A Bibliometric Analysis of Literature on Vegetable Prices at Domestic and International Markets-A Knowledge Graph Approach

Vegetable prices play an important role in people’s daily lives globally. However, there is very little research that has systematically analyzed and discussed the existing research. Therefore, in order to narrow this gap in the literature, there is a need for an extensive and macro-level study of vegetable price research. By sorting out a large volume of documents, This paper presents a visual representation of the vegetable price research literature in the Web of Science and CNKI databases; it includes three perspectives of the cooperative network, co-occurrence network and co-cited network, and draws scientific knowledge map, to acquire a good understanding of the current situation of vegetable price research, hot issues, clearly shows the focus of the research, summaries the fluctuation pattern of vegetable price, deeply analyses the influencing factors of vegetable price fluctuation, and find out the connection between related scholars and the correlation existing in each research content. The results show that scholars at home and abroad have conducted research from the perspectives of vegetable price influencing factors, forecasting and early warning, and insurance systems, but they are only limited to some regions, and some vegetable varieties, and the forecasting and early warning of vegetable prices are not accurate enough, the insurance system is not perfect, and a complete price influencing mechanism has not yet been proposed. The aim of this study is to make a significant contribution to the scientific community and industry practitioners by providing a comprehensive understanding of the latest status, popular keywords and topics, and emerging areas of vegetable price research. In addition, this study will be a useful and valuable reference and guide for researchers interested in this field.

CT appearances, patterns of progression, and follow-up of COVID-19: evaluation on thin-section CT

Background To retrospectively analyze CT appearances and progression pattern of COVID-19 during hospitalization, and analyze imaging findings of follow-up on thin-section CT. Methods CT findings of 69 patients with COVID-19 were evaluated on initial CT, peak CT, and pre-discharge CT. CT pattern were divided into four types on CT progression. Lesion percentage of pulmonary lobe (lobe score) was graded. Correlation analysis was made between scores and intervals. 53 patients were followed up by CT. Results Among 69 patients, 33.3% exhibited improvement pattern, 65.2% peak pattern, 1.5% deterioration pattern, and 0% fluctuation pattern. The lobe scores were positively correlated with most of intervals. It was more common to observe consolidation, pleural thickening and pleural effusion on the peak CT, and irregular line and reticulation on pre-discharge CT. The peak-initial interval were shortened when the initial CT with consolidation and pleural thickening. The intervals were extended when the irregular lines appeared on peak CT and reticulation on pre-discharge CT. Among 53 follow-up patients, 37.7% showed normal chest CT, and 62.3% showed viral pneumonia remained that mainly included GGO (100.0%) and irregular lines (33.3%). Conclusions COVID-19 displayed different appearances on CT as progressing. The peak pattern was the most common progression pattern. The CT appearances showed closely related to the intervals. The COVID-19 pneumonia can be remained or completely absorbed on CT with follow-up.

Daily Fluctuation of Facial Pore Area, Roughness and Redness among Young Japanese Women; Beneficial Effects of Galactomyces Ferment Filtrate Containing Antioxidative Skin Care Formula

Young women often complain about the daily fluctuation of their facial skin conditions. However, no objective study has been carried out on such changes. This study is aimed at quantitatively elucidating daily skin fluctuation and evaluating the efficacy of cosmetic skin care treatment. We developed the first portable and self-guided facial skin imaging device (eMR Pro) to reproducibly capture facial images at home. Two 8 week clinical studies were then conducted to analyze daily skin fluctuation of facial pore areas, roughness and redness in young Japanese women (n = 47 in study 1 and n = 57 in study 2) by collecting facial images three times a day, during the morning after wake-up, during the morning after face wash, and during the evening after face wash. After a 4 week baseline measurement period (week -4 to week -1), all subjects applied Galactomyces ferment filtrate (GFF, Pitera®) skin care formula twice a day for 4 weeks (week 1 to week 4). These three skin conditions did exhibit different fluctuation patterns. The pore area and roughness showed the “morning after wake-up”-largest fluctuation pattern, whereas redness showed the “evening after face wash”-largest fluctuation pattern. GFF treatment significantly reduced the net values and delta fluctuation of pore area, roughness, and redness, which were consistently observed in two studies. In conclusion, the daily fluctuation of facial skin conditions is potentially a new target field for investigating healthy skin maintenance.

Synchrony in Broadband Fluctuation and the 2008 Financial Crisis

We propose phase-like characteristics in scale-free broadband processes and consider fluctuation synchrony based on the temporal signature of significant amplitude fluctuation. Using wavelet transform, successful captures of similar fluctuation pattern between such broadband processes are demonstrated. The application to the financial data leading to the 2008 financial crisis reveals the transition towards a qualitatively different dynamical regime with many equity price in fluctuation synchrony. Further analysis suggests an underlying scale free “price fluctuation network” with large clustering coefficient.

Synchrony in Broadband Fluctuation and the 2008 Financial Crisis

We propose phase-like characteristics in scale-free broadband processes and consider fluctuation synchrony based on the temporal signature of significant amplitude fluctuation. Using wavelet transform, successful captures of similar fluctuation pattern between such broadband processes are demonstrated. The application to the financial data leading to the 2008 financial crisis reveals the transition towards a qualitatively different dynamical regime with many equity price in fluctuation synchrony. Further analysis suggests an underlying scale free “price fluctuation network” with large clustering coefficient.

Multidimensional Emotion Recognition Based on Semantic Analysis of Biomedical EEG Signal for Knowledge Discovery in Psychological Healthcare

Electroencephalogram (EEG) as biomedical signal is widely applied in the medical field such as the detection of Alzheimer’s disease, Parkinson’s disease, etc. Moreover, by analyzing the EEG-based emotions, the mental status of individual can be revealed for further analysis on the psychological causes of some diseases such as cancer, which is considered as a vital factor on the induction of certain diseases. Therefore, once the emotional status can be correctly analyzed based on EEG signal, more healthcare-oriented applications can be furtherly carried out. Currently, in order to achieve efficiency and accuracy, diverse amounts of EEG-based emotions recognition methods generally extract features by analyzing the overall characteristics of signal, along with optimization strategy of channel selection to minimize the information redundancy. Those methods have been proved their effectiveness, however, there still remains a big challenge when applied with single channel information for emotion recognition task. Therefore, in order to recognize multidimensional emotions based on single channel information, an emotion quantification analysis (EQA) method is proposed to objectively analyze the semantically similarity between emotions in valence-arousal domains, and a multidimensional emotion recognition (EMER) model is proposed on recognizing multidimensional emotions according to the partial fluctuation pattern (PFP) features based on single channel information, and result shows that even though semantically similar emotions are proved to have similar change patterns in EEG signals, each single channel of 4 frequency bands can efficiently recognize 20 different emotions with an average accuracy above 93% separately.

The surprising role of the default mode network in naturalistic perception

The default mode network (DMN) is a group of high-order brain regions recently implicated in processing external naturalistic events, yet it remains unclear what cognitive function it serves. Here we identified the cognitive states predictive of DMN fMRI coactivation. Particularly, we developed a state-fluctuation pattern analysis, matching network coactivations across a short movie with retrospective behavioral sampling of movie events. Network coactivation was selectively correlated with the state of surprise across movie events, compared to all other cognitive states (e.g. emotion, vividness). The effect was exhibited in the DMN, but not dorsal attention or visual networks. Furthermore, surprise was found to mediate DMN coactivations with hippocampus and nucleus accumbens. These unexpected findings point to the DMN as a major hub in high-level prediction-error representations.

Флуктуации электронной плотности и фазовый переход в α-титане

It is shown that the topological features of the electronic structure of α-titanium lead to the appearance of temperature-induced fluctuations of the electron density, which disappear near the temperature of the phase transition from the hcp (α-phase) to the bcc (β-phase). The experimen-tally observed linear temperature increase in the magnetic susceptibility in the beta-phase and its jump during the transition to the β-phase are described. The considered fluctuation pattern de-scribes a sharp decrease in the electron entropy and softening of the longitudinal phonon modes associated with the electron-ion interaction. It is shown that the temperature of the phase transition in α-titanium depends on the position of the Fermi level, which can be changed by introducing impurities.