper data cleaning. Topic clustering for papers and patents is performed, and the hierarchical structures are constructed. On this basis, the results of technology’s evolution based on papers and patents are compared and the development trends are obtained. With these results, it is speculated that technology on “Decision” will be the next hotspot in patents. The research results of this paper will provide reference and guidance for Chinese enterprises and government in decision-making on self-driving technology.

Single caudate neurons encode temporally discounted value for formulating motivation for action

The term ‘temporal discounting’ describes both choice preferences and motivation for delayed rewards. Here we show that neuronal activity in the dorsal part of the primate caudate head (dCDh) signals the temporally discounted value needed to compute the motivation for delayed rewards. Macaque monkeys performed an instrumental task, in which visual cues indicated the forthcoming size and delay duration before reward. Single dCDh neurons represented the temporally discounted value without reflecting changes in the animal’s physiological state. Bilateral pharmacological or chemogenetic inactivation of dCDh markedly distorted the normal task performance based on the integration of reward size and delay, but did not affect the task performance for different reward sizes without delay. These results suggest that dCDh is involved in encoding the integrated multidimensional information critical for motivation.

Interactive Evolution of Multidimensional Information in Social Media for Public Emergency: A Perspective from Optics Scattering

Most of the current research on the information analysis of social media (SM) for public emergency focused on a single dimension such as emotion while neglecting the interaction between multidimensional information. Therefore, in this study, an information dispersing–superimposing model is proposed to explain the implicit regularity of the impact within a symbol, sentiment, and context information and their dependent evolution on the SM. Information hue, saturation, and flux (HSF) are defined to measure the interaction process. An online event was selected to verify the concept and hypothesis of this study. The results proved that the interaction among multidimensional information did exist on the SM for a public emergency. The turning points of information dispersing–superimposing often emerged when the number of online users involved had significant changes, and sentiment and context information were showed to have a strong interaction relationship and tended to be spread at the same time. It was also manifested that the dominant information component was varied at each stage of the emergency. This paper is one of the first to study the interaction of multidimensional information on the SM derived from optics scattering. The findings of the study will try to provide a theoretical explanation for why certain information components may be enhanced during the online dissemination and suggest practical support for the information predictions and interface design for SM.

Optimization of Multidimensional Clinical Information System for Schizophrenia

Schizophrenia is a serious mental disease whose pathogenesis has not been fully elucidated. Its clinical evaluation and diagnosis still highly depend on the clinical experience of doctors. It is of great scientific value and clinical significance to study the inducing factors and neuropathological mechanism of schizophrenia. Based on the four research problems of schizophrenia, this paper analyzes the data types that need to be stored in clinical trials and scientific research, including basic information, case report data, neuropsychological and cognitive function evaluation, magnetic resonance data, electroencephalogram (EEG) data, and intestinal flora data. Through the demand analysis of the system, including the data management part, data analysis part, the functional demand of the system management part, and the overall nonfunctional demand of the system, the overall architecture design, functional module division, and database table structure design of the system are completed. Adopting Browser/Server (B/S) architecture and front-end and back-end separation mode and applying Java and Python programming language, based on spring framework and database, a multidimensional information management system for schizophrenia is designed and implemented, which includes four modules: data analysis, data management, system management, and security control. In addition, each functional module of the system is designed and implemented in detail, and the software operation flow of each module is illustrated with the sequence diagram. Finally, the multidimensional data of schizophrenia collected in our laboratory were used for system test to verify whether the system can meet the needs of clinical big data management of schizophrenia and the multidimensional information management system of schizophrenia can meet the needs of clinical big data management. The information management system helps schizophrenic researchers to carry out data management and data analysis. It also has advantages that are easy to use, safe, and efficient and has strong scalability in data management, data analysis, and scalability. It reflects the innovation of the system and provides a good platform for the management, research, and analysis of clinical big data of schizophrenia.