Bi-Dbar-Approach for a Coupled Shifted Nonlocal Dispersionless System

We propose a Bi-Dbar approach and apply it to the extended coupled shifted nonlocal dispersionless system. We introduce the nonlocal reduction to solve the coupled shifted nonlocal dispersionless system. Since no enough constraint conditions can be found to curb the norming contants in the Dbar data, the “solutions” obtained by the Dbar dressing method, in general, do not admit the coupled shifted nonlocal dispersionless system. In the Bi-Dbar approach to the extended coupled shifted nonlocal dispersionless system, the norming constants are free. The constraint conditions on the norming constants are determined by the general nonlocal reduction, and the solutions of the coupled shifted nonlocal dispersionless system are derived

UniMOS: A Universal Framework For Multi-Organ Segmentation Over Label-Constrained Datasets

Machine learning models for medical images can help physicians diagnose and manage diseases. However, due to the fact that medical image annotation requires a great deal of manpower and expertise, as well as the fact that clinical departments perform image annotation based on task orientation, there is the problem of having fewer medical image annotation data with more unlabeled data and having many datasets that annotate only a single organ. In this paper, we present UniMOS, the first universal framework for achieving the utilization of fully and partially labeled images as well as unlabeled images. Specifically, we construct a Multi-Organ Segmentation (MOS) module over fully/partially labeled data as the basenet and designed a new target adaptive loss. Furthermore, we incorporate a semi-supervised training module that combines consistent regularization and pseudolabeling techniques on unlabeled data, which significantly improves the segmentation of unlabeled data. Experiments show that the framework exhibits excellent performance in several medical image segmentation tasks compared to other advanced methods, and also significantly improves data utilization and reduces annotation cost. Code and models are available at: https://github.com/lw8807001/UniMOS.Comment: Accepted by BIBM202

Sub-100 fs watt-level Kerr-lens mode-locked Yb:CaYAlO4 laser with a gigahertz repetition rate

We report a 1.04 GHz high-power Kerr-lens mode-locked Yb:CaYAlO4 laser pumped by a single-mode fiber laser at 976 nm. Based on a bow-tie cavity, stable unidirectional mode-locked operation is obtained with an output coupler of 1.6%. The oscillator delivers pulses with an average power of 1.46 W and with the pulse duration of 99 fs, which, to the best of our knowledge, is the first gigahertz-level Kerr-lens mode-locked laser based on the Yb:CaYAlO4 gain medium. We believe that the watt-level solid-state femtosecond laser at GHz would be an excellent source for developing time-resolved broadband dual-comb spectroscopy

Yields, Quality and Metal Accumulation of Chinese Cabbage Irrigated with Diary Effluent

Abstract: In order to investigate the short-term effects of wastewater (dairy effluent) and EM treated wastewater on cabbage quality (vitamin C, nitrate), yield, Nitrogen (N) and Phosphorous (P) uptakes and heavy metals (i.e., Hg, Pb and Cd) accumulation in Cabbage, field experiments were conducted with the following irrigation treatments: Clean Water (CW), Waste Water (WW), Reclaimed Water-EM treated wastewater (RW), Clear Water-wastewater rotation (C/W) and clear water-treated wastewater rotation (C/R). The results showed that: yield of cabbages, concentration of total N and P in cabbages could be improved in treatment irrigated with both untreated and EM treated dairy effluent, especially in treatments RW and C/R. Heavy metals in cabbages irrigated with/without dairy effluent showed non-significant difference. The highest nitrate was obtained with C/W treatment and the lowest was obtained with the RW treatment. With integrate comparative study of nutrition, nitrate and heavy metal, EM treated dairy effluent is more suitable to irrigate cabbage than raw dairy effluent. And the cabbages under RW and C/W treatment grew better than other treatments. It is suggested that the EM treated wastewater can be used as a safe alternative for irrigation of cabbages edible

Effect of Plant Buffer Zone–Antifouling Curtain Wall on Reducing Non-Point Source Pollution in Paddy Fields, China

In view of the nitrogen and phosphorus non-point source pollution caused by paddy field drainage in southern China, two paddy fields in Nanjing and Yuyao cities were selected to study the effect of plant buffer zone–antifouling curtain walls on reducing non-point source pollution. The results showed that the designed plant buffer zone–antifouling curtain wall systems could significantly reduce the concentration of total nitrogen (TN) and total phosphorus (TP) in drainage of the two paddy fields. Compared with paddy field drainage in Nanjing, the interception rate of TN in the plant buffer zone and antifouling curtain wall were 33.0% and 59.3%, respectively; the removal rates of TP were about 18.4% and 40.3%, respectively. In addition, the contents of ammoniacal nitrogen (NH3-N), nitrate nitrogen (NO3-N) and Chemical Oxygen Demand (COD) were also significantly reduced. For the Yuyao experimental area, compared to the paddy field without the soil plant buffer zone (the control), the concentration of each indicator in the discharge water of the paddy fields with the soil plant buffer system operation mode was significantly reduced, the rejection rate of the TP, TN, total dissolved phosphorus (TDP), NO3-N and NH3-N were 64.28%, 70.66%, 83.73%, 65.22% and 80.69%, respectively. In summary, the construction of a plant buffer zone–antifouling curtain wall (soil plant buffer zone) has an obvious effect on the reduction of non-point source pollution in paddy fields, which could improve yield and fertilizer utilization. The plant buffer zone–antifouling curtain wall could be popularized and applied in local areas and southern China

A multi-layer fusion image enhancement method for visual odometry under poor visibility scenarios

Visual odometry (VO) is important in robotic rescue and navigation operations; however, poor visibility scenarios, which are characterised by weak illumination, few textures, and self-similarity, seriously influence image quality and image matching capability, thus degrading VO performance. This study proposes a multi-layer fusion image enhancement method to ensure VO performance under poor visibility scenarios. Our method can achieve a trade-off between naturalness preservation, texture feature enhancement, contrast improvement, and noise suppression. To achieve this, we first decomposed input images into illumination, reflectance, and detail layers. Subsequently, we designed multiple weighting strategies in the illumination layer to preserve naturalness and improve contrast and applied a linear operation to enhance the colour contrast in the reflectance layer. A double-interval frequency optimisation model was also applied to enhance the textures in the detail layer. Finally, these layers were recombined to obtain an enhanced image. Our experimental results demonstrated our quantitative and qualitative superiority over six other methods under poor-visibility scenarios. The overall performance revealed that our method can effectively improve image matching and VO results

Measuring Capacity Indicators of Civil Society for Environmental Management in Beijing Based on an Attitudinal Survey <Article>

There exist some limitations when applying macro-level data to measure social capacity for environmental management. Especially, such macro-level data cannot properly measure the quality of environmental management. This paper attempts to measure the capacity indicators of civil society based on an attitudinal survey, which is designed with the help of the concepts of Good Urban Governance and Service Quality. A case study is conducted in Beijing and finds that the citizens perceive that the capacities of government, firms and civil society interact with each other. It is also confirmed that capacity of civil capacity has the largest influence on people's health, livability, and ecosystems