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This paper discusses the problem of fault estimation for two-dimensional (2-D) Fornasini-Marchesini (FM) dynamical systems. The objective of this paper is to design a fault estimation filter to reconstruct the characteristics of faults in low-frequency domain and satisfy different performance levels. Utilizing the generalized Kalman-Yakubovich-Popov (GKYP) lemma, this problem is transformed into a multi-objective optimization problem, which is non-convex in essence. On this basis, an optimization algorithm is proposed to solve the non-convex optimization problem. Sufficient conditions are derived for the proposed fault estimation filter. Finally, simulation results show the effectiveness of the theoretical results.

At present, the digital meter recognition is widely used in the field of power transmission and transformation, but rarely used in the petrochemical industry. This paper combines traditional image processing techniques with deep learning methods and proposes a meter recognition method based on an improved neural network model. By establishing a neural network model architecture, setting up the three convolutional layers and adding a batch normalization processing operation, the digital meters of the oil extraction platform are recognized, and the recognition rate is about 99.17%, which achieve the expectations. Through comparative research, the model constructed in this paper has a higher recognition accuracy and reflects a better recognition effect.

With the acceleration of aging in society, elderly care institutions have become more important in urban planning and public service facilities than before. Geographic Information System(GIS), the kernel density analysis method, and the hot spot analysis method were used to analyze the points of interest(POI) data of elderly care institutions in Baiyun District, Guangzhou in 2021. The spatial distribution and agglomeration characteristics of elderly care institutions were explored in the research area. The result provided a comprehensive spatial evaluation of the elderly care institutions and showed the following: (1) The elderly care institutions in Baiyun District exhibit the characteristics of continuous clustering and spatial distribution in multiple centers and (2) Baiyun District has the characteristics of the concentrated distribution of significant hotspots, larger clustered block types appear, and the agglomeration characteristics are obvious. The research results are used as a reference for the government to plan public service facilities for the elderly.

Over the last years, the food delivery market has seen significant growth and provide a lot of jobs for deliverymen. The revenue of a takeaway deliveryman depends on not only reasonable order taking but also efficient delivery path planning. However, it is challenging to select among a large number of candidate orders and plan an efficient route passing all involved pickup points and service points. In this paper, we present a problem integrating order selection and delivery path optimization for takeaway deliverymen. The objective is to maximize the revenue per unit time subject to overtime penalty and high-workload reward. To efficiently solve this problem, we propose a hybrid intelligent algorithm, which adapts the water wave optimization (WWO) metaheuristic to evolve solutions to the main order selection problem and employs tabu search to optimize the path for each order selection solution. Experimental results on test instances demonstrate the performance advantages of the proposed algorithm compared to a set of popular metaheuristic optimization algorithms.

In this paper, we highlight the advances in chip-scale technologies in the terahertz spectrum between 100 GHz and 10 THz, particularly focusing on silicon-based integrated chip technology that can have a transformative impact in wireless communication, sensing and imaging.

In this study, the influences of Ag and Zn contents on the interfacial microstructure and corrosion behavior of Sn–Zn–Ag/6061Al joints aiming at 4G/5G antenna module packages were investigated using scanning electron microscopy (SEM) and potentiodynamic polarization measurement, respectively. Results show that Al-rich phase detaches from 6061Al substrate and forms Al–Zn–Sn solid solution in the solder matrix; meanwhile a continuous Ag–Zn intermetallic compound (IMC) layer forms near the interface when adding Ag to the solder, resulting in the roughness interface between the solder and 6061Al. In Sn–Zn–Ag/6061Al joints, 6061Al substrate acts as an anode and corrodes preferentially. Intergranular corrosion occurs in 6061Al and the crack initiates at the edges of joints. Simultaneously, the aggressive Cl– penetrates into the crack, which accelerates the corrosion, and the crack propagates rapidly along the interface, resulting in the failure of solder joints. Among the solders with different Ag and Zn contents in this study, Sn–6Zn–1.5Ag/6061Al joints exhibit superior corrosion resistance.

Cu nanoparticles (NPs) with two different size distributions were synthesized by a chemical reduction method, which are polydispersed Cu NPs with size in the range of 10 nm to 100 nm and bimodal-sized Cu NPs with large irregular-shaped particles (125 nm) surrounded by small NPs (9 nm). Cu pastes prepared by mixing the Cu NPs with the solvent were used to bond dummy die (i.e., copper plate with silver coating) and bare copper substrate. The results demonstrate that the bimodal-sized Cu NP based paste performs better than the other one in mechanical property of joints. Besides, the shear strength of joints fabricated by such paste can reach 52.6 MPa after pressureless sintering at 280 °C for 10 min in the atmosphere of nitrogen. The copper paste capable of pressureless sintering and making joints with high strength is a promising material for die attachment of IGBT.

In this study, the bimodal sized core–shell structured Cu–Ag nanoparticles (Cu@Ag NPs) of 20 and 110 nm were prepared using lactic acid as stabilizer. The Cu oxides were removed during the formation process of Ag shell. The obtained Cu and Cu@Ag NPs exhibit good oxidation resistance at temperatures below 150 and 200 °C, respectively. A conductive ink with a metal loading of about 50 wt.% was formulated for screen printing by mixing synthesized Cu@Ag NPs, ethyl cellulose and terpineol. The bimodal Cu@Ag NPs based ink shows low resistivity of 4×10-6 and 8.5×10-7 Ω•m after sintering at 120 and 200 °C, respectively, for 30 min in the atmosphere of nitrogen. In addition, a possible mechanism has been proposed to illustrate the sintering process of Cu@Ag NPs.

Data clustering is a well-known data analysis methodology in the optimization community that can be formulated as a Np-hard problem. The main concept of the clustering procedure is to identify and assign data objects into sensible disjointed groups based on similarity measures, such as the Euclidean distance. In this case, data objects within a group are similar to each other with regard to the similarity measure, and each group is dissimilar to each other. Fuzzy clustering is also a popular and powerful research method with many applications, such as medical imaging processing with real words. In the fuzzy clustering research field, the fuzzy c-means (FCM) algorithm is one of the most important fuzzy clustering approaches for efficient and easy implementation; however, the FCM algorithm has a weakness in which it can easily become trapped in local optima. Thus, some metaheuristic algorithms, such as genetic algorithm (GA) and particle swarm optimization (PSO), can be combined with FCM to solve the clustering problem. Recently, a novel metaheuristic algorithm inspired by the social behavior of humpback whales, called the whale optimization algorithm (WOA), has been proposed. In addition, the WOA has obtained more efficient solutions than some popular metaheuristic algorithms, such as the gene GA and PSO. In this paper, a fuzzy clustering algorithm that called the memetic fuzzy whale optimization (MFWO) algorithm, is proposed to solve the data clustering problem. The performance of the proposed algorithm is evaluated using eight real-world UCI benchmarks, and the FCM and fuzzy PSO algorithms are compared. The experimental results show that the proposed MFWO algorithm is more efficient than the compared algorithms.

Millimeter-wave based wireless communication and sensing systems for future 5G applications are expected to operate in a complex electromagnetic environment with dynamically changing near-field conditions. This is particularly true for user equipment where presence of near-field blockages and scatterers can significantly affect the front-end antenna and therefore the system performance. Classical beamforming architectures that rely on identical patterns on all elements can be extremely energy inefficient in such cases. Element-level pattern shaping that can dynamically reconfigure the properties of a single antenna can not only allow mitigation of such complex electromagnetic environment, but incorporate system properties that are distinct from classical arrays. In this work, we present a multi-port on-chip dual polarized antenna and a multi-port receiver co-design approach that allows dynamic pattern reconfiguration and element notch control that can reject interferers directly at the antenna surface before beamforming. We demonstrate this in state of the art receiver performance in a 65-nm CMOS process at 70 GHz with element maxima and notch tuning capability of more than 90° while allowing high sensitivity and minimizing impedance mismatches and power losses.

Data clustering is a well-known data mining approach that usually used to minimizes the intra distance but maximizes inter distance of each data center. The cluster problem has been proved to be an NP-hard problem. In this paper, a hybrid algorithm based on Whole optimization algorithm (WOA) and Crow search algorithm (CSA) is proposed, namely HWCA. The HWCA algorithm has the advantages of the search strategy of the WOA and CSA. In addition to, there are two operators used to improve the quality of solution, namely hybrid individual operator and enhance diversity operator. The hybrid individual operator is used to exchanges individuals from the WOA and CSA systems by using the roulette wheel approach. In other hand, the HWCA performs enhance diversity operator to improve the quality of each system. More over, the HWCA is incorporated with center optimization strategy to enhance diversity of each system. In the performance evaluation, the proposed MPGO algorithm was comparison WOA and CSA algorithm with six well-known UCI benchmarks. The results show that the proposed algorithm has a higher measure of accuracy rate with comparison algorithms.

In this paper, an edge enhanced super-resolution network (EESR) is proposed for a better generation of high-frequency structures in blind super resolution. In EESR, an edge detection network is used to extract high-frequency pixels. A generative adversarial network (GAN) is used to fine-tune the EESR network. And a more applicative criterion "perceptive texture score" (PTS) is defined and used to evaluate the quality of generated high-resolution image. Experiments show that the new EESR is able to recover textures with 4 times up-sampling, and gained PTS of 0.6210 on DIV2K test set, which is much better than the state-of-the-art methods.

The adoption and sustained use of self-tracking devices, including wearable and assistive technologies, are critical for the development of smart health systems. However, individual users' psychological, aesthetic and social preferences are often overlooked when designing devices and systems. By expanding and applying Moller & Kettleys' maker–wearer–viewer model more generally to smart health systems, this paper proposes co-creating design processes that not only focus on the role of people (makers, wearers, and viewers) but also allow for the creative meaning-making and caring processes among them. The paper also illustrates the ways in which co-created avatars have advantages over the pre-designed dashboards in presenting the well-being status of an individual. In contrast to the technology-centered clinical approach, a people-centered everyday life approach must be incorporated in the designed process. The implications of such design processes for the Internet of People were summarized, including the three principles of people-centered design that take the everyday life approach for designing and studying smart health, which contrasts with medicalized and clinical approach. The paper concludes with the reasons why such a people-centered everyday life approach can complement the current clinical approach in weaving the web of caring (self-care and care for others) by turning both subjective data and creative efforts into meaningful presentation of individual well-being that ultimately should lead to more adoption and sustained use of smart health systems.

The advent of the digital era has promoted the integration of information technology and classroom teaching, and the Internet and social media have been more and more applied to college classes. In the favor of social media, the concept like equality in class is constantly being shouted out, advocating the equality of teachers and students in the classroom, the equality of discourse power and the equality of the atmosphere in the classroom. Started with the application status of social media in the classroom teaching in Colleges and universities, based on the results of the current situation survey, this paper reflects the "three equals" of college classroom teaching, namely, the equality of body, the equality of language and the equality of meaning, and reconstructs the present college class based on the "three equals", thus making the "equality" truly realized in the class of universities.

Silicon-based integrated circuit technology provides a great platform for enabling compact, efficient, low-power, chip-scale THz systems for new applications in sensing, imaging and communication While this is partially facilitated by scaling that has pushed device cut-off frequencies ($f _{t},\,f_{max}$) up into the sub-THz and THz frequency range, the true paradigm shift in silicon integration is that it provides a unique opportunity to enable a new field of active THz electromagnetics realizable through a circuits-EM-systems co-design approach. At these frequencies, the chip dimension is several times larger than the THz wavelengths which allows novel scattering and radiating properties in a substrate that simultaneously supports a billion high-frequency transistors that can generate, process and sense these signals. The ability to actively synthesize, manipulate and sense THz EM fields at subwavelength scales with circuits opens up a new design space for THz electronics. THz architectures emerging from this space are often multi-functional, reconfigurable and break many of the classical trade-offs of a partitioned design approach. This paper provides examples to illustrate this design methodology on THz signal generation with beam-forming and spectrum control and THz spectrum sensing.

In this paper, we present a method to miniaturize THz spectroscopic receivers into chip-scale systems by eliminating traditional spectrum analysis components such as wideband tunable THz sources, frequency multipliers, nonlinear mixing and amplifiers. This is achieved by extracting incident THz spectral signatures from the current distribution impressed on the surface of an on-chip antenna under the THz field incidence. A log-periodic tooth antenna is converted from a classical single port antenna into a massively multi-port structure with 84 detectors that sense the 2D current distribution. This method converts THz spectroscopy into a linear estimation problem and we apply robust estimation techniques such as LASSO, typically used in machine learning, to extract spectral signatures with noisy detectors with high sensitivity. The paper presents analytical and experimental results for the single chip operating at room temperature across 0.04-0.99 THz with 10 MHz accuracy in spectrum estimation of THz tones. The presented examples demonstrates that through a co-design approach of THz electromagnetics and electronics, such as by combining deep sub-wavelength near-field sensing and regression analyses, can enable a new class of THz chip-scale sensory systems.

An integrated THz imager is proposed with an actively reconfigurable electromagnetic interface that can engineer the surface reception properties to reconfigure its sensitivity and aperture for three incident field properties, namely frequency, polarization and incident angle. The chip realized in a 65 nm CMOS process achieves upto 15x enhancement in responsivity and NEP across 0.1-0.99 THz and enables a programmable and versatile THz interface for hyperspectral, multi-angle and multi-polarization imaging.

We present the dose-rate effect and emitter size effect of DPSA bipolar transistors under gamma ray irradiation. Results indicated there have an ELDRS effect exist and the effects are discussed from the perspective of degradation rate.

Poly and metal field-plate structures were designed in lateral-PNP bipolar junction transistors which fabricated on standard linear bipolar technology for validating their TID hardened effectiveness. 60Co γ irradiation experiment was executed on these samples and experimental results were compared. Results showed that metal field-plate was better than poly field-plate.

Significant objects can be obtained from the gray or color images via image segmentation by referring to the clustering problem. Inspired by the search strategy of GSA and the rapid convergence of PSO, this study proposes a memetic particle gravitation optimization (MPGO) algorithm, which is a hybrid approach for performing image segmentation. The proposed MPGO algorithm is verified using six well-known images, including Lena, Baboon, F16, Goldhill, Pepper, and Sailboat. MPGO significantly outperforms k-means, PSO and GSA in measures of the PSNR values.

An optimal adaptive actuator failure compensation control scheme is proposed for a class of multi-input multi-output (MIMO) uncertain nonlinear continuous-time systems with redundant actuators subject to uncertain failures. Only single neural network is used in the proposed adaptive dynamic programming (ADP) scheme to simultaneously learn the infinite horizon cost function and the approximate optimal control input that minimizes the Hamilton-Jacobi-Bellman (HJB) equation. Besides, an uncertainty estimator is designed to estimate the uncertain dynamics and an adaptive parameter adjustment law is designed to estimate the actuator failure coefficients. Stability analysis and simulation results can demonstrate the effectiveness of the proposed method.

An investigation of radiated reliability of HBT and MOSFET which fabricated on 0.35 μm SiGe BiCMOS technology is presented under dose rates of 500 mGy(Si)/s and 1 mGy(Si)/s with a 60Co γ irradiation source. Gummel characteristics of SiGe HBT and transfer characteristics of MOSFET are measured before and after irradiation. Base current (IB), leakage current (IOFF) and threshold voltage (VTH) are extracted from gummel and transfer characteristics. Our results show that there is a slight increase in IB and an observed decrease in β for SiGe HBT device. For NMOS transistor, a conspicuous increase in IOFF and slight drift in vt H . No dose-rate effect has been seen in SiGe HBT devices; however, it has been observed in NMOS transistors.

Spectrally-efficient operation with high power and high efficiency at deep back-off will be critical for the next-generation mm-Wave transmitters for 5G and beyond. In addition, as larger non-contiguous chunks of the mm-Wave spectrum open up, dynamic frequency reconfiguration while ensuring high spectral and energy efficiency can become key towards optimal utilization of spectral resources. In this paper, we present a generalized asymmetrical multi-port combiner based network synthesis approach that enables both frequency and back-off reconfigurability in a mm-Wave power amplifier (PA) architecture to maintain high-efficiency operation with spectrally efficient codes across a wide frequency range. As a proof of concept, a silicon-based PA is presented which operates between 30–55 GHz with peak P sat of 23.7 dBm at 40 GHz and output collector efficiency (η out ) of 34.5 % and 22% at the 0 and −6 dB back-off respectively. The PA maintains η out > 16% at −6 dB back-off across the range. Non-constant modulation is demonstrated with pulse shaping and with data rates upto 4 Gbps across the frequencies from 30–50 GHz.

Slurm is a widely used resource management software for Linux cluster. It has several CPU selection plugins with different allocation strategies suitable for different scenarios. But the GPU allocation is constrained by the selected CPU's location because GPUs can only be accessed by the process running on the same node. This restriction may cause job waiting for GPUs even if there are some free GPUs in the cluster. This paper presents a global GPU management plugin for Slurm. The plugin using remote GPU virtualization method detaches the GPUs to form a global GPU pool and decouples the GPU allocation procedure from the CPU's. GPUs in the pool are available to CUDA jobs on any node in the cluster. Furthermore, we implement two GPU selection strategy, best fit and local first. Experiments show the global GPU management plugin shorter the job's waiting time and makes efficient use of GPUs in the cluster.

An optimal adaptive compensation control scheme is proposed for a class of multi-input multi-output (MIMO) affine nonlinear systems with actuator failures. Considering stuck actuators and partial effectiveness failures, an adaptive dynamic programming method is adopted by using neural network to approximate the cost function. It adjust the weights of the neural network by using an online adaptive algorithm. An adaptive parameter adjustment law is designed to estimate the actuator failure coefficients. The proposed optimal adaptive compensation law can guarantee that the closed-loop system with actuator failures is stable and that the given reference signals are effectively tracked. Simulation results demonstrate the effectiveness of the proposed method.

This paper related the irradiation reliability properties exhibited by double polysilicon self aligned (DPSA) bipolar junction transistors (BJTs). Gummel curses, leakage current of junction and breakdown voltage were measured before and after 60Co γ irradiation for two bias modes. We found that the devices are susceptible to 60Co γ irradiation, especially the parameters of base current and C-B junction leakage current. We also found that the devices biased on reverse mode were more susceptible than biased on forward mode.

The Epidemic Simulation System (EpiSimS) is a scalable, complex modeling tool for analyzing disease within the United States. Due to its high input dimensionality, time requirements, and resource constraints, simulating over the entire parameter space is unfeasible. One solution is to take a granular sampling of the input space and use simpler predictive models (emulators) in between. The quality of the implemented emulator depends on many factors: robustness, sophistication, configuration, and suitability to the input data. Visual analytics can be leveraged to provide guidance and understanding of these things to the user. In this paper, we have implemented a novel interface and workflow for emulator building and use. We introduce a workflow to build emulators, make predictions, and then analyze the results. Our prediction process first predicts temporal time series, and uses these to derive predicted spatial densities. Integrated into the EpiSimS framework, we target users who are non-experts at statistical modeling. This approach allows for a high level of analysis into the state of the built emulators and their resultant predictions. We present our workflow, models, the associated system, and evaluate the overall utility with feedback from EpiSimS scientists.

In this paper, a scalable architecture is presented which can generate and radiate reconfigurable periodic waveforms in free-space with picosecond time-widths. This is achieved by allowing radiated electromagnetic-fields of fundamental and multiple harmonic frequencies to combine in free-space with the right amplitudes and delays, and quasi-optically construct the time-domain waveform in the desired direction. In this paper, a 4-element array with integrated antennas is presented which is demonstrated to radiate pulse trains of 2.6 ps time-widths as well as pure tones and harmonic frequencies at 107.5 GHz (EIRP=4.5 dBm), 215 GHz (EIRP=5.0 dBm) and any combination of amplitudes and delays of these two harmonics to generate a set of reconfigurable waveforms in free space. No silicon lens or substrate thinning was employed. To the best of the authors' knowledge, this is the sharpest radiated pulses demonstrated in any IC technology. The chip is fabricated in 65nm LP CMOS process.

In this paper, a scalable and reconfigurable architecture is presented for digitally programmable sub-THz waveform generation in CMOS. The architecture allows individual control of both amplitudes and phases of harmonic frequencies beyond f max to achieve waveform shaping. This is enabled through controlled interference of multiple traveling-waves with rich harmonic components and delays. As an example, inspired from mode-locked laser, picosecond pulse generation is demonstrated in CMOS with a measured pulse-width of 2.6ps and 0.46 mW output power for the pulse train. To the best of the authors' knowledge, this is the smallest pulse width demonstrated in integrated circuit technology with additional capability of dynamic reconfiguration. The chip is fabricated in 65nm LP CMOS process.

Safety requirements have commanded increasing attention as software is playing a more and more important role in today's safety critical systems. As many experts, scholars have found that the main reason for safety critical systems' accident is bad requirements which means inaccurate, incomplete or inconsistent requirements may lead to misunderstanding of the system and may cause a fault in software design and realization, and brought disaster to people or environment. The main reason of bad requirements is poor communication between safety engineers and requirements analysis engineers. Safety requirements essentially are requirements to protect the software system go into a danger state which will cause lost of life or asset or environment damage. Safety requirements deal with errors, faults that the system may come across. So In this paper, we combine fault protection concepts with safety requirements, and propose a model-based safety requirements modeling approach named Safety RUCM to describe safety requirements in order to reduce inaccurate, incomplete or inconsistent safety requirements and at the same time to enhance mutual understanding on safety requirements between safety.

This study examines the relationship between perceived voice and turnover intention. The proposed hypotheses are tested with a sample of 274 employees in Mainland China. The results show that perceived voice is negatively related to turnover intention. And as independent negative predictors of turnover intention, both affective organizational commitment and affective commitment to immediate supervisor mediate the relationship between perceived voice and turnover intention. Another finding is that benevolent leadership, an important leadership, not only moderates the relations between perceived voice and affective organizational commitment, also predicts affective commitment to supervisor. The results also shed light on the controversial relations between affective commitment to supervisor and turnover intention. Theoretical and practical implications are discussed.

Theil index has been widely used in inequality measure for its systematic and homogeneous. This paper establishes the knowledge stock index system to calculate the knowledge stock, considering the specific economic background with fewer indexes reflecting the stock accurately and scientifically, then evaluates the knowledge stock gap based on the Theil index. The empirical analysis of 31 Chinese provinces in 2011 shows that there are differences among different regions, the evaluation of knowledge stock gap of Beijing, Jiangsu and Guangdong are significantly higher than the whole country's average level. Besides, the reasons are analyzed in detail.

Modern information technologies continue to provide manufacturing industry with new and improved methods. Reverse supply chain (RSC) management, which is oriented towards the entire lifecycle of products, has been concerned with the emerging of green manufacturing. With the rapid development of IoT, a smart reverse supply chain (SRSC) will be formed based on RFID, sensors, high performance computing, intelligent technologies and nanotechnologies. The SRSC system will help manufacturing process reduce energy consumption, enable resources to be recycled and create an environmentally friendly mode of green manufacturing. This paper focuses on the studies of SRSC network topology and the integrated architecture. Furthermore, some related key technologies are discussed.

COD, TN and TP removal efficiency was studied in different C / N in the system by changing the dosage of CH 3 COONa. The best results obtained by experiment is that when the C / N is between 4 and 6. The average COD effluent concentration is 40.08mg / L, the removal rate is 87.5%;the average TN effluent concentration is 9.32 mg / L, the removal rate is 83.91%; the TP average effluent concentration is 1.02 mg / L, the removal rate is 88.1%. Too high or too low C / N is not conducive to removal rate of system.

The paper analyzed a two-stage choice pattern of transport mode under the circumstance that a new urban railway is going to be introduced to local transportation system. The supporting RP and SP data were obtained from a questionnaire of Suzhou railway. The paper accounted for bias nature of SP data and put forward a false data eliminating method. Then, from data digging in the survey, three interactive functional modules are built to estimate the share rate of transport modes not only in a macro scale but could it forecast the transferring rate. Finally, data aggregating technology is introduced which is proved to do macro-scale forecasting.

The experiment dealt with the best anaerobic, anoxic running time with using denitrification and phosphorus removal technology in SBR, at the same time, under the optimal anaerobic/anoxic time combination, the effect of the system on removal of contaminant was also investigated. The results showed that the best anaerobic, anoxic running time was 90min and 180min. The system optimal sludge age was 22d.

Phosphate accumulating organisms (PAO) is the most common sludge in sewage treatment, This paper examines the effect of carbon source, temperature, PH on PAO, providing references and basis for training.

This experiment was investigated and compared the effects of NO 3 −-N and NO 2 −-N on the anaerobic phosphorus release and anoxic phosphorus uptake of Denitrifying Phosphate Removal Bacteria(DPB).The results showed: with the concentration of NO 3 −-N and NO 2 −-N increased in the Anaerobic stage, the amount of phosphorus release decreased. In the Anoxic phase, When the concentration of NO 3 −-N is 40mg / L removal of NO 3 −-N and phosphorus worked best, the removal rate respectively reached to 98.4% and 97.2%; The DPB had not been Acclimated by NO 2 −-N could still use NO 2 −-N as the electron acceptor, when NO 2 −-N is 20mg / L, phosphorus concentration of effluent was 14.42 mg / L, Removal rate was 59.13%, the phenomenon of Denitrifying Phosphorus can still happen when the concentration of NO 2 −-N ≤ 30mg / L, anoxic phosphate uptake were severely inhibited until the concentration of NO 2 −-N reached 40mg/L, the removal rate of NO 2 −-N was only 32.25% in 4 hours.