Autofocusing of laser lithography through the crosshair projection method.

In laser direct writing lithography, there is not any image information from the sample surface, which makes it difficult to find the position of the focal plane. To overcome the problem, an autofocusing through the crosshair projection method is proposed in this work. The crosshair on the reticle is inserted into the lighting path and imaged onto the sample surface. The addition of the crosshair projection increases the image information from the sample surface, meeting the requirement for the image information in focusing and improving the focusing environment. Furthermore, this work presents what we believe to be a new division of the focusing curve based on the range of the perpendicular feature extracted from the crosshair projection during the focusing process. The perpendicular feature can be extracted from the crosshair projection in the focusing zone but not in the flat zone. Compared with the traditional division, this new division enables the use of the perpendicular feature to directly determine the zone of the current sample position and to find the focusing zone during the focusing process. This can completely filter out the interference of local fluctuations in the flat zone, greatly facilitating the sample focusing. The autofocusing process was designed based on this division, and experiments were carried out accordingly. The focusing accuracy is about 0.15 µm, which is in the range of the depth of focus of the optical system. The results show that the proposed method provides a good solution to achieve accurate focusing based on the crosshair projection image from the sample surface in laser lithography.

TDMD: A Database for Dynamic Color Mesh Quality Assessment Study.

Dynamic colored meshes (DCM) are widely used in various applications. However, this kind of meshes may undergo different processes, such as compression or transmission, which can distort them and degrade their quality. To facilitate the development of objective metrics for DCMs and study the influence of typical distortions on their perception, we create the Tencent - Dynamic colored Mesh Database (TDMD) containing eight reference DCM objects with six typical distortions. Using processed video sequences (PVS) derived from the DCM, we conduct a large-scale subjective experiment that resulted in 303 distorted DCM samples with mean opinion scores, making the TDMD the largest available DCM database to our knowledge. This database enables us to study the impact of different types of distortion on human perception and offers recommendations for DCM compression and related tasks. Additionally, we have evaluated three types of state-of-the-art objective metrics on the TDMD, including image-based, point-based, and video-based metrics, on the TDMD. Our experimental results highlight the strengths and weaknesses of each metric, and we provide suggestions about the selection of metrics in practical DCM applications. The TDMD is publicly available at the following location: https://multimedia.tencent.com/resources/tdmd.

TCDM: Transformational Complexity Based Distortion Metric for Perceptual Point Cloud Quality Assessment.

The goal of objective point cloud quality assessment (PCQA) research is to develop quantitative metrics that measure point cloud quality in a perceptually consistent manner. Merging the research of cognitive science and intuition of the human visual system (HVS), in this paper, we evaluate the point cloud quality by measuring the complexity of transforming the distorted point cloud back to its reference, which in practice can be approximated by the code length of one point cloud when the other is given. For this purpose, we first make space segmentation for the reference and distorted point clouds based on a 3D Voronoi diagram to obtain a series of local patch pairs. Next, inspired by the predictive coding theory, we utilize a space-aware vector autoregressive (SA-VAR) model to encode the geometry and color channels of each reference patch with and without the distorted patch, respectively. Assuming that the residual errors follow the multi-variate Gaussian distributions, the self-complexity of the reference and transformational complexity between the reference and distorted samples are computed using covariance matrices. Additionally, the prediction terms generated by SA-VAR are introduced as one auxiliary feature to promote the final quality prediction. The effectiveness of the proposed transformational complexity based distortion metric (TCDM) is evaluated through extensive experiments conducted on five public point cloud quality assessment databases. The results demonstrate that TCDM achieves state-of-the-art (SOTA) performance, and further analysis confirms its robustness in various scenarios. The code will be publicly available at https://github.com/zyj1318053/TCDM.

GPA-Net:No-Reference Point Cloud Quality Assessment with Multi-task Graph Convolutional Network.

With the rapid development of 3D vision, point cloud has become an increasingly popular 3D visual media content. Due to the irregular structure, point cloud has posed novel challenges to the related research, such as compression, transmission, rendering and quality assessment. In these latest researches, point cloud quality assessment (PCQA) has attracted wide attention due to its significant role in guiding practical applications, especially in many cases where the reference point cloud is unavailable. However, current no-reference metrics which based on prevalent deep neural network have apparent disadvantages. For example, to adapt to the irregular structure of point cloud, they require preprocessing such as voxelization and projection that introduce extra distortions, and the applied grid-kernel networks, such as Convolutional Neural Networks, fail to extract effective distortion-related features. Besides, they rarely consider the various distortion patterns and the philosophy that PCQA should exhibit shift, scaling, and rotation invariance. In this paper, we propose a novel no-reference PCQA metric named the Graph convolutional PCQA network (GPA-Net). To extract effective features for PCQA, we propose a new graph convolution kernel, i.e., GPAConv, which attentively captures the perturbation of structure and texture. Then, we propose the multi-task framework consisting of one main task (quality regression) and two auxiliary tasks (distortion type and degree predictions). Finally, we propose a coordinate normalization module to stabilize the results of GPAConv under shift, scale and rotation transformations. Experimental results on two independent databases show that GPA-Net achieves the best performance compared to the state-of-the-art no-reference PCQA metrics, even better than some full-reference metrics in some cases. The code is available at: https://github.com/Slowhander/GPA-Net.git.

[Soil respiration rate and its influencing factors in artificial land-bridge islands system]. / äººå·¥é™†æ¡¥å²›å±¿ç³»ç»ŸåœŸå£¤å‘¼å¸é€ŸçŽ‡åŠå ¶å½±å“å› å­.

It is of great significance to understand the pattern of soil respiration rate in fragmented forests for further revealing terrestrial ecosystem carbon cycling. With different habitats (island vs. mainland, island edge vs. island interior) of the artificial land-bridge island system in Thousand Island Lake (TIL) region as the objects, we analyzed the seasonal dynamics of soil respiration rate and its relationships with soil physicochemical factors. The results showed that: 1) Soil respiration rates varied significantly across different seasons, with an order of summer (3.74 µmol·m-2·s-1) > autumn (2.30 µmol·m-2·s-1) > spring (1.82 µmol·m-2·s-1) > winter (1.40 µmol·m-2·s-1). 2) Forest fragmentation had significant effects on soil respiration rate, with soil respiration rate of island (2.37 µmol·m-2·s-1) being significantly higher than that of mainland (2.08 µmol·m-2·s-1) and the soil respiration rate of island edge (2.46 µmol·m-2·s-1) being significantly higher than that of island interior (2.03 µmol·m-2·s-1). 3) Soil temperature significantly promoted soil respiration rate, explaining 56.1% of the total variation. 4) There was a significant positive correlation between soil respiration rate and soil total carbon, ammo-nium nitrogen content, and vegetation coverage. The soil total carbon and ammonium nitrogen content of island edge were significantly higher than those of island interior. In all, forest fragmentation promoted soil respiration rate, with soil physicochemical factors as the drivers for its variation.

[Effect of thyroxine on the expression of HIF-1α after aneurysmal subarachnoid hemorrhage in rat brain and its mechanism].

Objective: To investigate the effect of thyroxine (T4) on the expression of hypoxia inducible factor-1α (HIF-1α) in rat brain after aneurysmal subarachnoid hemorrhage (SAH) and its mechanism. Methods: Seventy-two adult male SD rats were randomly divided into the following 4 groups: subarachnoid hemorrhage model group(SAH), subarachnoid hemorrhage model and T4 group (SAH with T4), subarachnoid hemorrhage model with normal saline group (SAH with vehicle), and sham-operation group, 18 rats in each group. The model of subarachnoid hemorrhage group was established by internal carotid artery puncture. CT plain scan was performed after the modeling immediately, T4 was administrated by intraabdominal injection of 3 µg/100 g every 24 hours for 3 days. SAH with T4 group was treated with thyroxine. SAH with vehicle group was treated with equal volume vehicle, all of them were killed 72 hours after modeling. The brain water content was determined to evaluate the brain edema, the apoptosis of cerebral cortex cells was detected by TUNEL method, and HIF-1α protein and p-Akt protein in cerebral cortex were detected by immunohistochemistry in six SD rats of each group. Results: After the modeling, the brain tissues of SAH group, SAH + T4 group and SAH +vehicle group were swollen obviously, and blood clots were observed in subarachnoid space. The neurobehavioral score,the brain water content, apoptosis index, HIF-1α protein and p-Akt protein in SAH group were significantly higher than those in sham-operation group(P＜0.05).The neurobehavioral score,HIF-1α protein and p-Akt protein in SAH with T4 group were significantly higher than those in SAH group, and the brain water content, apoptosis index were significantly lower than those in SAH group (P＜0.05). Conclusion: The expression of HIF-1α protein in the brain of rats after aneurysm subarachnoid hemorrhage can be upregulated by T4 replacement therapy, which may by activating the signal pathway of inositol triphosphate kinase / protein kinase B (PI3K/Akt). Finally, apoptosis index was decreased, the rat behavior was improved and the brain was protected.

Analysis of synonymous codon usage and evolution of begomoviruses.

Begomoviruses are single-stranded DNA viruses and cause severe diseases in major crop plants worldwide. Based on current genome sequence analyses, we found that synonymous codon usage variations in the protein-coding genes of begomoviruses are mainly influenced by mutation bias. Base composition analysis suggested that the codon usage bias of AV1 and BV1 genes is significant and their expressions are high. Fourteen codons were determined as translational optimal ones according to the comparison of codon usage patterns between highly and lowly expressed genes. Interestingly the codon usages between begomoviruses from the Old and the New Worlds are apparently different, which supports the idea that the bipartite begomoviruses of the New World might originate from bipartite ones of the Old World, whereas the latter evolve from the Old World monopartite begomoviruses.