Design and Performance Research on Dual Layer Cement Based Absorber Reinforced with Graphene Nanosheets and Manganese-zinc Ferrite

Dual layer cement-based absorber is synthesized by mixing with graphene nanosheets and manganese-zinc ferrite, to study the effect of absorbing filler content on the mechanical properties, microstructure, electrical resistivity and reflectivity of the paste. The microstructure of the absorber is seen by Scanning Electron Microscope (SEM) images, Fourier Transform Infrared (FTIR) spectroscopy, X-Ray Diffraction (XRD) curves of the absorber. The results show that graphene nanosheets significantly reduce the electrical resistivity of paste, increasing its mechanical properties by improving its pore structure. SEM images indicate that graphene nanosheets promote the increase and coarsening of cement hydration products and produce a large number of dense bulk crystals. Furthermore, reflectivity measurements show that the minimum reflectivity of – 14.1 dB is obtained in the range of 2 ~ 18 GHz and the effective bandwidth of 16 GHz is obtained when reflectivity is less than – 7 dB. This study provides a new method for the preparation of dual layer cement-based absorber

Exploring the Role of Natural Gas in U.S. Trucking (Revised Version)

The recent emergence of natural gas as an abundant, inexpensive fuel in the United States could prompt a momentous shift in the level of natural gas utilized in the transportation sector. The cost advantage of natural gas vis-à-vis diesel fuel is particularly appealing for vehicles with a high intensity of travel and thus fuel use. Natural gas is already a popular fuel for municipal and fleet vehicles such as transit buses and taxis. In this paper, we investigate the possibility that natural gas could be utilized to provide fuel cost savings, geographic supply diversity and environmental benefits for the heavy-duty trucking sector and whether it can enable a transition to lower carbon transport fuels. We find that a small, cost-effective intervention in markets could support a transition to a commercially sustainable natural gas heavyduty fueling system in the state of California and that this could also advance some of the state’s air quality goals. Our research shows that an initial advanced natural gas fueling system in California could facilitate the expansion to other U.S. states. Such a network would enable a faster transition to renewable natural gas or biogas and waste-to-energy pathways. Stricter efficiency standards for natural gas Class 8 trucks and regulation of methane leakage along the natural gas supply chain would be necessary for natural gas to contribute substantially to California’s climate goals as a trucking fuel. To date, industry has favored less expensive technologies that do not offer the highest level of environmental performance

Sound Event Detection with Binary Neural Networks on Tightly Power-Constrained IoT Devices

Sound event detection (SED) is a hot topic in consumer and smart city applications. Existing approaches based on Deep Neural Networks are very effective, but highly demanding in terms of memory, power, and throughput when targeting ultra-low power always-on devices. Latency, availability, cost, and privacy requirements are pushing recent IoT systems to process the data on the node, close to the sensor, with a very limited energy supply, and tight constraints on the memory size and processing capabilities precluding to run state-of-the-art DNNs. In this paper, we explore the combination of extreme quantization to a small-footprint binary neural network (BNN) with the highly energy-efficient, RISC-V-based (8+1)-core GAP8 microcontroller. Starting from an existing CNN for SED whose footprint (815 kB) exceeds the 512 kB of memory available on our platform, we retrain the network using binary filters and activations to match these memory constraints. (Fully) binary neural networks come with a natural drop in accuracy of 12-18% on the challenging ImageNet object recognition challenge compared to their equivalent full-precision baselines. This BNN reaches a 77.9% accuracy, just 7% lower than the full-precision version, with 58 kB (7.2 times less) for the weights and 262 kB (2.4 times less) memory in total. With our BNN implementation, we reach a peak throughput of 4.6 GMAC/s and 1.5 GMAC/s over the full network, including preprocessing with Mel bins, which corresponds to an efficiency of 67.1 GMAC/s/W and 31.3 GMAC/s/W, respectively. Compared to the performance of an ARM Cortex-M4 implementation, our system has a 10.3 times faster execution time and a 51.1 times higher energy-efficiency.Comment: 6 pages conferenc

Urinary Aromatic Amino Acid Metabolites Associated With Postoperative Emergence Agitation in Paediatric Patients After General Anaesthesia: Urine Metabolomics Study

Background: Emergence agitation (EA) is very common in paediatric patients during recovery from general anaesthesia, but underlying mechanisms remain unknown. This prospective study was designed to profile preoperative urine metabolites and identify potential biomarkers that can predict the occurrence of EA.Methods: A total of 224 patients were screened for recruitment; of those, preoperative morning urine samples from 33 paediatric patients with EA and 33 non-EA gender- and age-matched patients after being given sevoflurane general anaesthesia were analysed by ultra-high-performance liquid chromatography (UHPLC) coupled with a Q Exactive Plus mass spectrometer. Univariate analysis and orthogonal projection to latent structures squares-discriminant analysis (OPLS-DA) were used to analyse these metabolites. The least absolute shrinkage and selection operator (LASSO) regression was used to identify predictive variables. The predictive model was evaluated through the receiver operating characteristic (ROC) analysis and then further assessed with 10-fold cross-validation.Results: Seventy-seven patients completed the study, of which 33 (42.9%) patients developed EA. EA and non-EA patients had many differences in preoperative urine metabolic profiling. Sixteen metabolites including nine aromatic amino acid metabolites, acylcarnitines, pyridoxamine, porphobilinogen, 7-methylxanthine, and 5′-methylthioadenosine were found associated with an increased risk of EA, and they all exhibited higher levels in the EA group than in the non-EA group. The main metabolic pathways involved in these metabolic changes included phenylalanine, tyrosine and tryptophan metabolisms. Among these potential biomarkers, L-tyrosine had the best predictive value with an odds ratio (OR) (95% CI) of 5.27 (2.20–12.63) and the AUC value of 0.81 (0.70–0.91) and was robust with internal 10-fold cross-validation.Conclusion: Urinary aromatic amino acid metabolites are closely associated with EA in paediatric patients, and further validation with larger cohorts and mechanistic studies is needed.Clinical Trial Registration:clinicaltrials.gov, identifier NCT0480799

Can social support make adolescents gritty? The moderating roles of age and gender

To extend our understanding of the development of adolescent grit, we examined the relationships between social support and the two facets of grit (i.e., perseverance of effort and consistency of interest) and whether the relations were moderated by age and gender. Our sample was composed of 1475 Chinese adolescents with ages ranging from 10.65 to 19.24 years old (M-age = 14.98, SDage = 1.66). The results showed that social support was positively related to perseverance of effort but not significantly related to consistency of interest. However, these relations were moderated by age. Specifically, the effect of social support on perseverance of effort declined as age increased, but remained positive among late adolescents. Nevertheless, the effect of social support on consistency of interest was positive only among early adolescents, and the effect decreased and even became marginally negative among late adolescents. Gender difference was further examined, and the results show that the moderating role in the relationship between social support and perseverance of effort was only significant among males rather than females. That is, the positive effect of social support on perseverance of effort did not change with age among females. Theoretic and practical implications are discussed.</p

A Dragon Fruit Picking Detection Method Based on YOLOv7 and PSP-Ellipse

Dragon fruit is one of the most popular fruits in China and Southeast Asia. It, however, is mainly picked manually, imposing high labor intensity on farmers. The hard branches and complex postures of dragon fruit make it difficult to achieve automated picking. For picking dragon fruits with diverse postures, this paper proposes a new dragon fruit detection method, not only to identify and locate the dragon fruit, but also to detect the endpoints that are at the head and root of the dragon fruit, which can provide more visual information for the dragon fruit picking robot. First, YOLOv7 is used to locate and classify the dragon fruit. Then, we propose a PSP-Ellipse method to further detect the endpoints of the dragon fruit, including dragon fruit segmentation via PSPNet, endpoints positioning via an ellipse fitting algorithm and endpoints classification via ResNet. To test the proposed method, some experiments are conducted. In dragon fruit detection, the precision, recall and average precision of YOLOv7 are 0.844, 0.924 and 0.932, respectively. YOLOv7 also performs better compared with some other models. In dragon fruit segmentation, the segmentation performance of PSPNet on dragon fruit is better than some other commonly used semantic segmentation models, with the segmentation precision, recall and mean intersection over union being 0.959, 0.943 and 0.906, respectively. In endpoints detection, the distance error and angle error of endpoints positioning based on ellipse fitting are 39.8 pixels and 4.3°, and the classification accuracy of endpoints based on ResNet is 0.92. The proposed PSP-Ellipse method makes a great improvement compared with two kinds of keypoint regression method based on ResNet and UNet. Orchard picking experiments verified that the method proposed in this paper is effective. The detection method proposed in this paper not only promotes the progress of the automatic picking of dragon fruit, but it also provides a reference for other fruit detection

Consistencies and differences in posttraumatic stress disorder and depression trajectories from the Wenchuan earthquake among children over a 4-year period

Background: Posttraumatic stress disorder (PTSD) and depression are the most prevalent mental disorders following disasters, and they often co-occur. The current study investigated trajectories of PTSD and depression among children after exposure to the Wenchuan earthquake and identified factors associated with PTSD or depression trajectories. Methods: Three hundred children who were exposed to the Wenchuan earthquake reported PTSD and depression symptoms 4, 16, 29, 40 and 52 months after the disaster, and potential predictors (age, earthquake exposure, prequake trauma and parental relationship) were identified. The PTSD and depression trajectories were identified with latent growth mixture modeling (LGMM), and the predictors were explored with multinomial logistic regression. Results: Two depression trajectories emerged: resilient (66.2%) and chronic (33.8%). Three PTSD trajectories emerged: resilient (74.9%), recovery (7.5%) and relapsing (17.7%). Overall, 57.3% of the children had low depression and PTSD symptoms over four years. Depression trajectories were significantly predicted by age and parental relationship, while PTSD trajectories were significantly predicted by trauma exposure and prequake trauma experience. Limitations: The children's prequake mental health statuses were unknown, and all assessments relied on self report questionnaires. Conclusion: The postdisaster developmental course of depression was more stable than that of PTSD, and PTSD and depression had different risk factors. Previous studies that focus only on PTSD or depression trajectories may overestimate children's resilient responses. Longer-term postdisaster intervention should pay more attention to depression than to PTSD

Correlation between Serum 25-Hydroxyvitamin D Levels and Gastric Cancer: A Systematic Review and Meta-Analysis

The purpose of this meta-analysis was to evaluate the relationship between serum 25-hydroxyvitamin D[25(OH)D] levels and gastric cancer. PubMed, Embase, Cochrane Library, Web of Science, The China Academic Journals full-text database, Wanfang Database of Chinese Academic Journals, VIP Chinese Science and Technology Periodicals database, and Chinese Biomedical Literature database were systematically searched. Case-control studies on the correlation between serum 25-hydroxyvitamin D levels and gastric cancer were retrieved, and the data extracted were analyzed. The results of 9 case-control studies containing 671 patients showed that serum 25(OH)D levels in the gastric cancer group were lower than those in the control group (weighted mean difference (WMD) = −8.90, 95% confidence interval (CI): −11.5, −6.32, p p p = 0.01). Thus, low levels of vitamin D may increase the risk of gastric cancer. Systematic review registration: PROSPERO CRD42022327942