Preozonation of Chlorophenolic Wastewater for Subsequent Biological Treatment

Preozonation was investigated for its effects on the biodegradability of five chlorophenolic compounds in activated-sludge systems. The biodegradability was expressed in terms of the oxidation of each compound itself and of the total organic contents of the whole sample.

Results indicate that preozonation could either promote or retard the biodegradability, depending primarily on whether or not the sludge used in the subsequent biological system had been acclimated beforehand. For unacclimated sludge, preozonation was found to be helpful in promoting the biodegradability of all the compounds, especially the chlorophenols with a meta-position chlorine attachment. For acclimated sludge, a reverse effect generally, was observed.     

低温等离子体处理模式对冷藏南美白对虾中假单胞菌的抑菌效果及机理研究

摘 要：目的 探究低温等离子体(cold plasma, CP)处理模式对冷藏南美白对虾中常见荧光假单胞菌(Pseudomonas fluorescens)的抑菌效果及其作用机制。方法 通过CP直接处理和循环处理P. fluorescens,研究了两种处理模式下臭氧含量动态变化对P. fluorescens的生长曲线、细胞活力,生物膜形成、细胞壁、细胞膜完整性和南美白对虾菌落总数及假单胞菌数等指标的影响。结果 两种处理模式在CP处理3 min或3 cycles后,包装内臭氧含量达到最高值,分别为(850±10) mg/m3和(874±20) mg/m3。CP循环处理模式使得臭氧含量随处理循环数递增,因此获得更长的臭氧存在时间从而具有更大的抑菌能力。P. fluorescens生长曲线表明CP处理使得菌体延迟期变长且对数生长期推迟。此外,CP处理后的P. fluorescens细胞活力显著下降(P<0.05),CP-1 min,CP-3 min和CP-3 cycles组的细胞活力分别为33.03%、5.90%和4.82%。同时相比CP-3 min组,CP-3 cycles组的P. fluorescens生物膜OD值下降27.61%。碱性磷酸酶(alkaline phosphatase, AKP)活性和核酸蛋白泄漏量结果表明,细胞壁和细胞膜完整性受损可能是P. fluorescens失活的直接原因。对虾保鲜测试结果证实,贮藏第6 d,CP-3 cycles组虾体中的菌落总数和假单胞菌数相比CP-3 min组分别降低了58.02%和79.54%。结论 CP循环处理模式通过延长对臭氧与对虾的暴露时间,提高了对P. fluorescens的灭活效果,同时还具有更优越的保鲜能力。本研究为开发基于CP技术的新型保鲜技术应用提供了理论参考。 关键词：低温等离子体;荧光假单胞菌;抑菌机制;保鲜     

云数据中心时延优化的数据放置方法

针对云数据中心数据获取效率低和服务器资源浪费问题,为优化云平台的数据访问和资源利用,文中提出了一种时延优化的云数据中心数据放置（LOP）方法。文中首先分析了云平台的性能,建立了云平台的资源利用和数据获取时间模型。然后基于非支配排序算法NSGA-Ⅲ实现了全局最优的数据放置策略,对数据资源进行合理部署,有效利用服务器的资源,提高了数据获取的效率。最后通过CloudSim仿真平台,对提出的数据放置方法进行了仿真和对比实验。实验结果表明,LOP方法能明显提高云服务器的资源利用率,缩短任务的数据获取时间。     

Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

Proximity-Induced Fully Ferromagnetic Order with Eightfold Magnetic Anisotropy in Heavy Transition Metal Oxide CaRuO3

Ferromagnetic materials with a strong spin-orbit coupling (SOC) have attracted much attention in recent years because of their exotic properties and potential applications in energy-efficient spintronics. However, such materials are scarce in nature. Here, a proximity-induced paramagnetic to ferromagnetic transition for the heavy transition metal oxide CaRuO₃ in (001)-(LaMnO₃/CaRuO₃) superlattices is reported. Anomalous Hall effect is observed in the temperature range up to 180 K. Maximal anomalous Hall conductivity and anomalous Hall angle are as large as ∼15 Ω⁻¹ cm⁻¹ and ∼0.93%, respectively, by one to two orders of magnitude larger than those of the typical 3d ferromagnetic oxides such as La_0.67Sr_0.33MnO₃. Density functional theory calculations indicate the existence of avoid band crossings in the electronic band structure of the ferromagnetic CRO layer, which enhances Berry curvature thus strong anomalous Hall effects. Further evidences from polarized neutron reflectometry show that the CaRuO₃ layers are in a fully ferromagnetic state (∼0.8 μ_B/Ru), in sharp contrast to the proximity-induced canted antiferromagnetic state in 5d oxides SrIrO₃ and CaIrO₃ (∼0.1 μ_B/Ir). More than that, the magnetic anisotropy of the (001)-(LaMnO₃/CaRuO₃) superlattices is eightfold symmetric, showing potential applications in the technology of multistate data storage.     

Graph-based fine-grained model selection for multi-source domain

Pattern Analysis and Applications - The prosperity of datasets and model architectures has led to the development of pretrained source models, which simplified the learning process in multi-domain...     

Point cloud completion via structured feature maps using a feedback network

Computational Visual Media - In this paper, we tackle the challenging problem of point cloud completion from the perspective of feature learning. Our key observation is that to recover the...     

Stabilization of uncertain networked control systems with actuator saturation and probabilistic cyberattacks

This paper investigates the stabilization of uncertain networked control systems (NCSs) with actuator saturation and cyberattacks. The cyberattacks are governed by a set of independent random variables satisfying Bernoulli distribution. To relieve the network bandwidth load effectively, an event-triggered communication strategy is proposed. By employing Lyapunov stability theory and stochastic analysis techniques, a stability criterion is obtained for the system with actuator saturation and cyberattacks. Moreover, the desired controller gain is derived by solving some matrix inequalities. Finally, the validity and applicability of the criteria are verified through numerical examples.     

Syntax–Aware graph convolutional network for the recognition of chinese implicit inter-sentence relations

The Journal of Supercomputing - In the literature, most previous studies on English implicit inter-sentence relation recognition only focused on semantic interactions, which could not exploit the...