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This paper investigates the association between board characteristics and the company's corporate social responsibility (CSR) assurance decision in China. By examining 2054 firm-years of Chinese listed companies with CSR reports from 2008 to 2012, we find that firms with a large board size, more female directors, and separation of CEO and chairman positions are more likely to engage in CSR assurance. Gender diversity also influences the CSR assurance provider choice. However, board independence and overseas background of the CEO do not affect the CSR assurance decision. Inconsistent with our prediction, firms with foreign directors are less likely to engage in voluntary CSR assurance. In summary, this research provides in-depth insights into the determinants of Chinese firms' voluntary CSR assurance.

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

A novel color image encryption algorithm based on a cross 2D hyperchaotic map is proposed in this paper. The cross 2D hyperchaotic map is constructed using one nonlinear function and two chaotic maps with a cross structure. Chaotic behaviors are illustrated using bifurcation diagrams, Lyapunov exponent spectra, phase portraits, etc. In the color image encryption algorithm, the keys are generated using hash function SHA-512 and the information of the plain color image. First, the color plain image is converted to a combined bit-level matrix and permuted by the chaos-based row and column combined cycle shift scrambling method. Then, the scrambled integer matrix is diffused according to the selecting sequence which depends on the chaotic sequence. Last, decompose the diffusion matrix to get the encrypted color image. Simulation experiments and security evaluations show that the algorithm can encrypt the color image effectively and has good security to resist various kinds of attacks.

Inter- and intra-subject variability pose a major challenge to decoding human brain activity in brain-computer interfaces (BCIs) based on non-invasive electroencephalogram (EEG). Conventionally, a time-consuming and laborious training procedure is performed on each new user to collect sufficient individualized data, hindering the applications of BCIs on monitoring brain states (e.g. drowsiness) in real-world settings. This study proposes applying hierarchical clustering to assess the inter- and intra-subject variability within a large-scale dataset of EEG collected in a simulated driving task, and validates the feasibility of transferring EEG-based drowsiness-detection models across subjects. A subject-transfer framework is thus developed for detecting drowsiness based on a large-scale model pool from other subjects and a small amount of alert baseline calibration data from a new user. The model pool ensures the availability of positive model transferring, whereas the alert baseline data serve as a selector of decoding models in the pool. Compared with the conventional within-subject approach, the proposed framework remarkably reduced the required calibration time for a new user by 90% (18.00 min–1.72 ± 0.36 min) without compromising performance (p = 0.0910) when sufficient existing data are available. These findings suggest a practical pathway toward plug-and-play drowsiness detection and can ignite numerous real-world BCI applications. •A novel subject-transfer framework for reducing calibration time in brain state decoding.•Feasibility of cross-subject model transferring inferred from hierarchical clustering.•Robust decoding performance supported by large-scale existing data.•Significant decrease in calibration time using baseline brain activity.

Motivational regulation has long been recognized as an essential but insufficiently investigated aspect of self-regulated learning (SRL), especially in relation to learning English-as-a-foreign-language (EFL) writing. This study intends to fill the gap by investigating the predictive effect of motivational regulation strategies on EFL students’ writing performance mediated by SRL strategies. Data were collected from undergraduate students in mainland China (N = 512) through self-report questionnaires and an English writing test. Results of structural equation modeling (SEM) confirmed a partial mediation model in which motivational regulation strategies, as a whole, not only had direct and indirect effects on students’ writing performance but were also significantly correlated with their reported use of SRL strategies relating to cognition, metacognition, and social behavior. In addition, only cognitive and metacognitive strategies were found to be significant mediators in the model while social behavior strategies were not. The findings suggest that cumulative knowledge of motivational regulation is an antecedent of the reported use of other SRL strategies in affecting EFL writing performance. The inclusion of SRL strategies in the mediation model also contributes to a clear understanding of L2 writing processes within the SRL mechanism for improving writing outcomes.

Spatial navigation is a complex cognitive process based on multiple senses that are integrated and processed by a wide network of brain areas. Previous studies have revealed the retrosplenial complex (RSC) to be modulated in a task-related manner during navigation. However, these studies restricted participants’ movement to stationary setups, which might have impacted heading computations due to the absence of vestibular and proprioceptive inputs. Here, we present evidence of human RSC theta oscillation (4–8 Hz) in an active spatial navigation task where participants actively ambulated from one location to several other points while the position of a landmark and the starting location were updated. The results revealed theta power in the RSC to be pronounced during heading changes but not during translational movements, indicating that physical rotations induce human RSC theta activity. This finding provides a potential evidence of head-direction computation in RSC in healthy humans during active spatial navigation.

Stress is an inherent part of the normal human experience. Although, for the most part, this stress response is advantageous, chronic, heightened, or inappropriate stress responses can have deleterious effects on the human body. It has been suggested that individuals who experience repeated or prolonged stress exhibit blunted biological stress responses when compared to the general population. Thus, when assessing whether a ubiquitous stress response exists, it is important to stratify based on resting levels in the absence of stress. Research has shown that stress that causes symptomatic responses requires early intervention in order to mitigate possible associated mental health decline and personal risks. Given this, real-time monitoring of stress may provide immediate biofeedback to the individual and allow for early self-intervention. This study aimed to determine if the change in heart rate variability could predict, in two different cohorts, the quality of response to acute stress when exposed to an acute stressor and, in turn, contribute to the development of a physiological algorithm for stress which could be utilized in future smartwatch technologies. This study also aimed to assess whether baseline stress levels may affect the changes seen in heart rate variability at baseline and following stress tasks. A total of 30 student doctor participants and 30 participants from the general population were recruited for the study. The Trier Stress Test was utilized to induce stress, with resting and stress phase ECGs recorded, as well as inter-second heart rate (recorded using a FitBit). Although the present study failed to identify ubiquitous patterns of HRV and HR changes during stress, it did identify novel changes in these parameters between resting and stress states. This study has shown that the utilization of HRV as a measure of stress should be calculated with consideration of resting (baseline) anxiety and stress states in order to ensure an accurate measure of the effects of additive acute stress.

Graphitic carbon nitride (C3N4) is a kind of visible light-responsive photocatalyst that has been of great interest in wastewater treatment. However, its environmental impact and biological effect remains to be elucidated. This study investigated the effect of C3N4 nanosheets on bacterial abundance and antibiotic tolerance in wastewater. Interestingly, as compared to the wastewater containing the antibiotic ofloxacin alone, the wastewater containing both ofloxacin and C3N4 had much higher numbers of total living bacteria, but lower levels of the ofloxacin-resistant bacteria and the ofloxacin-resistant gene qnrS. The model bacterium Staphylococcus aureus was then used to explore the mechanism of C3N4-induced antibiotic tolerance. The nanosheets neither adsorbed the antibiotic nor promoted drug efflux, uncovering that drug adsorption and efflux were not involved in antibiotic tolerance. Further investigations revealed that the nanosheets, like arsenate and menadione, drastically reduced ATP levels and induced the production of reactive oxygen species for enhanced antibiotic tolerance. This study revealed an antibiotic-tolerating mechanism associated with C3N4-induced ATP depletion, and shed a light on the effect of photocatalysts on microbial ecology during their application in wastewater treatment.

Presynaptic inhibition after spinal cord injury (SCI) has been hypothesised to disproportionately affect flexion reflex loops in locomotor spinal circuitry. Reducing gamma-aminobutyric acid (GABA) inhibitory activity increases the excitation of flexion circuits, restoring muscle activation and stepping ability. Conversely, nociceptive sensitisation and muscular spasticity can emerge from insufficient GABAergic inhibition. To investigate the effects of neuromodulation and proprioceptive sensory afferents in the spinal cord, a biologically constrained spiking neural network (SNN) was developed. The network describes the ankle flexor motoneuron (MN) reflex loop with inputs from ipsilateral Ia- and II-fibres and tonically firing interneurons. The model was tuned to a Baseline level of locomotive activity before simulating an inhibitory-dominant and body-weight supported (BWS) SCI state. Electrical stimulation (ES) and serotonergic agonists were simulated by the excitation of dorsal fibres and reduced conductance in excitatory neurons. ES was applied across all afferent fibres without phase- or muscle-specific protocols. The present computational findings suggest that reducing stance-phase GABAergic inhibition on flexor motoneurons could facilitate more physiological flexor activation during locomotion. The model further predicts that neuromodulatory therapy, together with body-weight support, modulates the balance of synaptic excitation and inhibition in ankle flexor motoneurons to mitigate excessive inhibitory drive in the ankle flexor circuitry.

The kinetics and the conversion features of two 3-component systems (A/B/N), based on the proposed new kinetic schemes of Mokbel and Mau et al, in which a visible LED is used to excite a copper complex to its excited triplet state (G*). The coupling of G* with iodonium salt and ethyl 4-(dimethylamino)benzoate (EDB) produces both free radical polymerization (FRP) of acrylates and the free radical promoted cationic polymerization (CP) of epoxides using various new copper complex as the initiator. Higher FRP and CP conversion can be achieved by co-additive of [B] and N, via the dual function of (i) regeneration [A], and (ii) generation of extra radicals. The interpenetrated polymer network (IPN) capable of initiating both FRP and CP in a blend of TMPTA and EPOX. The synergic effects due to CP include: (i) CP can increase viscosity limiting the diffusional oxygen replenishment; (ii) the cation also acts as a diluting agent for the IPN network, and (iii) the exothermic property of the CP. The catalytic cycle, synergic effects, and the oxygen inhibition are theoretically confirmed to support the experimental hypothesis. The measured results of Mokbel and Mau et al are well analyzed and matching the predicted features of our modeling.