One- and Two-Photon Photophysical Properties, Ultrafast Dynamics, and DFT Study of Three Modified Zinc Phthalocyanines.

As two-photon absorption (TPA) materials, phthalocyanine molecules have promising application prospects due to their large TPA absorption cross-section, high third-order nonlinear optical susceptibility, and ultrafast response characteristics. In this work, optical properties and the ultrafast response of three modified zinc phthalocyanine molecules (P-HPcZn, Pc-P-Pc, and (DR1)4PcZn) were analyzed. No obvious side-shoulder absorption peaks in the Q-band can be observed from the steady-state absorption spectra of the three molecules, confirming the lack of aggregation products in the solutions of our measurement. Open-aperture Z-scan results show relatively large TPA cross-section values of 136.4 and 55.3 GM for Pc-P-Pc and (DR1)4PcZn, respectively. The nonlinear optical results show that the absorption process observed under the excitation of femtosecond pulses is a reverse saturable absorption (RSA) mechanism. Up-conversion fluorescence spectra of (DR1)4PcZn in THF solution indicate that the fluorescence emission mechanism is TPA. In the study of ultrafast dynamics, the transient absorption spectra were investigated and the decay lifetime of the dynamic traces corresponding to some representative probe wavelengths was obtained through data fitting with a multi-exponential function. Finally, the charge transfer and excited state properties of the modified zinc phthalocyanine molecules were discussed in depth by the DFT method. The energy gaps of P-HPcZn, Pc-P-Pc, and (DR1)4PcZn are 2.16, 1.39, and 2.13 eV, respectively. The results indicate that the Pc-P-Pc of donor-acceptor-donor (D-A-D) structure has the smallest energy gap as well as the best charge transfer properties.

Assessing the air pollution abatement effect of prefabricated buildings in China.

Due to the acceleration of urbanization and industrialization, air pollutants has been increasing, posing a major threat to human health and the ecological environment. During the past period of rapid growth, with the booming development of real estate, the air pollutants brought about by the construction of housing buildings have become more and more serious, especially sulfur dioxide, nitrogen dioxide, and dust, which cast a great threat to human life and seriously jeopardize human health. Compared with the traditional construction of houses, prefabricated buildings construction procedures are reduced, to some extent, can reduce air pollutants. Therefore, this paper takes an empirical perspective to include prefabricated buildings and air pollutants into the same research framework and analyze the inherent logical relationship. We found that prefabricated buildings have a substantial role in mitigating urban air pollution. This conclusion remained solid after various robustness tests including constructing instrumental variables. The effect is observed to be greater in cities above the non-sub-provincial level and those positioned within central regions. The conclusions explore new areas for the green and sustainable development of the construction industry, which in the future will have to fill the requirements of green development in order to survive. Else, perspectives from the construction industry, it provides a realistic solution to economic development and ecological protection, helping to alleviate or resolve the conflict between development and survival.

The impacts of casual environmental regulation on carbon intensity in China: Dual mediating pathways of energy low-carbon reconstitution and industrial structure upgrading.

In the new era of global net zero, how to reduce carbon intensity became a hot topic, while few attentions had been paid to the impacts of casual environmental regulation, especially in the emerging economy such as China. In this regard, this study uses the panel data of 30 provinces in China from 2003 to 2019 to study the impacts of causal environmental regulation on the carbon intensity, with the adoption of multiple econometric models. The empirical results show that causal environmental regulation has a significant inhibitory effect on carbon intensity, while at current stage, causal environmental regulation cannot inhibit carbon intensity through the mediating of green innovation and renewable energy production. Fortunately, energy low-carbon reconstitution and industrial structure upgrading are proved to effectively act as the intermediary channels. In addition, the spatial spillover effects and the spatial heterogeneity are supported in the empirical analysis. In a summary, this study starts with the case of China to provide a realistic reference case for the international community, enriches the theory, policy and practice related to environmental regulation, and provides a realistic reference example for emerging economics in a developing country.

Identification of long non-coding RNAs and microRNAs involved in anther development in the tropical Camellia oleifera.

BACKGROUND: Explored the molecular science of anther development is important for improving productivity and overall yield of crops. Although the role of regulatory RNAs, including long non-coding RNAs (lncRNAs) and microRNAs (miRNAs), in regulating anther development has been established, their identities and functions in Camellia oleifera, an important industrial crop, have yet not been clearly explored. Here, we report the identification and characterization of genes, lncRNAs and miRNAs during three stages of the tropical C. oleifera anther development by single-molecule real-time sequencing, RNA sequencing and small RNA sequencing, respectively. RESULTS: These stages, viz. the pollen mother cells stage, tetrad stage and uninucleate pollen stage, were identified by analyzing paraffin sections of floral buds during rapid expansion periods. A total of 18,393 transcripts, 414 putative lncRNAs and 372 miRNAs were identified, of which 5,324 genes, 115 lncRNAs, and 44 miRNAs were differentially accumulated across three developmental stages. Of these, 44 and 92 genes were predicted be regulated by 37 and 30 differentially accumulated lncRNAs and miRNAs, respectively. Additionally, 42 differentially accumulated lncRNAs were predicted as targets of 27 miRNAs. Gene ontology enrichment indicated that potential target genes of lncRNAs were enriched in photosystem II, regulation of autophagy and carbohydrate phosphatase activity, which are essential for anther development. Functional annotation of genes targeted by miRNAs indicated that they are relevant to transcription and metabolic processes that play important roles in microspore development. An interaction network was built with 2 lncRNAs, 6 miRNAs and 10 mRNAs. Among these, miR396 and miR156 family were up-regulated, while their targets, genes (GROWTH REGULATING FACTORS and SQUAMOSA PROMOTER BINDING PROTEIN-LIKE genes) and lncRNAs, were down-regulated. Further, the trans-regulated targets of these lncRNAs, like wall-associated kinase2 and phosphomannose isomerase1, are involved in pollen wall formation during anther development. CONCLUSIONS: This study unravels lncRNAs, miRNAs and miRNA-lncRNA-mRNA networks involved in development of anthers of the tropical C. oleifera lays a theoretical foundation for further elucidation of regulatory roles of lncRNAs and miRNAs in anther development.

Third-generation sequencing and metabolome analysis reveal candidate genes and metabolites with altered levels in albino jackfruit seedlings.

BACKGROUND: Most plants rely on photosynthesis; therefore, albinism in plants with leaves that are white instead of green causes slow growth, dwarfing, and even death. Although albinism has been characterized in annual model plants, little is known about albino trees. Jackfruit (Artocarpus heterophyllus) is an important tropical fruit tree species. To gain insight into the mechanisms underlying the differential growth and development between albino jackfruit mutants and green seedlings, we analyzed root, stem, and leaf tissues by combining PacBio single-molecule real-time (SMRT) sequencing, high-throughput RNA-sequencing (RNA-seq), and metabolomic analysis. RESULTS: We identified 8,202 differentially expressed genes (DEGs), including 225 genes encoding transcription factors (TFs), from 82,572 full-length transcripts. We also identified 298 significantly changed metabolites (SCMs) in albino A. heterophyllus seedlings from a set of 692 metabolites in A. heterophyllus seedlings. Pathway analysis revealed that these DEGs were highly enriched in metabolic pathways such as 'photosynthesis', 'carbon fixation in photosynthetic organisms', 'glycolysis/gluconeogenesis', and 'TCA cycle'. Analysis of the metabolites revealed 76 SCMs associated with metabolic pathways in the albino mutants, including L-aspartic acid, citric acid, succinic acid, and fumaric acid. We selected 225 differentially expressed TF genes, 333 differentially expressed metabolic pathway genes, and 76 SCMs to construct two correlation networks. Analysis of the TF-DEG network suggested that basic helix-loop-helix (bHLH) and MYB-related TFs regulate the expression of genes involved in carbon fixation and energy metabolism to affect light responses or photomorphogenesis and normal growth. Further analysis of the DEG-SCM correlation network and the photosynthetic carbon fixation pathway suggested that NAD-ME2 (encoding a malic enzyme) and L-aspartic acid jointly inhibit carbon fixation in the albino mutants, resulting in reduced photosynthetic efficiency and inhibited plant growth. CONCLUSIONS: Our preliminarily screening identified candidate genes and metabolites specifically affected in albino A. heterophyllus seedlings, laying the foundation for further study of the regulatory mechanism of carbon fixation during photosynthesis and energy metabolism. In addition, our findings elucidate the way genes and metabolites respond in albino trees.

Employing Shadows for Multi-Person Tracking Based on a Single RGB-D Camera.

Although there are many algorithms to track people that are walking, existing methods mostly fail to cope with occluded bodies in the setting of multi-person tracking with one camera. In this paper, we propose a method to use people's shadows as a clue to track them instead of treating shadows as mere noise. We introduce a novel method to track multiple people by fusing shadow data from the RGB image with skeleton data, both of which are captured by a single RGB Depth (RGB-D) camera. Skeletal tracking provides the positions of people that can be captured directly, while their shadows are used to track them when they are no longer visible. Our experiments confirm that this method can efficiently handle full occlusions. It thus has substantial value in resolving the occlusion problem in multi-person tracking, even with other kinds of cameras.

Factors Influencing the Participation of Shared Decision Making in Stable Coronary Artery Disease Patient: Protocol of a Mixed Methods Study.

INTRODUCTION: The "paternalistic decision-making model" is no longer well suited to the modern clinical environment, and therefore, shared decision making (SDM) has emerged as a key approach. Although the benefits of SDM have been largely reported, several studies have reported low participation in SDM in coronary artery disease (CAD) patients. The theory of planned behavior (TPB) model is one of the most frequently employed theoretical frameworks for predicting human behaviors. According to the TPB, intention is influenced by attitude, subjective norm, and perceived behavioral control, while behavior is influenced by both intention and perceived behavioral control. Therefore, we propose a mixed methods study based on TPB to investigate the status of Chinese stable coronary artery disease (SCAD) patients' participation in SDM, understand their experiences of SDM, and explore the factors that influence their participation in SDM. MATERIALS AND METHODS: An explanatory sequential mixed methods design will be used to explore the study aims, including a quantitative phase, a subsequent qualitative phase, and the final integration study. The quantitative study will use convenient sampling from the Affiliated Hospital of Hangzhou Normal University to conduct a cross-sectional survey (n ≥ 252). The qualitative study will be sampled using the maximum difference sampling method from the quantitative study results, and then the data will be collected through semi-structured interviews (n = 10-20). This study will use descriptive statistics and test hypotheses while considering a p-value of <0.05, which will be considered statistically significant. DISCUSSIONS: The study employs a mixed method approach with an explanatory sequential design, incorporating qualitative and quantitative methods to comprehensively understand the factors influencing SCAD patients' participation in SDM. Furthermore, these findings can inform the design of future intervention studies and provide healthcare providers with targeted information and communication to help SCAD patients make the most appropriate decisions. Study participants will be recruited using convenience sampling from just one single clinical setting, which may limit the findings' generalizability. ETHICS AND DISSEMINATION: This study has been approved by the Ethical Committee of the School of Nursing, Hangzhou Normal University (Approval No.: 2024013). All the participants will sign an informed consent form before participating in the survey. The corresponding results and conclusions will be disseminated in journals and conferences after the completion of the study.

Degradation of fluoride in groundwater by electrochemical fixed bed system with bauxite: performance and synergistic catalytic mechanism.

Fluoride pollution in water has garnered significant attention worldwide. The issue of fluoride removal remains challenging in areas not covered by municipal water systems. The industrial aluminum electrode and natural bauxite coordinated defluorination system (IE-BA) have been employed for fluoride removal. The experiment investigated the effects of pH, current density, and inter-electrode mineral layer thickness on the defluorination process of IE-BA. Additionally, the study examined the treatment efficiency of IE-BA for simulated water with varying F- concentrations and assessed its long-term performance. The results demonstrate that the defluorination efficiency can reach 98.4% after optimization. Moreover, irrespective of different fluoride concentrations, the defluorination rate exceeds 95.2%. After 72 hours of continuous operation, the defluorination rate reached 91.9%. The effluent exhibited weak alkalinity with a pH of around 8.0, and the voltage increased by 2.0 V compared to the initial moment. By analyzing the characterization properties of minerals and flocs, this study puts forward the possible defluorination mechanism of the IE-BA system. The efficacy of the IE-BA system in fluoride removal from water was ultimately confirmed, demonstrating its advantages in terms of defluorination ability under different initial conditions and resistance to complex interference. This study demonstrates that the IE-BA technology is a promising approach for defluorination.

Improving Global Generalization and Local Personalization for Federated Learning.

Federated learning aims to facilitate collaborative training among multiple clients with data heterogeneity in a privacy-preserving manner, which either generates the generalized model or develops personalized models. However, existing methods typically struggle to balance both directions, as optimizing one often leads to failure in another. To address the problem, this article presents a method named personalized federated learning via cross silo prototypical calibration (pFedCSPC) to enhance the consistency of knowledge of clients by calibrating features from heterogeneous spaces, which contributes to enhancing the collaboration effectiveness between clients. Specifically, pFedCSPC employs an adaptive aggregation method to offer personalized initial models to each client, enabling rapid adaptation to personalized tasks. Subsequently, pFedCSPC learns class representation patterns on clients by clustering, averages the representations within each cluster to form local prototypes, and aggregates them on the server to generate global prototypes. Meanwhile, pFedCSPC leverages global prototypes as knowledge to guide the learning of local representation, which is beneficial for mitigating the data imbalanced problem and preventing overfitting. Moreover, pFedCSPC has designed a cross-silo prototypical calibration (CSPC) module, which utilizes contrastive learning techniques to map heterogeneous features from different sources into a unified space. This can enhance the generalization ability of the global model. Experiments were conducted on four datasets in terms of performance comparison, ablation study, in-depth analysis, and case study, and the results verified that pFedCSPC achieves improvements in both global generalization and local personalization performance via calibrating cross-source features and strengthening collaboration effectiveness, respectively.

Neural Temporal Denoising for Indirect Illumination.

Various temporal denoising methods have been proposed to clean up the noise for real-time ray tracing (RTRT). These methods rely on the temporal correspondences of pixels between the current and previous frames, i.e. per-pixel screen-space motion vectors. However, the state-of-the-art temporal reuse methods with traditional motion vectors cause artifacts in motion occlusions. We accordingly propose a novel neural temporal denoising method for indirect illumination of Monte Carlo (MC) ray tracing at 1 sample per pixel. Based on end-to-end multi-scale kernel-based reconstruction, we apply temporally reliable dual motion vectors to facilitate better reconstruction of the occlusions, and also introduce additional motion occlusion loss to reduce ghosting artifacts. Experiments show that our method significantly reduces the over-blurring and ghosting artifacts while generating high-quality images at real-time rates.

Multiomics studies with co-transformation reveal microRNAs via miRNA-TF-mRNA network participating in wood formation in Hevea brasiliensis.

Introduction: MicroRNAs (miRNAs) are small endogenous non-coding RNAs that play an important role in wood formation in plants. However, the significance of the link between miRNAs and their target transcripts in wood formation remains unclear in rubber tree (Hevea brasiliensis). Methods: In this study, we induced the formation of reaction wood by artificially bending rubber trees for 300 days and performed small RNA sequencing and transcriptome deep sequencing (RNA-seq) to describe the complement of miRNAs and their targets contributing to this process. Results and discussion: We identified 5, 11, and 2 differentially abundant miRNAs in normal wood (NW) compared to tension wood (TW), in NW relative to opposite wood (OW), and between TW and OW, respectively. We also identified 12 novel miRNAs and 39 potential miRNA-mRNA pairs with different accumulation patterns in NW, TW, and OW. We noticed that many miRNAs targeted transcription factor genes, which were enriched in KEGG pathways associated with phenylpropanoid biosynthesis, phenylalanine metabolism, and pyruvate metabolism. Thus, miRNA-TF-mRNA network involved in wood formation via tension wood model were constructed. We validated the differential accumulation of miRNAs and their targets by RT-qPCR analysis and overexpressed miRNA in Nicotiana benthamiana with its potential target gene. These results will provide a reference for a deep exploration of growth and development in rubber tree.

Six-Degree-of-Freedom Posture Measurement Technologies Using Position Sensitive Detectors (PSDs): State of the Art.

Six degree-of-freedom (6-DOF) posture measurement is an important academic research topic which has been broadly applied in many fields. As a high-speed photoelectronic sensor with ultra-high resolution and precision, position sensitive detector (PSD) has shown to be one of the most competitive candidates in 6-DOF measurement. This review presents the research progress of PSD-based 6-DOF posture measurement systems in the field of large-scale equipment assembly, ultra-precision manufacturing and other emerging areas. A total of six methods for implementing 6-DOF measurement are summarized and their advantages and limitations are discussed. Meanwhile, the paper illustrates challenges, potential solutions and future development trends.

Integrated mRNA and Small RNA Sequencing Reveals microRNAs Associated With Xylem Development in Dalbergia odorifera.

Dalbergia odorifera is a rare and precious rosewood specie, whose wood is a very high-quality material for valuable furniture and carving crafts. However, limited information is available about the process of wood formation in D. odorifera. To determine genes that might be closely associated with the xylem differentiation process, we analyzed the differentially expressed genes (DEGs) and microRNAs (miRNAs) from specific xylem tissues of D. odorifera by RNA sequencing (RNA-seq) and small RNA sequencing (small RNA-seq). In total, we obtained 134,221,955 clean reads from RNA-seq and 90,940,761 clean reads from small RNA-seq. By comparing the transition zone (Dotz) and sapwood (Dosw) samples, a total of 395 DEGs were identified. Further analysis revealed that DEGs encoded for WRKY transcription factors (eight genes), lignin synthesis (PER47, COMT, CCR2), cell wall composition (UXS2), gibberellin synthesis (KAO2, GA20OX1), jasmonic acid synthesis (OPR2, CYP74A), and synthesis of flavonoids (PAL2) and terpenoids (CYP71A1). Subsequently, a preliminary analysis by small RNA-seq showed that the expressions of 14 miRNAs (such as miR168a-5p, miR167f-5p, miR167h-5p, miR167e, miR390a, miR156g, novel_52, and novel_9) were significantly different between Dotz and Dosw. Further analysis revealed that the target genes of these differentially expressed miRNAs were enriched in the GO terms "amino acid binding," "cellulase activity," and "DNA beta-glucosyltransferase activity". Further, KEGG pathway annotation showed significant enrichment in "fatty acid elongation" and "biosynthesis of unsaturated fatty acids". These processes might be participating in the xylem differentiation of D. odorifera. Next, expression correlation analysis showed that nine differentially expressed miRNAs were significantly negatively associated with 21 target genes, which encoded for proteins such as pyrH, SPL6, SPL12, GCS1, and ARF8. Overall, this is the first study on miRNAs and their potential functions in the xylem development of D. odorifera, which provides a stepping stone for a detailed functional investigation of D. odorifera miRNAs.

Soluble Flt-1 in AMI Patients Serum Inhibits Angiogenesis of Endothelial Progenitor Cells by Suppressing Akt and Erk's Activity.

In acute myocardial infarction (AMI), endothelial progenitor cells (EPCs) are essential for the recovery of collateral circulation via angiogenesis. Clinical research has shown that the poor prognosis of the patients with AMI is closely associated with the cell quantity and function of EPCs. Whether there are differences in the biological features of EPCs from AMI patients and healthy subjects is worth exploring. In this study, EPCs were isolated from human peripheral blood and identified as late-stage EPCs by flow cytometry, immunofluorescence, and blood vessel formation assay. Compared to healthy subjects, AMI patients had more EPCs in the peripheral blood compared to healthy subjects. In addition, EPCs from AMI patients exhibited higher migration ability in the transwell assay compared to EPCs from healthy subjects. However, no difference in the angiogenesis of EPCs was observed between AMI patients and healthy subjects. Further studies revealed that soluble vascular endothelial growth factor receptor 1 (sFlt-1) in the serum of AMI patients was involved in the inhibition of EPCs angiogenesis by suppressing the Akt and Erk pathways. In conclusion, this study demonstrated that elevated serum sFlt-1 inhibits angiogenesis of EPC in AMI patients. Our findings uncover a pathogenic role of sFlt-1 in AMI.

Interactive Simulation of Scattering Effects in Participating Media Using a Neural Network Model.

Rendering participating media is important to the creation of photorealistic images. Participating media has a translucent aspect that comes from light being scattered inside the material. For materials with a small mean-free-path (mfp), multiple scattering effects dominate. Simulating these effects is computationally intensive, as it requires tracking a large number of scattering events inside the material. Existing approaches precompute multiple scattering events inside the material and store the results in a table. During rendering time, this table is used to compute the scattering effects. While these methods are faster than explicit scattering computation, they incur higher storage costs. In this paper, we present a new representation for double and multiple scattering effects that uses a neural network model. The scattering response from all homogeneous participating media is encoded into a neural network in a preprocessing step. At run time, the neural network is then used to predict the double and multiple scattering effects. We demonstrate the effects combined with Virtual Ray Lights (VRL), although our approach can be integrated with other rendering algorithms. Our algorithm is implemented on GPU. Double and multiple scattering effects for the entire participating media space are encoded using only 23.6 KB of memory. Our method achieves 50 ms per frame in typical scenes and provides results almost identical to the reference.

RNA Sequencing Reveals Phenylpropanoid Biosynthesis Genes and Transcription Factors for Hevea brasiliensis Reaction Wood Formation.

Given the importance of wood in many industrial applications, much research has focused on wood formation, especially lignin biosynthesis. However, the mechanisms governing the regulation of lignin biosynthesis in the rubber tree (Hevea brasiliensis) remain to be elucidated. Here, we gained insight into the mechanisms of rubber tree lignin biosynthesis using reaction wood (wood with abnormal tissue structure induced by gravity or artificial mechanical treatment) as an experimental model. We performed transcriptome analysis of rubber tree mature xylem from tension wood (TW), opposite wood (OW), and normal wood (NW) using RNA sequencing (RNA-seq). A total of 214, 1,280, and 32 differentially expressed genes (DEGs) were identified in TW vs. NW, OW vs. NW, and TW vs. OW, respectively. GO and KEGG enrichment analysis of DEGs from different comparison groups showed that zeatin biosynthesis, plant hormone signal transduction, phenylpropanoid biosynthesis, and plant-pathogen interaction pathways may play important roles in reaction wood formation. Sixteen transcripts involved in phenylpropanoid biosynthesis and 129 transcripts encoding transcription factors (TFs) were used to construct a TF-gene regulatory network for rubber tree lignin biosynthesis. Among them, MYB, C2H2, and NAC TFs could regulate all the DEGs involved in phenylpropanoid biosynthesis. Overall, this study identified candidate genes and TFs likely involved in phenylpropanoid biosynthesis and provides novel insights into the mechanisms regulating rubber tree lignin biosynthesis.

Silhouette smoothing for real-time rendering of mesh surfaces.

Coarse piecewise linear approximation of surfaces causes undesirable polygonal appearance of silhouettes. We present an efficient method for smoothing the silhouettes of coarse triangle meshes using efficient 3D curve reconstruction and simple local re-meshing. It does not assume the availability of a fine mesh and generates only moderate amount of additional data at run time. Furthermore, polygonal feature edges are also smoothed in a unified framework. Our method is based on a novel interpolation scheme over silhouette triangles and this ensures that smooth silhouettes are faithfully reconstructed and always change continuously with respect to continuous movement of the view point or objects. We speed up computation with GPU assistance to achieve real-time rendering of coarse meshes with the smoothed silhouettes. Experiments show that this method outperforms previous methods for silhouette smoothing.

Generic Content-Based Retrieval of Marker-Based Motion Capture Data.

In this work, we propose an original scheme for generic content-based retrieval of marker-based motion capture data. It works on motion capture data of arbitrary subject types and arbitrary marker attachment and labelling conventions. Specifically, we propose a novel motion signature to statistically describe both the high-level and the low-level morphological and kinematic characteristics of a motion capture sequence, and conduct the content-based retrieval by computing and ordering the motion signature distance between the query and every item in the database. The distance between two motion signatures is computed by a weighted sum of differences in separate features contained in them. For maximum retrieval performance, we propose a method to pre-learn an optimal set of weights for each type of motion in the database through biased discriminant analysis, and adaptively choose a good set of weights for any given query at the run time. Excellence of the proposed scheme is experimentally demonstrated on various data sets and performance metrics.