Emission Inventory for PFOS in China: Review of Past Methodologies and Suggestions

Perfluorooctane sulfonate (PFOS) is a persistent, bioaccumulative, and toxic chemical that has the potential for long-range transport in the environment. Its use in a wide variety of consumer products and industrial processes makes a detailed characterization of its emissions sources very challenging. These varied emissions sources all contribute to PFOS' existence within nearly all environmental media. Currently, China is the only country documented to still be producing PFOS, though there is no China PFOS emission inventory available. This study reviews the inventory methodologies for PFOS in other countries to suggest a China-specific methodology framework for a PFOS emission inventory. The suggested framework combines unknowns for PFOS-containing product penetration into the Chinese market with product lifecycle assumptions, centralizing these diverse sources into municipal sewage treatment plants. Releases from industrial sources can be quantified separately using another set of emission factors. Industrial sources likely to be relevant to the Chinese environment are identified

A CMAC-Based Systematic Design Approach of an Adaptive Embedded Control Force Loading System

In this chapter, an adaptive embedded control system is developed to measure yield strength of the material plate with an applied load. A systematic approach is proposed to handle special requirements of embedded control systems which are different from computer-based control systems as there are much less computational power and hardware resources available. Efficient control algorithm has to be designed to remove CPU burden so that the microcontroller has enough power available. A three-step approach is proposed to address the embedded control issue: Firstly, the mathematical description of the whole system is studied using both theoretical and experimental methods. A mathematical model is derived from the physical models of each component used, and an experiment is retrieved by employing Levy’s method and least square estimation to identify specific parameters of the system model. Secondly, an adaptive feedforward plus feedback controller is designed and simulated as a preparation for the embedded system implementation. The Cerebellar Model Articulation Controller (CMAC) is chosen as the feedforward part, and a PD controller is used as the feedback part to train the CMAC. Finally, the proposed algorithm is applied to the embedded system, and experiments are conducted to verify both the identified model and designed controller

Case Report: Clinical benefit from multi-target tyrosine kinase inhibitor and PARP inhibitor in a patient with cancer of unknown primary with BRCA1 large genomic rearrangement

Background: Cancer of unknown primary (CUP), which accounts for 3%–5% of new cancer cases every year, involves the presence of a type of histologically confirmed metastatic tumors whose primary site cannot be confirmed by conventional diagnostic methods. This difficulty in identifying the primary site means that CUP patients fail to receive precisely targeted therapy. Most patients are treated with empiric chemotherapy, with a median survival of 6 months and even poorer prognosis within an unfavorable subset of CUP.Case report: An 80-year-old woman presented with masses in the abdomen. Following comprehensive imagological and immunohistochemical examinations, she was diagnosed with CUP. She emphatically declined chemotherapy; thus, anlotinib has been administered with patient consent since 02/07/2019, and stable disease (SD) was observed for 2 years. During subsequent treatment, a large genomic rearrangement in BRCA1 was identified in the patient via NGS, and SD was observed for a further 6 months following olaparib treatment. The type of LGR identified in this patient was discovered to be BRCA1 exon 17-18 inversion (inv), which has never been previously reported.Conclusion: For CUP patients, a chemo-free regimen seems to be acceptable as a first-line treatment, and NGS-guided targeted treatment could improve patient outcomes

Bacillus cereus Isolated From Vegetables in China: Incidence, Genetic Diversity, Virulence Genes, and Antimicrobial Resistance

Bacillus cereus is a food-borne opportunistic pathogen that can induce diarrheal and emetic symptoms. It is widely distributed in different environments and can be found in various foods, including fresh vegetables. As their popularity grows worldwide, the risk of bacterial contamination in fresh vegetables should be fully evaluated, particularly in vegetables that are consumed raw or processed minimally, which are not commonly sterilized by enough heat treatment. Thereby, it is necessary to perform potential risk evaluation of B. cereus in vegetables. In this study, 294 B. cereus strains were isolated from vegetables in different cities in China to analyze incidence, genetic polymorphism, presence of virulence genes, and antimicrobial resistance. B. cereus was detected in 50% of all the samples, and 21/211 (9.95%) of all the samples had contamination levels of more than 1,100 MPN/g. Virulence gene detection revealed that 95 and 82% of the isolates harbored nheABC and hblACD gene clusters, respectively. Additionally, 87% of the isolates harbored cytK gene, and 3% of the isolates possessed cesB. Most strains were resistant to rifampicin and β-lactam antimicrobials but were sensitive to imipenem, gentamicin, ciprofloxacin, kanamycin, telithromycin, ciprofloxacin, and chloramphenicol. In addition, more than 95.6% of the isolates displayed resistance to three kinds of antibiotics. Based on multilocus sequence typing, all strains were classified into 210 different sequence types (STs), of which 145 isolates were assigned to 137 new STs. The most prevalent ST was ST770, but it included only eight isolates. Taken together, our research provides the first reference for the incidence and characteristics of B. cereus in vegetables collected throughout China, indicating a potential hazard of B. cereus when consuming vegetables without proper handling

Rootstock Alleviates Salt Stress in Grafted Mulberry Seedlings: Physiological and PSII Function Responses

This study investigated the effect of NaCl stress on Na+ and K+ absorption and transport by roots, nitrogen and phosphorus content in leaves, PSII photochemical activity and reactive oxygen species (ROS) in leaves of mulberry own-root seedlings and grafted seedlings. To determine the response, own-root seedlings of a high yielding mulberry cultivar, Tieba mulberry (Morus alba L.), and the grafted seedlings, obtained by using Qinglong mulberry with high salt tolerance as rootstock and Tieba mulberry as scion, were used. The Na+ content in roots and leaves of grafted seedlings was significantly lower than that in own-root seedlings under salt stress; while K+ content in roots and leaves of grafted seedlings was significantly higher than that in own-root seedlings. The root activity in grafted seedlings was significantly higher than that in own-root seedlings, as well as the content of nitrogen, phosphorous and water. PSII photochemical activity in leaves of grafted seedlings was less significantly affected by salt stress compared to own-root seedlings. The electron transport at the acceptor side of PSII from QA to QB was less affected by salt stress, which resulted in a significantly lower ROS content in leaves of grafted seedlings than that of own-root seedlings. Therefore, grafting high-yielding and good-quality Tieba mulberry with salt tolerant Qinglong mulberry as rootstock showed a relatively high salt tolerance. This may be because (1) the root system of rootstock presented high Na+ resistance and has selective absorption capacity for Na+ and K+ (2) the root system of rootstock prevented excess Na+ from being transported to aerial parts in order to reduce adverse effects of Na+ (3) the root system of rootstock had enhanced root activity under salt stress, which accelerated water and nutrient absorption (4) the leaves of grafted seedlings had higher PSII photochemical activity and electron transport rate compared with those of own-root seedlings under salt stress, which effectively reduced ROS burst mediated by photosynthesis and reduced oxidative damage

Matching-Based Virtual Network Function Embedding for SDN-Enabled Power Distribution IoT

The power distribution internet of things (PD-IoT) has the complex network architecture, various emerging services, and the enormous number of terminal devices, which poses rigid requirements on substrate network infrastructure. However, the traditional PD-IoT has the characteristics of single network function, management and maintenance difficulties, and poor service flexibility, which makes it hard to meet the differentiated quality of service (QoS) requirements of different services. In this paper, we propose the software-defined networking (SDN)-enabled PD-IoT framework to improve network compatibility and flexibility, and investigate the virtual network function (VNF) embedding problem of service orchestration in PD-IoT. To solve the preference conflicts among different VNFs towards the network function node (NFV) and provide differentiated service for services in various priorities, a matching-based priority-aware VNF embedding (MPVE) algorithm is proposed to reduce energy consumption while minimizing the total task processing delay. Simulation results demonstrate that MPVE significantly outperforms existing matching algorithm and random matching algorithm in terms of delay and energy consumption while ensuring the task processing requirements of high-priority services

Adaptive Barrier Control for Nonlinear Servomechanisms with Friction Compensation

This paper proposes an adaptive barrier controller for servomechanisms with friction compensation. A modified LuGre model is used to capture friction dynamics of servomechanisms. This model is incorporated into an augmented neural network (NN) to account for the unknown nonlinearities. Moreover, a barrier Lyapunov function (BLF) is utilized to each step in a backstepping design procedure. Then, a novel adaptive control method is well suggested to ensure that the full-state constraints are within the given boundary. The stability of the closed-loop control system is proved using Lyapunov stability theory. Comparative experiments on a turntable servomechanism confirm the effectiveness of the devised control method

UAV-Borne LiDAR Crop Point Cloud Enhancement Using Grasshopper Optimization and Point Cloud Up-Sampling Network

Because of low accuracy and density of crop point clouds obtained by the Unmanned Aerial Vehicle (UAV)-borne Light Detection and Ranging (LiDAR) scanning system of UAV, an integrated navigation and positioning optimization method based on the grasshopper optimization algorithm (GOA) and a point cloud density enhancement method were proposed. Firstly, a global positioning system (GPS)/inertial navigation system (INS) integrated navigation and positioning information fusion method based on a Kalman filter was constructed. Then, the GOA was employed to find the optimal solution by iterating the system noise variance matrix Q and measurement noise variance matrix R of Kalman filter. By feeding the optimal solution into the Kalman filter, the error variances of longitude were reduced to 0.00046 from 0.0091, and the error variances of latitude were reduced to 0.00034 from 0.0047. Based on the integrated navigation, an UAV-borne LiDAR scanning system was built for obtaining the crop point. During offline processing, the crop point cloud was filtered and transformed into WGS-84, the density clustering algorithm improved by the particle swarm optimization (PSO) algorithm was employed to the clustering segment. After the clustering segment, the pre-trained Point Cloud Up-Sampling Network (PU-net) was used for density enhancement of point cloud data and to carry out three-dimensional reconstruction. The features of the crop point cloud were kept under the processing of reconstruction model; meanwhile, the density of the crop point cloud was quadrupled

A high-reliability SEPIC converter with reconfigurable voltage conversion gain

A high-reliability SEPIC converter with reconfigurable voltage conversion gain is proposed, which is composed of a basic SEPIC converter and n extended units. Adopting an interleaved parallel structure on the input side of the converter not only achieves leg-level hardware redundancy but also reduces the input current ripple. When one branch of the converter suddenly changes or fails, due to the redundancy between branches, the converter can still to work, and the duty cycle of the other branches can be readjusted by using PI control without changing output voltage and power of the converter. This feature undoubtedly presents the reliability of the converter. On the contrary, when the converter works in normal operation, it can also actively control operation mode of each branch to achieve reconfigurable voltage conversion gain function. In addition, since the duty cycles of the switches are not limited, voltage conversion gain of the converter is widely, which makes it more suitable for the occasions where the input side fluctuates greatly. Section 2 details the working principle of the proposed converter and the voltage and current stress on components. Then, the reconfigurable voltage conversion gain of the converter and its high reliability characteristics are analyzed in Section 3. Finally, the correctness of the theoretical analysis is verified by experiments