An investigation of heterogeneous impact, temporal stability, and aggregate shift in factors affecting the driver injury severity in single-vehicle rollover crashes.

Single-vehicle rollover crashes have been acknowledged as a predominant highway crash type resulting in serious casualties. To investigate the heterogeneous impact of factors determining different injury severity levels in single-vehicle rollover crashes, the random parameters logit model with unobserved heterogeneity in means and variances was employed in this paper. A five-year dataset on single-vehicle rollover crashes, gathered in California from January 1, 2013, to December 31, 2017, was utilized. Driver injury severities that were determined to be outcome variables include no injury, minor injury, and severe injury. Characteristics pertaining to the crash, driver, temporal, vehicle, roadway, and environment were acknowledged as potential determinants. The results showed that the gender indicator specified to minor injury was consistently identified as a significant random parameter in four years' models and the joint five-year model, excluding the 2016 crash model where the night indicator associated with no injury was observed to produce the random effect. Additionally, two series of likelihood ratio tests were conducted to assess the year-to-year and aggregate-to-component temporal stability of model estimation results. Marginal effects of explanatory variables were also calculated and compared to analyze the temporal stability and interpret the results. The findings revealed an overall temporal instability of model specifications across individual years, while there is no significant aggregate-to-component variation. Injury severities were observed to be stably affected by several variables, including improper turn indicator, under the influence of alcohol indicator, old driver indicator, seatbelt indicator, insurance indicator, and airbag indicator. Furthermore, the year-to-year and aggregate-to-component shift was quantified and characterized by calculating the differences in probabilities between within-sample observations and out-of-sample predictions. The overall results imply that continuing to expand and refine the model to incorporate more comprehensive datasets can result in more robust and stable injury severity prediction, thus benefiting in mitigating the associated driver injury severity.

AI-based soundscape analysis: Jointly identifying sound sources and predicting annoyancea).

Soundscape studies typically attempt to capture the perception and understanding of sonic environments by surveying users. However, for long-term monitoring or assessing interventions, sound-signal-based approaches are required. To this end, most previous research focused on psycho-acoustic quantities or automatic sound recognition. Few attempts were made to include appraisal (e.g., in circumplex frameworks). This paper proposes an artificial intelligence (AI)-based dual-branch convolutional neural network with cross-attention-based fusion (DCNN-CaF) to analyze automatic soundscape characterization, including sound recognition and appraisal. Using the DeLTA dataset containing human-annotated sound source labels and perceived annoyance, the DCNN-CaF is proposed to perform sound source classification (SSC) and human-perceived annoyance rating prediction (ARP). Experimental findings indicate that (1) the proposed DCNN-CaF using loudness and Mel features outperforms the DCNN-CaF using only one of them. (2) The proposed DCNN-CaF with cross-attention fusion outperforms other typical AI-based models and soundscape-related traditional machine learning methods on the SSC and ARP tasks. (3) Correlation analysis reveals that the relationship between sound sources and annoyance is similar for humans and the proposed AI-based DCNN-CaF model. (4) Generalization tests show that the proposed model's ARP in the presence of model-unknown sound sources is consistent with expert expectations and can explain previous findings from the literature on soundscape augmentation.

The association between perchlorate in drinking water and height and weight of children and adolescents in Southwest China: a retrospective cross-sectional study.

Objective: To investigate the association between the concentration of perchlorate in drinking water and the height and weight of children and adolescents in Sichuan Province. Methods: Perchlorate in the drinking water of 24 counties in Sichuan Province from 2021 to 2022 was detected and analyzed, 66 drinking water samples were collected, and the content of perchlorate in drinking water during the wet season and dry season was detected by ultra-high performance liquid chromatography in series. The linear mixed effect model was used to estimate the relationship between perchlorate in drinking water and the height and weight of 144,644 children and adolescents, and 33 pieces of local average wage data were used as confounding factors for quality control. Results: After controlling the age, gender, and local economic situation, we found that the concentration of perchlorate in drinking water increased by 10 µg/L is associated with a 1.0 cm decrease in height and a 1.6 kg decrease in weight in children and adolescents (p < 0.05). Conclusion: The concentration of perchlorate in drinking water may be negatively correlated with the height and weight of children.

Behavioural Models of Risk-Taking in Human-Robot Tactile Interactions.

Touch can have a strong effect on interactions between people, and as such, it is expected to be important to the interactions people have with robots. In an earlier work, we showed that the intensity of tactile interaction with a robot can change how much people are willing to take risks. This study further develops our understanding of the relationship between human risk-taking behaviour, the physiological responses by the user, and the intensity of the tactile interaction with a social robot. We used data collected with physiological sensors during the playing of a risk-taking game (the Balloon Analogue Risk Task, or BART). The results of a mixed-effects model were used as a baseline to predict risk-taking propensity from physiological measures, and these results were further improved through the use of two machine learning techniques-support vector regression (SVR) and multi-input convolutional multihead attention (MCMA)-to achieve low-latency risk-taking behaviour prediction during human-robot tactile interaction. The performance of the models was evaluated based on mean absolute error (MAE), root mean squared error (RMSE), and R squared score (R2), which obtained the optimal result with MCMA yielding an MAE of 3.17, an RMSE of 4.38, and an R2 of 0.93 compared with the baseline of 10.97 MAE, 14.73 RMSE, and 0.30 R2. The results of this study offer new insights into the interplay between physiological data and the intensity of risk-taking behaviour in predicting human risk-taking behaviour during human-robot tactile interactions. This work illustrates that physiological activation and the intensity of tactile interaction play a prominent role in risk processing during human-robot tactile interaction and demonstrates that it is feasible to use human physiological data and behavioural data to predict risk-taking behaviour in human-robot tactile interaction.

Microcella aerolata sp. nov., isolated from electronic waste-associated bioaerosols.

A Gram-positive, non-motile, non-spore-forming and short rod-shaped actinomycete strain, designated GA224T, was isolated from electronic waste-associated bioaerosols. The optimal growth conditions for this isolate, a facultatively anaerobic bacterium, were 37 °C and pH 8.0. The cell-wall peptidoglycan type was B2γ, with 2,4-diaminobutyric acid (DAB) as the diamino acids, while the major menaquinone was MK-12. The polar lipid profile was composed of diphosphatidylglycerol, phosphatidylglycerol, unidentified phospholipids, unidentified glycolipids and an unidentified lipid. The major cellular fatty acids were anteiso-C15:0 and iso-C16:0. Phylogenetic analyses based on 16S rRNA gene sequences showed that strain GA224T fell within the genus Microcella. The draft genome of strain GA224T comprised 2,495,189 bp with a G + C content of 72.2 mol%. The average nucleotide identity and digital DNA-DNA hybridization values between strain GA224T and the type strain of the type species of Microcella species were lower than 95% and 70%, respectively. Based on the phenotypic, chemotaxonomic and genomic data, strain GA224T represents a novel species, for which the name Microcella aerolata sp. nov. is proposed, with GA224T as the type strain (= GDMCC 1.2165 T = JCM 34462 T).

Roseicella aerolata sp. nov., isolated from bioaerosols of electronic waste.

A novel Gram-stain-negative, non-motile, spherical-shaped and facultatively anaerobic bacterial strain, designated as GB24T was isolated from bioaerosols of an E-waste dismantling site in Guiyu, Guangdong Province, South PR China. Growth occurred at 15-40 °C (optimum 37 °C), pH 5.5-9.5 (optimum 7.0), and up to 0.5 % NaCl (w/v) under aerobic conditions, GB24T was characterized taxonomically and phylogenetically. The sole isoprenoid quinone detected was ubiquinone-10 (Q-10). The polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, phosphatidylcholine, three unidentified glycolipids, one unidentified phospholipid, and one unidentified aminolipid. Carotenoid pigments were produced. The major cellular fatty acids (> 10 % of total fatty acids) were C17 : 1ω6c (51.5 %) and summed feature 8 (13.5 %, comprising C18 : 1ω7c and/or C18 : 1ω6c). Phylogenetic analysis based on 16S rRNA gene sequence and draft genome grouped strain GB24T into the genus Roseicella. GB24T was most closely related to Roseicella frigidaeris DB1506T with 97.5 % 16S rRNA gene sequence similarity. The draft genome of GB24T comprised 6 153 170 bp with a DNA G+C content of 71.5 %. The average nucleotide identity (ANI) and in silico DNA-DNA hybridization (isDDH) values between GB24T and DB1506T were 83.2 % (Ortho ANI), 83.3 % [ANI by blast (ANIb)] and 27.0 %, respectively. Further genomic analysis of GB24T revealed the secondary metabolite clusters of terpene and phosphonate, which indicate the capacity for malleobactin (14 %) and phosphinothricin (6 %) tripeptide production. On the basis of the genotypic, chemotaxonomic and phenotypic results, GB24T represents a novel species, for which the name Roseicella aerolata sp. nov. is proposed. The type strain of Roseicella aerolata is GB24T (= GDMCC 1.2169T = JCM 34449T).

Insight Into Microbial Community Aerosols Associated With Electronic Waste Handling Facilities by Culture-Dependent and Culture-Independent Methods.

Airborne microorganisms in the waste associated environments are more active and complex compared to other places. However, the diversity and structure of airborne bacteria in waste-associated environments are still not clearly understood. The purpose of this study was to assess airborne bacterial community in electronic waste dismantling site and a waste transfer station based on culture-dependent and culture-independent methods. A total of 229 isolates were obtained from four airborne sites collected from residential area, electronic industrial park, and office area in or near an electronic waste dismantling site and a waste transfer station in Southern China in the morning, afternoon, and evening. Most of the isolates were isolated from air for the first time and 14 potentially novel species were identified by Sanger sequencing. Bacterial communities in waste-associated bioaerosols were predominated by Proteobacteria and Bacteroidetes. Abundant genera (>1%) included Paracaedibacteraceae (uncultured EF667926), Ralstonia, Chroococcidiopsis, Chitinophagaceae (uncultured FN428761), Sphingobium, and Heliimonas. One-third of the species in these genera were uncultured approximately. Differences community structure existed in airborne bacterial diversity among different sampling sites. These results showed that waste-associated environments have unique bacterial diversity. Further studies on such environments could provide new insights into bacterial community.

Bacillus aerolatus sp. nov., a novel member of the genus Bacillus, isolated from bioaerosols in a school playground.

A Gram-positive, endospore-forming, rod-shaped bacterium with a single flagellum, and a motile strain, designated CX253, was isolated from bioaerosols. The isolate is facultatively anaerobic, is able to grow at 25-45 â„ƒ (optimum 37 â„ƒ) and pH 6.5-10.0 (optimum 7.5), and can tolerate up to 5.0% NaCl (w/v) under aerobic conditions. The diagnostic diamino acid in the cell wall of strain CX253T is meso-diaminopimelic acid, while major isoprenoid quinone is menaquinone 6 (MK-6) along with a smaller amount of MK-7 (20%). The polar lipid profile is composed of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, phospholipids and glycolipids. The major cellular fatty acid is iso-C15:0 and anteiso-C15:0. Phylogenetic analysis based on 16S rRNA gene and genome sequence grouped strain CX253T into the genus Bacillus. The strain was most closely related to Bacillus thermotolerans CCTCC AB 2012108 T by comparison of 16S rRNA gene sequence (97.2% similarity) and to Bacillus wudalianchiensis CCTCC AB 2015266 T by comparison of gyrB gene sequence (80.1% similarity). The draft genome of strain CX253T comprised 3,929,195 bp with a G + C content of 43.3 mol%. The average nucleotide identity and digital DNA-DNA hybridization values between strain CX253T and phylogenetically related Bacillus species were lower than 95% and 70%, respectively. Thus, the polyphasic evidence generated through phenotypic, chemotaxonomic and genomic methods confirmed that strain CX253T (= GDMCC 1.1608 T = KACC 21318 T) was a novel species of the genus Bacillus, for which the name Bacillus aerolatus sp. nov. is proposed.

Intergenerational transfer of Dechlorane Plus and the associated long-term effects on the structure and function of gut microbiota in offspring.

The gut microbiota has been shown to be highly involved in many vital physiological processes that play key roles in human health. The intergenerational transfer of Dechlorane Plus (DP) and the complex interaction between DP and microbiota has been poorly studied. Additionally, the structural and functional effects of DP on the gut microbiota have not been studied. This study aimed to investigate the DP transfer in Sprague-Dawley rats during pregnancy and the effects of DP exposure on gut microbiota, as detected by 16S rRNA gene sequencing. The results showed that excretion in feces is a very important elimination pathway of orally dosed DP. The main intergenerational transfer pathway of DP might be via lactation rather than transplacental transport. The 16S rRNA sequencing revealed that DP exposure could decrease the richness and diversity of gut microbiota, especially at the genus level. Furthermore, in DP exposure groups, the gut microbiota production of metabolites of short-chain fatty acids was dramatically increased. The results demonstrated that DP exposure not only altered the gut microbiota structures, but also immensely influenced metabolic functions, causing long-term impact to offspring. This data indicates that more attention should be paid to the long-term health effects related to DP exposure.

Complete Genome Insights into Lactococcus petauri CF11 Isolated from a Healthy Human Gut Using Second- and Third-Generation Sequencing.

Lactococcus petauri CF11 was originally isolated from the gut of healthy humans. To determine the underlying molecular and genetic mechanisms of the probiotic potential of CF11, we performed complete genome sequencing, annotation, and comparative genome analysis. The complete genome of L. petauri CF11 comprised of 1,997,720 bp, with a DNA G+C content of 38.21 mol% containing 1982 protein coding genes and 16 rRNA operons. We found that 1206 genes (56.05%) were assigned a putative function using the gene ontology (GO) resource. The gene products of CF11 were primarily concentrated in molecular function and biological processes, such as catalysis, binding, metabolism, and cellular processes. Furthermore, 1,365 (68.87%) genes were assigned an illative function using COGs. CF11 proteins were associated with carbohydrate transport and metabolism, and amino acid transport and metabolism. This indicates that CF11 bacteria can perform active energy exchange. We classified 1,111 (56.05%) genes into six KEGG functional categories; fructose-bisphosphate aldolase and the phosphoenol pyruvate:phosphotransferase system (PTS), which are necessary in producing short-chain fatty acids (SCFAs), were excited in the carbohydrate metabolic pathway. This suggests that L. petauri CF11 produces SCFAs via glycolysis. The genomic island revealed that some regions contain fragments of antibiotic resistance and bacteriostatic genes. In addition, ANI analysis showed that L. petauri CF11 had the closest relationship with L. petauri 159469T, with an average nucleotide consistency of 98.03%. Taken together, the present study offers further insights into the functional and potential role of L. petauri CF11 in health care.

Interface synthesis, assembly and characterization of close-packed monolayer of prussian blue/polypyrrole nanocomposites.

The self-assembly of nanomaterials into ordered two- or three-dimensional structures has been extensively explored over the past years due to the great application potential. This paper reports a simple one-step methodology for the synthesis and assembly of Prussian blue/polypyrrole (PBPPy) nanocomposites into close-packed monolayer at a toluene-water interface where the formation of PBPPy and evaporation of organic phase happen simultaneously. The formed films could be easily transferred onto the glass carbon surface by layer-by-layer technique. The obtained PBPPy nanocomposites and their assembled film were characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, UV-vis spectroscopy and cyclic voltammetry. The PBPPy nanocomposite film on the electrode surface exhibits excellent electron transfer and high electrocatalysis toward the reduction of H2O2. Herein, PPy component in PBPPy nanocomposites plays a great role in this great electrochemical performance. On the one hand, the presence of PPy is helpful of the formation of close-packed monolayer of PBPPy nanocomposites, and the adhesion of the ordered monolayer or multilayer onto the electrode surface due to the molecular interaction of PPy or the surface group of electrode. On the other hand, the conductive PPy facilitates the electron transfer between PB and PB or PB and electrode. The suggested method can be extended to a wide range of nanomaterials assembly and devise development.

One-step synthesis of graphene/polyallylamine-Au nanocomposites and their electrocatalysis toward oxygen reduction.

A simple, inexpensive, one-step synthesis of graphene/PAA-Au nanocomposites was achieved by using polyallylamine (PAA) as a reducing and stabilizing agent. The synthetic process was carried out only in aqueous solution, which is versatile and environmentally friendly. The resulting nanocomposites could be dispersed into water stably without any additional protection by polymeric or surfactant stabilizers. The products were further characterized by UV-visible absorption spectroscopy, transmission electron microscopy (TEM), fourier transform infrared spectroscopy (FTIR) and photoelectron spectroscopy (XPS). The results indicate that graphene sheets played an important role as a support material to increase the active area of Au nanoparticles (AuNPs). And the resulting graphene/PAA-Au nanocomposites film exhibited good electrocatalytical activity towards reduction of both H(2)O(2) and O(2), which showed potential application in electrochemical sensors.