Solar Tracking Error Analysis of Fresnel Reflector

Depending on the rotational structure of Fresnel reflector, the rotation angle of the mirror was deduced under the eccentric condition. By analyzing the influence of the sun tracking rotation angle error caused by main factors, the change rule and extent of the influence were revealed. It is concluded that the tracking errors caused by the difference between the rotation axis and true north meridian, at noon, were maximum under certain conditions and reduced at morning and afternoon gradually. The tracking error caused by other deviations such as rotating eccentric, latitude, and solar altitude was positive at morning, negative at afternoon, and zero at a certain moment of noon

Adapting Prompt for Few-shot Table-to-Text Generation

Pretrained language models (PLMs) have made remarkable progress in table-to-text generation tasks. However, the lack of domain-specific knowledge makes it challenging to bridge the topological gap between tabular data and text, especially in real-world applications with limited resources. To mitigate the limitation of insufficient labeled data, we propose a novel framework: Adapt-Prompt-to-Generate (AdaPTGen). The core insight of AdaPTGen is to adapt prompt templates of domain-specific knowledge into the model, which brings at least three benefits: (1) it injects representation of normal table-related descriptions to bridge the topological gap between tabular data and texts; (2) it enables us to use large amounts of unlabeled domain-specific knowledge fully, which can alleviate the PLMs' inherent shortcomings of lacking domain knowledge; (3) it allows us to design various tasks to explore the domain-specific knowledge. Extensive experiments and analyses are conducted on three open-domain few-shot natural language generation (NLG) data sets: Humans, Songs, and Books. Compared to previous state-of-the-art approaches, our model achieves superior performance in terms of both fluency and accuracy.Comment: arXiv admin note: substantial text overlap with arXiv:2302.0441

Polystyrene microplastics protect lettuce (Lactuca sativa) from the hazardous effects of Cu(OH)2 nanopesticides

Copper-based nanopesticides are released into the environment during foliar spray application, and they could, on their own or in combination with microplastics (MPs), pose threats to environmental safety and human health. In this study, Cu(OH)2 nanowires greatly decreased the vigor of lettuce seeds (p< 0.01) and the root length of lettuce seedlings (p< 0.01) and significantly altered the lettuce antioxidant defence system and MDA content (p< 0.05). Released Cu2+ played a critical role in the toxicity mechanism of Cu(OH)2 nanowires in lettuce seedlings, as evidenced by the substantial accumulation of Cu in the seedling roots (p< 0.01) rather than in the leaves. Polystyrene (PS) MPs (1 mg/L) stimulated lettuce seedling growth, as shown by the (highly) significant increase in root and leaf length and in the seed vigor index (p< 0.01 or 0.05). Notably, PS MPs (1 mg/L) neutralized the hazardous effects of 1 mg/L Cu(OH)2 nanowire treatment on lettuce growth, as reflected by the vitality and root length of the seedlings returning to normal levels. The PS MPs (1 mg/L) absorbed on middle root surfaces and strongly hindered Cu accumulation in lettuce roots, which was the predominant mechanism by which PS MPs suppressed the hazardous effects of the Cu(OH)2 nanowires. This study strengthens the understanding of the toxicity and toxicity mechanisms of Cu(OH)2 nanowires with or without PS MPs in the environment

Effectiveness of Post-Traumatic Growth Intervention to Promote Positive Post-Traumatic Traits in Chinese Breast Cancer Patients:A Randomized Controlled Trial

Objective: The purpose of this study was to evaluate the effectiveness of post-traumatic growth (PTG) model-based intervention to improve positive psychological traits in Chinese breast cancer patients. Design: A randomized control trial of a psychological group intervention based on PTG model. Methods: The Clinical Trial was registered on 17 August 2019 at Chinese Clinical Trials.gov with Registration number ChiCTR1900025264. A total of 92 patients with breast cancer were recruited. The participants were randomly assigned to the experimental group (n = 46) and the control group (n = 46). A six-session psychological group intervention based on PTG model was implemented in the experimental group, and a six-session health education was implemented in the control group. The outcomes were measured at baseline (pre-intervention), 3 weeks, 6 weeks after the intervention. The primary outcome was post-traumatic growth assessed by the Chinese version of the Post-Traumatic Growth Inventory (PTGI); Secondary outcomes included psychological resilience, family resilience, rumination, and self-disclosure. Results: A total of 87 patients with breast cancer completed this study, including 44 patients in the experimental group and 43 patients in the control group. There was no significant difference in baseline data of breast cancer patients between the two groups except for the treatment regimen (p &gt; 0.05). The two groups were compared after the intervention; the interaction effects between the total scores of post-traumatic growth, family resilience, and self-disclosure and the time term were statistically significant (p &lt; 0.05), indicating that the trend of change in total scores of post-traumatic growth, family resilience, and self-disclosure differed between the experimental and control groups over time, and the scores improved in the experimental group were significantly higher than those in the control group. The comparison of psychological resilience and total score of rumination at each time point was statistically significant (p &lt; 0.05), indicating that group intervention based on the PTG model could improve the psychological recovery ability and rumination level of the experimental group. Conclusion: The psychological group intervention based on the PTG model significantly improved post-traumatic growth, family resilience, and self-disclosure in patients with breast cancer. However, the impact on psychological resilience and rumination was relatively small. Long-term intervention is needed to further test the effect of the PTG model on psychological resilience and rumination.</p

A hydrated deep eutectic electrolyte with finely-tuned solvation chemistry for high-performance zinc-ion batteries

Despite their cost-effectiveness and intrinsic safety, aqueous zinc-ion batteries have faced challenges with poor reversibility originating from various active water-induced side reactions. After systematically scrutinizing the effects of water on the evolution of solvation structures, electrolyte properties, and electrochemical performances through experimental and theoretical approaches, a hydrated deep eutectic electrolyte with a water-deficient solvation structure ([Zn(H2O)2(eg)2(otf)2]) and reduced free water content in the bulk solution is proposed in this work. This electrolyte can dramatically suppress water-induced side reactions and provide high Zn2+ mass transfer kinetics, resulting in highly reversible Zn anodes (∼99.6% Coulombic efficiency over 1000 cycles and stable cycling over 4500 h) and high capacity Zn//NVO full cells (436 mA h g−1). This work will aid the understanding of electrolyte solvation structure–electrolyte property–electrochemical performance relationships of aqueous electrolytes in aqueous zinc-ion batteries

Surface passivation for highly active, selective, stable, and scalable CO2 electroreduction

Electrochemical conversion of CO2 to formic acid using Bismuth catalysts is one the most promising pathways for industrialization. However, it is still difficult to achieve high formic acid production at wide voltage intervals and industrial current densities because the Bi catalysts are often poisoned by oxygenated species. Herein, we report a Bi3S2 nanowire-ascorbic acid hybrid catalyst that simultaneously improves formic acid selectivity, activity, and stability at high applied voltages. Specifically, a more than 95% faraday efficiency was achieved for the formate formation over a wide potential range above 1.0 V and at ampere-level current densities. The observed excellent catalytic performance was attributable to a unique reconstruction mechanism to form more defective sites while the ascorbic acid layer further stabilized the defective sites by trapping the poisoning hydroxyl groups. When used in an all-solid-state reactor system, the newly developed catalyst achieved efficient production of pure formic acid over 120 hours at 50 mA cm–2 (200 mA cell current)

Differentiation of malignant brain tumor types using intratumoral and peritumoral radiomic features

Tumor infiltration of central nervous system (CNS) malignant tumors may extend beyond visible contrast enhancement. This study explored tumor habitat characteristics in the intratumoral and peritumoral regions to distinguish common malignant brain tumors such as glioblastoma, primary central nervous system lymphoma, and brain metastases. The preoperative MRI data of 200 patients with solitary malignant brain tumors were included from two datasets for training. Quantitative radiomic features from the intratumoral and peritumoral regions were extracted for model training. The performance of the model was evaluated using data (n = 50) from the third clinical center. When combining the intratumoral and peritumoral features, the Adaboost model achieved the best area under the curve (AUC) of 0.91 and accuracy of 76.9% in the test cohort. Based on the optimal features and classifier, the model in the binary classification diagnosis achieves AUC of 0.98 (glioblastoma and lymphoma), 0.86 (lymphoma and metastases), and 0.70 (glioblastoma and metastases) in the test cohort, respectively. In conclusion, quantitative features from non-enhanced peritumoral regions (especially features from the 10-mm margin around the tumor) can provide additional information for the characterization of regional tumoral heterogeneity, which may offer potential value for future individualized assessment of patients with CNS tumors

Single-Trait and Multi-Trait Genome-Wide Association Analyses Identify Novel Loci for Blood Pressure in African-Ancestry Populations

Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P \u3c 1.25×10−8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension

Genome-Wide Association of Body Fat Distribution in African Ancestry Populations Suggests New Loci

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0×10−6 were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10−8 for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10−8 for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5×10−8; RREB1: p = 5.7×10−8). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity

Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms

Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. Video Abstract [Figure presented] Keywords: type 2 diabetes (T2D); genetics; disease mechanism; SLC16A11; MCT11; solute carrier (SLC); monocarboxylates; fatty acid metabolism; lipid metabolism; precision medicin