Towards sustainable space research in France
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Sustainable supply chain management practices and performance: The moderating effect of stakeholder pressure
Currently, sustainable supply chain management practices have become an important strategy for firms to improve performance and gain competitive advantage. However, there is a current debate over the performance outcomes of sustainable supply chain management practices. Additionally, the role of stakeholder pressure is frequently overlooked. Drawing on Natural Resources-Based View and Stakeholder Theory, this study aims to elucidate the ambiguous connection between sustainable supply management, sustainable process management, stakeholder pressure and performance, and investigate the mediation role of sustainable process management and the moderation effect of stakeholder pressure. Our analysis, based on data collected from 235 Chinese manufacturing firms, reveals significant insights. First, stakeholder pressure positively moderates the relationship between sustainable process management and performance, while negatively moderates the relationship between sustainable supply management and performance. Second, sustainable process management has a complete mediation effect on the relationship between sustainable supply management and performance. The conclusion not only explains the inconsistent relationship between sustainable supply chain management practice and performance, but also reveals clearly the relationship between sustainable supply management and sustainable process management. Besides, it also highlights the difference in performance outcomes of sustainable supply management and sustainable process management under stakeholder pressures, and has valuable guidance to the practice of sustainable supply chain management in Chinese manufacturing firms.
Self-reports map the landscape of task states derived from brain imaging
Psychological states influence our happiness and productivity; however, estimates of their impact have historically been assumed to be limited by the accuracy with which introspection can quantify them. Over the last two decades, studies have shown that introspective descriptions of psychological states correlate with objective indicators of cognition, including task performance and metrics of brain function, using techniques like functional magnetic resonance imaging (fMRI). Such evidence suggests it may be possible to quantify the mapping between self-reports of experience and objective representations of those states (e.g., those inferred from measures of brain activity). Here, we used machine learning to show that self-reported descriptions of experiences across tasks can reliably map the objective landscape of task states derived from brain activity. In our study, 194 participants provided descriptions of their psychological states while performing tasks for which the contribution of different brain systems was available from prior fMRI studies. We used machine learning to combine these reports with descriptions of brain function to form a ‘state-space’ that reliably predicted patterns of brain activity based solely on unseen descriptions of experience (N = 101). Our study demonstrates that introspective reports can share information with the objective task landscape inferred from brain activity.
Awareness of human microbiome may promote healthier lifestyle and more positive environmental attitudes
The human microbiome is an essential factor of physical and mental health, yet the general population has little knowledge about it. This survey explores public familiarity with the human microbiome and (potential) public preferences related to monitoring and improving one’s microbiome health. The study also examines whether recognizing the importance of one’s microbiome may promote a more ecosystem-aware perspective towards microorganisms.
Neural correlates of personal space regulation in psychosis: role of the inferior parietal cortex
Regulation of interpersonal distance or “personal space” (PS; the space near the body into which others cannot intrude without eliciting discomfort) is a largely unconscious channel of non-verbal social communication used by many species including humans. PS abnormalities have been observed in neuropsychiatric illnesses, including schizophrenia. However, the neurophysiological basis of these abnormalities remains unknown. To investigate this question, in this study, functional magnetic resonance imaging (fMRI) data were collected while individuals with psychotic disorders (PD; n = 37) and demographically-matched healthy control (HC) subjects (n = 60) viewed images of faces moving towards or away from them. Responses of a frontoparietal-subcortical network of brain regions were measured to the approaching versus the withdrawing face stimuli, and resting-state fMRI data were also collected. PS size was measured using the classical Stop Distance Procedure. As expected, the PD group demonstrated a significantly larger PS compared to the HC group (P = 0.002). In both groups, a network of parietal and frontal cortical regions showed greater approach-biased responses, whereas subcortical areas (the striatum, amygdala and hippocampus) showed greater withdrawal-biased responses. Moreover, within the PD (but not the HC) group, approach-biased activation of the inferior parietal cortex (IPC) and functional connectivity between the IPC and the ventral/limbic striatum were significantly correlated with PS size. This study provides evidence that PS abnormalities in psychotic illness involve disrupted function and connectivity of the PS network. Such brain-behavior relationships may serve as objective treatment targets for novel interventions for schizophrenia and related psychotic illnesses.
User-specified inverse kinematics taught in virtual reality reduce time and effort to hand-guide redundant surgical robots
Medical robots should not collide with close by obstacles during medical procedures, such as lamps, screens, or medical personnel. Redundant robots have more degrees of freedom than needed for moving endoscopic tools during surgery and can be reshaped to avoid obstacles by moving purely in the space of these additional degrees of freedom (null space). Although state-of-the-art robots allow surgeons to hand-guide endoscopic tools, reshaping the robot in null space is not intuitive for surgeons. Here we propose a learned task space control that allows surgeons to intuitively teach preferred robot configurations (shapes) that avoid obstacles using a VR-based planner in simulation. Later during surgery, surgeons control both the endoscopic tool and robot configuration (shape) with one hand. In a user study, we found that learned task space control outperformed state-of-the-art naive task space control in all the measured performance metrics (time, effort, and user-perceived effort). Our solution allowed users to intuitively interact with robots in VR and reshape robots while moving tools in medical and industrial applications.
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