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Rapid urbanization leads to fragmentation and reduced connectivity of urban landscapes, endangering regional biodiversity conservation and sustainable development. Constructing a red, green, and blue spatial ecological network is an effective way to alleviate ecological pressure and promote economic development. Using circuit theory, hydrological analysis, and suitability analysis, this study constructs a composite ecological network under urban–rural integration. The results show the following: (1) A total of 22 ecological corridors with a length of 349.20 km, 22 ecological pinch points, and 22 ecological barrier points are identified in the municipal area, mainly distributed in Haidong Town. There are 504 stormwater corridors, which are more evenly distributed, 502 riverfront landscape corridors, and 130 slow-moving landscape corridors. (2) A total of 20 ecological corridors, with a length of 99.23 km, 19 ecological pinch points, and 25 barrier points were identified in the main urban area, and most of them are located in the ecological corridors. There are 71 stormwater corridors, mainly located in the northwestern forest area, 71 riverfront recreation corridors, and 50 slow-moving recreation corridors. (3) Two scales of superimposed ecological source area of 3.65 km2, and eleven ecological corridors, are primarily distributed between Erhai Lake and Xiaguan Town. There are two superimposed stormwater corridors and fourteen recreational corridors. The eco-nodes are mostly distributed in the east and south of Dali City; wetland nodes are mainly situated in the eighteen streams of Cangshan Mountain; and landscape nodes are more balanced in spatial distribution. The study results can provide a reference for composite ecological network construction. [ABSTRACT FROM AUTHOR]

Decision prediction based on neurophysiological signals is of great application value in many real‐life situations, especially in human–AI collaboration or counteraction. Single‐trial analysis of electroencephalogram (EEG) signals is a very valuable step in the development of an online decision‐prediction system. However, previous EEG‐based decision‐prediction methods focused mainly on averaged EEG signals of all decision‐making trials to predict an individual's general decision tendency (e.g., risk seeking or aversion) over a period rather than on a specific decision response in a single trial. In the present study, we used a rock–paper–scissors game, which is a common multichoice decision‐making task, to explore how to predict participants' single‐trial choice with EEG signals. Forty participants, comprising 20 females and 20 males, played the game with a computer player for 330 trials. Considering that the decision‐making process of this game involves multiple brain regions and neural networks, we proposed a new algorithm named common spatial pattern‐attractor metagene (CSP‐AM) to extract CSP features from different frequency bands of EEG signals that occurred during decision making. The results showed that a multilayer perceptron classifier achieved an accuracy significantly exceeding the chance level among 88.57% (31 of 35) of participants, verifying the classification ability of CSP features in multichoice decision‐making prediction. We believe that the CSP‐AM algorithm could be used in the development of proactive AI systems. [ABSTRACT FROM AUTHOR]

Theories on procrastination propose that associating tasks with higher valued incentive outcomes results in less task procrastination. However, it remains unknown how representation of incentive outcomes and task‐outcome association are mediated by the human brain. Using event‐related functional magnetic resonance imaging, we scanned human participants while they were thinking about both tasks and the incentive outcomes each task can yield in an unconstrained way. Results showed that tasks that are more likely to be procrastinated are associated with less value in incentive outcomes. Interestingly, procrastination was more likely if it was more difficult for participants to associate a task with its valued incentives when thinking about the task (i.e., the decreased task‐outcome association). On the neural level, higher value of rewarding outcomes was correlated with increased putamen activations, which further negatively predicted task procrastination. On the other hand, when participants were associating tasks with the incentive outcomes, the decreasing task‐outcome association corresponded to decreasing activation in putamen, and a decreasing hippocampus‐putamen coupling which further mediated the effect of the insufficient task‐outcome association on procrastination. In particular, the current findings show that procrastination is more likely when people are less able to associate tasks with highly valued incentives, which is accompanied by reduced hippocampal–striatal interactions during task construction. [ABSTRACT FROM AUTHOR]

BackgroundMobile-based interventions appear to be promising in ameliorating huge burdens experienced by patients with type 2 diabetes. However, it is unclear how effective mobile-based interventions are in glycemic management of patients with type 2 diabetes based on real-world evidence. ObjectiveThis study aimed to evaluate the effectiveness of a mobile-based intervention on glycemic control in patients with type 2 diabetes based on real-world population data. MethodsThis retrospective, propensity score-matched cohort study analyzed longitudinal data from a clinical electronic health database. The study population included 37,913 patients with type 2 diabetes at cohort entry between October 1, 2016, and July 31, 2018. A total of 2400 patients were matched 1:1, using propensity score matching, into the usual care and mobile health (mHealth) groups. The primary outcomes of glycemic control included control rates of glycated hemoglobin (HbA1c), fasting blood glucose (FBG), and postprandial 2-hour blood glucose (P2BG). Mean values and variation trends of difference with 95% CI were the secondary outcomes. The general linear model was used to calculate repeated-measures analyses of variance to examine the differences between the two groups. Subgroup and sensitivity analyses were performed. ResultsOf the 2400 patients included in the analysis, 1440 (60.00%) were male and the mean age was 52.24 years (SD 11.56). At baseline, the control rates of HbA1c, FBG, and P2BG in the mHealth and usual care groups were 45.75% versus 47.00% (P=.57), 38.03% versus 32.76% (P=.07), and 47.32% versus 47.89% (P=.83), respectively. At the 3-, 6-, 9-, and 12-month follow-ups, the mHealth group reported higher control rates of HbA1c than did the usual care group: 69.97% versus 46.06% (P

Thioamide peptides were synthesized in a straightforward one-pot process via the linkage of diverse natural amino acids in the presence of thiolphosphonate and trichlorosilane, wherein carbonyl groups were replaced with thiono compounds with minimal racemization. Experimental and computational mechanistic studies demonstrated that the trichlorosilane enables the activation of carboxylic acids via intense interactions with the Si-O bond, followed by coupling of the carboxylic acids with thiolphosphonate to obtain the key intermediate S-acyl dithiophosphate. Silyl-activated quadrangular metathesis transition states afforded the thioamide peptides. The potential applications of these thioamide peptides were further highlighted via late-stage linkages of diverse natural products and pharmaceutical drugs and the thioamide moiety., (© 2023 Wiley-VCH GmbH.)

Procrastination, an irrational delay of intended action, has caused harms in many life domains. Although procrastination has a robust link with the dorsolateral prefrontal cortex (DLPFC), the causal role of DLPFC in this behavior remains unclear. A recent temporal decision model (TDM) proposed that people pit task aversiveness against outcome value to decide to procrastinate or not. In short, people would procrastinate if task aversiveness has a stronger effect than outcome value. According to the TDM, the DLPFC might reduce procrastination by inhibiting task aversiveness, or amplifying outcome value, or both. The present study tested those possibilities by investigating whether brain stimulation on DLPFC changes procrastination and its underlying mechanism. One hundred and three participants with high procrastination were randomly assigned to receive either active or sham stimulation over the left (active, n = 27; sham, n = 27) or right (active, n = 25; sham, n = 24) DLPFC and rated task aversiveness, outcome value and task-execution willingness toward their self-planned real-life tasks before and after stimulation. We found that active stimulation of the left DLPFC significantly boosted task-execution willingness. This left DLPFC stimulation also changed subjects' evaluation of tasks such that decreasing task aversiveness and increasing outcome value. Causal mediation analyses further revealed that stimulation of the left DLPFC enhances willingness for task completion through increasing outcome value. Overall these results provide the first evidence that neuromodulation of the left DLPFC could improve timely task-execution willingness via increasing the outcome value, which offers new insights for treating individuals with severe or even pathological procrastination. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Procrastination, the voluntary and irrational delay of an intended course of action, has troubled individuals and society extensively. Various studies have been conducted to explain why people procrastinate and to explore the neural substrates of procrastination. First, research has identified many contributing factors to procrastination. Specifically, task aversiveness, future incentives, and time delay of these incentives have been confirmed as three prominent task characteristics that affect procrastination. On the other hand, self-control and impulsivity have been identified as two most predictive traits of procrastination. After identifying contributing factors, two important theories proposed to explain procrastination by integrating these factors are reviewed. Specifically, an emotion-regulation perspective regards procrastination as a form of self-regulation failure that reflects giving priority to short-term mood repair over achieving long-term goals. However, temporal motivation theory explains why people's motivation to act increases when time approaches a deadline with time discounting effect. To further specify the cognitive mechanism underlying procrastination, this study proposes a novel theoretical model which clarifies how the motivation to act and the motivation to avoid vary differently when delaying a task, explaining why people decide not to act now but are willing to act in the future. Of note, few recent studies have investigated neural correlates of procrastination. Specifically, it was revealed that individual differences in procrastination are correlated with structural abnormalities and altered spontaneous metabolism in the parahippocampal cortex and the prefrontal cortex, which might contribute to procrastination through episodic future thinking or memory and emotion regulation, respectively. This article is categorized under: Economics > Individual Decision Making Psychology > Theory and Methods Psychology > Emotion and Motivation Psychology > Reasoning and Decision Making., (© 2019 Wiley Periodicals, Inc.)

Objective: To explore the expression of thyroid transcription factor-1 (TTF-1) in thyroid tumors and in different parts of follicular epithelium and the correlation of expression of TTF-1 with the expression of RET, galectin-3 (Gal-3) and mucin-1 (MUC1) genes., Methods: One hundred thirty-three samples of resected thyroid tumors were examined by streptavidin/peroxidase (S-P) immunohistochemical technique to detect the expression of TTF-1 and RET, Gal-3, and MUC1 genes., Results: (1) TTF-1 was expressed in the nuclei and cytoplasm of different kinds of tumor cells and normal cells around the tumors. There was no significant difference between the expression of TTF-1 in nuclei of malignant thyroid tumor cells and that in nuclei of benign thyroid tumor cells (P > 0.05). The positive expression rate of TTF-1 was 27.40% in cytoplasm of benign tumor and was 66.10% in cytoplasm of malignant tumor was 66.10% (P < 0.05). (2) The expression rate of RET gene was 38.9% in thyroid adenoma, 88.4% in papillary carcinoma, and 87.5% in follicular carcinoma. The difference of expression rate of RET gene between adenoma and both of papillary and follicular carcinomas was statistically significant (P < 0.05). (3) The expression rate of MUC1 was 23.3% in benign tumor and 50.9% in malignant tumor. The expression rate of MUC1 was lower in benign thyroid diseases (nodular goiter and adenoma) than in thyroid papillary carcinoma and follicular carcinoma (P < 0.05). (4) The expression rate of Gal-3 gene was 38.4% in benign tumor and 88.1% in malignant tumor. (5) The expression rates of Gal-3 and MUC1 in benign lesions (nodular goiter and adenoma) were lower than those in thyroid papillary and follicular carcinomas (P < 0.05). The expression of Gal-3 and that of MUC1 in thyroid carcinomas were fundamentally parallel. However, the sensitivity of Gal-3 was higher than that of MUC1. In part of adenomas Gal-1 and MUC1 were positive locally simultaneously. The expression of TTF-1 in cytoplasm was associated with that of Gal-3 and MUC1., Conclusion: The expression of TTF-1 in nucleus is a phenomenon common to both normal and pathological thyroid follicles. Combined tests of RET, Gal-3 and MUC1 may act as the diagnostic markers to distinguish benign follicular tumor from malignant ones. Expression of TTF-1 in cytoplasm is probably a characteristic of malignant phenotypes of thyroid tumors.