CogEmoNet: A cognitive-feature-augmented driver emotion recognition model for smart cockpit

Driver's emotion recognition is vital to improving driving safety, comfort, and acceptance of intelligent vehicles. This article presents a cognitive-feature-augmented driver emotion detection method that is based on emotional cognitive process theory and deep networks. Different from the traditional methods, both the driver's facial expression and cognitive process characteristics (age, gender, and driving age) were used as the inputs of the proposed model. Convolutional techniques were adopted to construct the model for driver's emotion detection simultaneously considering the driver's facial expression and cognitive process characteristics. A driver's emotion data collection was carried out to validate the performance of the proposed method. The collected dataset consists of 40 drivers' frontal facial videos, their cognitive process characteristics, and self-reported assessments of driver emotions. Another two deep networks were also used to compare recognition performance. The results prove that the proposed method can achieve well detection results for different databases on the discrete emotion model and dimensional emotion model, respectively

A multimodal psychological, physiological and behavioural dataset for human emotions in driving tasks

Human emotions are integral to daily tasks, and driving is now a typical daily task. Creating a multi-modal human emotion dataset in driving tasks is an essential step in human emotion studies. we conducted three experiments to collect multimodal psychological, physiological and behavioural dataset for human emotions (PPB-Emo). In Experiment I, 27 participants were recruited, the in-depth interview method was employed to explore the driver’s viewpoints on driving scenarios that induce different emotions. For Experiment II, 409 participants were recruited, a questionnaire survey was conducted to obtain driving scenarios information that induces human drivers to produce specific emotions, and the results were used as the basis for selecting video-audio stimulus materials. In Experiment III, 40 participants were recruited, and the psychological data and physiological data, as well as their behavioural data were collected of all participants in 280 times driving tasks. The PPB-Emo dataset will largely support the analysis of human emotion in driving tasks. Moreover, The PPB-Emo dataset will also benefit human emotion research in other daily tasks

Preparation of Pd-Diimine@SBA-15 and Its Catalytic Performance for the Suzuki Coupling Reaction

A highly efficient and stable Pd-diimine@SBA-15 catalyst was successfully prepared by immobilizing Pd onto diimine-functionalized mesoporous silica SBA-15. With the help of diimine functional groups grafted onto the SBA-15, Pd could be anchored on a support with high dispersion. Pd-diimine@SBA-15 catalyst exhibited excellent catalytic performance for the Suzuki coupling reaction of electronically diverse aryl halides and phenylboronic acid under mild conditions with an ultralow amount of Pd (0.05 mol % Pd). When the catalyst amount was increased, it could catalyze the coupling reaction of chlorinated aromatics with phenylboronic acid. Compared with the catalytic performances of Pd/SBA-15 and Pd-diimine@SiO2 catalysts, the Pd-diimine@SBA-15 catalyst exhibited higher hydrothermal stability and could be repeatedly used four times without a significant decrease of its catalytic activity

Elevated thyroid stimulating hormone and metabolic syndrome risk in patients with first-episode and drug-na?ve major depressive disorder: a large-scale cross-sectional study

Background Metabolic syndrome (MetS) is common in major depressive disorder (MDD), but its relationship with thyroid hormones remains unclear. We aimed to examine the association of thyroid hormones and MetS in first-episode drug-na & iuml;ve (FEDN) MDD patients. Methods We recruited 1718 unmedicated MDD patients in this cross-sectional study. MetS was defined based on the 2004 Chinese Diabetes Society Criteria. Serum thyroid hormones including free thyroxine (FT4), free triiodothyronine (FT3), thyroid-stimulating hormone (TSH), thyroid peroxidase antibodies (TPOAb), and anti-thyroglobulin (TGAb) were examined. We used the logistic regression model to determine risk factors for MetS and examined the performance of the regression model by using the Area Under the Curve (AUC). In addition, we performed the trend test to test whether the results were robust. Results The prevalence of MetS in unmedicated MDD patients was 34.4%. MDD patients with MetS had higher levels of serum TSH, TGAb, and TPOAb (all P < 0.001). Concurrently, serum TSH levels were independent risk factors for MetS in MDD patients (OR:1.49, 95%CI: 1.40-1.58), which could also distinguish MDD patients with and without MetS (AUC was 0.77). Additionally, in the trend test, the results also indicated a similar trend when TSH was used as a categorical variable (P for trend < 0.001). Conclusions This study suggests that TSH levels were independent risk factors for MetS in FEDN MDD patients (OR:1.49). The examination of thyroid function may contribute to the early detection of MetS

Remnant cholesterol and mild cognitive impairment: A cross-sectional study

ObjectiveEmerging evidence suggests that elevated remnant cholesterol (RC) correlates with several health conditions. To explore the association of plasma RC with MCI incidence and the relationship between plasma RC and different domains of cognition in MCI patients.MethodsThirty-six MCI patients and 38 cognitively healthy controls (HC) were enrolled in the present cross-sectional study. Using total cholesterol (TC) minus high-density lipoprotein cholesterol (HDL-C) minus low-density lipoprotein cholesterol (LDL-C) as the formula for calculating fasting RC. Cognition was assessed using the Chinese version of the Montreal cognitive assessment (MoCA), Auditory Verbal Learning Test (AVLT), Digit Symbol Substitution Test (DSST), Trail Making Test (TMT), and Rey-Osterrieth Complex Figure Test (ROCF).ResultsCompared to healthy controls, MCI patients had a higher level of RC, the median difference in RC levels between these two groups was 8.13 mg/dl (95.0%CI: 0.97–16.1). Concurrently, plasma RC level was positively associated with MCI risk (OR = 1.05, 95%CI: 1.01–1.10). Notably, elevated RC level was correlated with impaired cognition in MCI patients, such as DSST (pr = −0.45, p = 0.008), ROCF- Long Delayed Recall (pr = −0.45, p = 0.008), AVLT-Immediate Recall (pr = −0.38, p = 0.028), and TMT-A (pr = 0.44, p = 0.009). Conversely, no significant correlation was found between RC and the AVLT-Long Delayed Recall test.ConclusionThis study found that plasma remnant cholesterol was associated with MCI. Further large longitudinal studies are needed in the future to confirm the results and clarify the cause-and-effect relationship

Ultralow-temperature CO oxidation on an In2O3-Co3O4 catalyst: a strategy to tune CO adsorption strength and oxygen activation simultaneously

Highly efficient In2O3–Co3O4 catalysts were prepared for ultralow-temperature CO oxidation by simultaneously tuning the CO adsorption strength and oxygen activation over a Co3O4 surface.</p

Low-Temperature Methane Combustion over Pd/H-ZSM-5: Active Pd Sites with Specific Electronic Properties Modulated by Acidic Sites of H‑ZSM‑5

Pd/H-ZSM-5 catalysts could completely catalyze CH₄ to CO₂ at as low as 320 °C, while there is no detectable catalytic activity for pure H-ZSM-5 at 320 °C and only a conversion of 40% could be obtained at 500 °C over pure H-ZSM-5. Both the theoretical and experimental results prove that surface acidic sites could facilitate the formation of active metal species as the anchoring sites, which could further modify the electronic and coordination structure of metal species. PdO_<i>x</i> interacting with the surface Brönsted acid sites of H-ZSM-5 could exhibit Lewis acidity and lower oxidation states, as proven by the XPS, XPS valence band, CO-DRIFTS, pyridine FT-IR, and NH₃-TPD data. Density functional theory calculations suggest PdO_<i>x</i> groups to be the active sites for methane combustion, in the form of [AlO₂]­Pd­(OH)-ZSM-5. The stronger Lewis acidity of coordinatively unsaturated Pd and the stronger basicity of oxygen from anchored PdO_<i>x</i> species are two key characteristics of the active sites ([AlO₂]­Pd­(OH)-ZSM-5) for methane combustion. As a result, the PdO_<i>x</i> species anchored by Brønsted acid sites of H-ZSM-5 exhibit high performance for catalytic combustion of CH₄ over Pd/H-ZSM-5 catalysts