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Linear minimum mean square error (MMSE) detection achieves a good trade‐off between performance and complexity for massive multiple‐input multiple‐output (MIMO) systems. To avoid the high‐dimensional matrix inversion involved, MMSE detection can be transformed into an unconstrained optimization problem and then solved by efficient numerical algorithms in an iterative way. Three low‐complexity Broyden‐Fletcher‐Goldfarb‐Shanno (BFGS) quasi‐Newton methods are proposed to iteratively realize massive MIMO MMSE detection without matrix inversion. The complexity can be reduced from O(K3)$\mathcal {O}(K^{3})$ to O(LK2)$\mathcal {O}(LK^{2})$, where K and L denote the number of users and iterations, respectively. Leveraging the special properties of massive MIMO, the authors first explore a simplified BFGS method (named S‐BFGS) to alleviate the computational burden in the search direction. For lower complexity, BFGS method with the unit step size (named U‐BFGS) is presented subsequently. When the base station (BS)‐to‐user‐antenna ratio (BUAR) is large enough, the two proposed BFGS methods can be integrated (named U‐S‐BFGS) to further reduce complexity. In addition, an efficient initialization strategy is devised to accelerate convergence. Simulation results verify that the proposed detection scheme can achieve near‐MMSE performance with a small number of iterations L as low as 2 or 3. [ABSTRACT FROM AUTHOR]

Sensitive and accurate detection of multiplex foodborne pathogens is crucial for food safety. In this work, a dual-mode and dual-target biosensor regulated by a Tesla valve was established for simultaneously determining Escherichia coli O157:H7 (E. coli) and Salmonella typhimurium (S. T). Two zeolitic imidazolate framework (ZIF-8) signal probes decorated with electroactive materials (ferrocene or methylene blue), DNAzyme, and different phages were synthesized to specifically recognize the targets and generate fluorescent/electrochemical dual-mode signals. In the presence of bacteria, they were captured and enriched on two individual working electrodes through the modified 4-mercaptophenylboric acid. The encoded signal probes added on different working electrodes could be conjugated with the corresponding target bacteria depending on the specificity of phages. Under the acidic condition, the DNAzyme could catalyze click chemistry for fluorescent signals. Simultaneously, the released ferrocene and methylene blue from ZIF-8 could generate electrochemical signals at different potentials. Benefiting from the flow regulation feature of the Tesla valve, the triggered fluorescent and electrochemical signals in the two individual electrodes would not influence each other, achieving simultaneous dual-mode and dual-target determination of foodborne pathogens. It depicted good linearity ranged 10–107 CFU mL−1. And the corresponding detection of limits were 5 CFU mL−1 and 8 CFU mL−1 for two bacteria, respectively. A low false positive was realized through the dual-mode strategy. The proposed biosensor can not only on-site, specifically, and sensitively determine E. coli and S. T , but also provide the wide prospect in rapid screening of other foodborne pathogens. [Display omitted] • A biosensor with dual-mode and dual-target determination was made. • A double-disk electrode platform with a Tesla valve was developed. • ZIF-8 encoded probes could emit fluorescent and electrochemical signals. • The limits of detection for two targets were 5 CFU mL−1 and 8 CFU mL−1 within 30 min. • The assay could reduce the false positive rates. [ABSTRACT FROM AUTHOR]

In conventional stochastic computation, all the input streams are Bernoulli sequences (BSs), which may result in large random error. To reduce random error and improve computational accuracy, some other sequences have been reported as alternatives to BSs. However, these sequences only apply to the specific stochastic circuits, have difficulties in hardware generation, or have length constraints. To this end, new sequences without these disadvantages should be considered. This paper proposes the random error analysis method for stochastic computation based on autocorrelation sequence (AS), which is more general than the conventional one based on BS. The analysis results show that we can use the proper ASs as input streams of stochastic circuits to reduce random error. On the basis of that conclusion, we propose the random error reduction scheme based on maximal concentrated autocorrelation sequence (MCAS) and BS, both of which are ASs. MCAS and BS are applicable to any combinational stochastic circuit, are easily generated by hardware, and have no length constraints, which avoid the disadvantages of sequences in the previous work. Moreover, we apply the proposed random error reduction scheme into several typical stochastic circuits as case studies. The simulation results confirm the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

To ensure the safety of food, rapid screening and quantitative detection of foodborne pathogens are both significantly required. In this work, a dual-signal response biosensing strategy integrated with the visual fluorescent signal and the quantitative electrochemical signal was developed to simultaneously satisfy these demands. The deoxyribozyme (DNAzyme)-ferrocene immobilized on the MXene/gold nanobipyramid/antimicrobial peptide was employed as the signal probe for dual signal output. In the presence of Vibrio parahaemolyticus (V.P, as the model analyte), the typical immunocomplexes between the signal probe, target, and capture antibody were formed on the sensing electrode. The DNAzyme with excellent catalytic ability allowed the click reaction of 3-azide-7-hydroxycoumarin and 3-butyn-1-ol with the assistance of copper ion (Cu2+) to provide the visual fluorescent signal for rapid screening. Then the ferrocene provided a quantified electrochemical detection signal to further confirm the foodborne pathogen contamination. Notably, the two signals provided a built-in cross-reference correction, which greatly improved the detection accuracy. Under optimum conditions, the proposed biosensing strategy exhibited a wide detectable range of 10–108 CFU·mL−1 and a low detection limit of 6 CFU·mL−1. This dual-signal biosensing strategy provides a useful route to develop simple and novel strategies for the on-site detection of foodborne pathogens. [Display omitted] • A signal probe was designed to provided fluorescent and electrochemical signals. • The gold nanobipyramid-modified MXene was used to carry massive signal tags. • A dual-signal strategy was provided for on-site V.P screening with a LOD of 6 CFU·mL−1. • The dual-signal strategy owned the built-in cross-reference correction. [ABSTRACT FROM AUTHOR]

Aim: To determine the prevalence of dyslipidemia in urban adults in southeast China. Patients & methods: A cross-sectional survey was conducted by using a two-stage probability sampling design according to socioeconomic levels, sex and age in an urban representative sample of 11,877 Chinese adults aged 20-81 years in Shaoxing (Zhejiang, China) between 1998 and 2010. During 2011 and 2012, 11,620 subjects were thoroughly followed up with 93.5% in participation rate versus 99.0% in 2011 and 98.8% in 2012. Results: The observed prevalence of dyslipidemia, according to the recent National Cholesterol Education Programme guidelines, at baseline examination was 27.53% compared with 29.27% in 2011 and 31.35% in 2012 (p < 0.001). Conclusion: The age-adjusted prevalence of dyslipidemia increased with age, with a significance in males. The relative risk of developing dyslipidemia was significantly higher in those who were overweight/obese, had high blood pressure and diabetes mellitus. This suggests that aggressive goals and screening programs for population-based dyslipidemia among middle-age people in southeast China are needed. [ABSTRACT FROM AUTHOR]

It is critically important to develop assays for point-of-care testing (POCT) vibrio in water. In this study, an aptamer-modified electrode was used in conjunction with an antimicrobial peptide-labeled nano metal-organic framework (NMOF) signal tag to screen Vibrio parahaemolyticus (VP) as a model. Firstly, single stranded DNA labeled methylene blue (cDNA-MB) was hybridized with VP aptamer (Apt) on the electrode to form an electroactive DNA probe. Simultaneously, NMOF modified antimicrobial peptide and ferrocene (NMOF@AMP-Fc) was prepared as signal tag. The aptasensor was incubated in VP samples that would compete with aptamer and release the cDNA-MB into the supernatant. Afterwards, the NMOF@AMP-Fc signal tag was conjugated with the captured VP to form a sandwich complex, resulting in the generation of an electrical signal from Fc. The cDNA-MB signal (I MB) decreased and the Fc signal (I Fc) accordingly increased as VP concentration increased. The I Fc /I MB ratio was proportional to the logarithm value of VP concentration, with a lower limit of detection as 4 CFU·mL-1. The whole analysis was completed within 30 min with high sensitivity and specificity, which was due to the dual recognition from antimicrobial peptide and aptamer then the amplification of NMOF. The aptasensor could on-site monitor vibrio contamination in aquaculture water. • A ratiometric electrochemical aptasensor was constructed for on-site detection of vibrio. • Antimicrobial peptide-labeled nano metal-organic framework signal tag was constructed. • The NMOF signal tag could significantly amplify the signal to achieve high sensitivity. • The dual recognition of antimicrobial peptide and aptamer achieved high specificity. • The whole analysis was completed within 30 min with a LOD of 4 CFU·mL-1 VP. [ABSTRACT FROM AUTHOR]

It is critically important to develop assays for point-of-care testing (POCT) vibrio in water. In this study, an aptamer-modified electrode was used in conjunction with an antimicrobial peptide-labeled nano metal-organic framework (NMOF) signal tag to screen Vibrio parahaemolyticus (VP) as a model. Firstly, single stranded DNA labeled methylene blue (cDNA-MB) was hybridized with VP aptamer (Apt) on the electrode to form an electroactive DNA probe. Simultaneously, NMOF modified antimicrobial peptide and ferrocene (NMOF@AMP-Fc) was prepared as signal tag. The aptasensor was incubated in VP samples that would compete with aptamer and release the cDNA-MB into the supernatant. Afterwards, the NMOF@AMP-Fc signal tag was conjugated with the captured VP to form a sandwich complex, resulting in the generation of an electrical signal from Fc. The cDNA-MB signal (I MB) decreased and the Fc signal (I Fc) accordingly increased as VP concentration increased. The I Fc /I MB ratio was proportional to the logarithm value of VP concentration, with a lower limit of detection as 4 CFU·mL-1. The whole analysis was completed within 30 min with high sensitivity and specificity, which was due to the dual recognition from antimicrobial peptide and aptamer then the amplification of NMOF. The aptasensor could on-site monitor vibrio contamination in aquaculture water. • A ratiometric electrochemical aptasensor was constructed for on-site detection of vibrio. • Antimicrobial peptide-labeled nano metal-organic framework signal tag was constructed. • The NMOF signal tag could significantly amplify the signal to achieve high sensitivity. • The dual recognition of antimicrobial peptide and aptamer achieved high specificity. • The whole analysis was completed within 30 min with a LOD of 4 CFU·mL-1 VP. [ABSTRACT FROM AUTHOR]

Abstract: Achieving high speed and reliability is a key challenge in on-chip bus design. To address the challenge, in this paper we propose a fault model for on-chip communication and further develop a new joint scheme which integrates an equalization technique and special spacing rules for improving the speed and communication reliability for on-chip buses. The proposed equalizer employs a variable threshold inverter whose switching threshold is adjusted as a function of the past output of the buses to achieve high-speed and high-reliability of the buses. Special spacing rules use the sufficient spacing between the adjacent wires to mitigate the crosstalk effect from the adjacent wires. The joint scheme equalization and special spacing rules exploits their respective advantages to further improve the speed and communication reliability of the buses. The simulation results show that the joint scheme equalization and increasing spacing of the uncoded bus can reduce 50% delay and save 42% power only with 52% area overhead compared with the minimum-spaced uncoded bus. The bit error rate of the bus can be improved from 10−5 to 10−24. [Copyright &y& Elsevier]

Abstract: Networks on Chip (NoC) and 3-Dimensional Integrated Circuits (3D IC) have been proposed as the solutions to the ever-growing communication problem in System on Chip (SoC). Most of contemporary 3D architectures are based on Mesh topology, which fails to achieve small latency and power consumption due to its inherent large network diameter. Moreover, the conventional XY routing lacks the ability of fault tolerance. In this paper, we propose a new 3D NoC architecture, which adopts De Bruijn graph as the topology in physical horizontal planes by leveraging its advantage of small latency, simple routing, low power, and great scalability. We employ an enhanced pillar structure for vertical interconnection. We design two shifting based routing algorithms to meet separate performance requirements in latency and computing complexity. Also, we use fault tolerant routing to guarantee reliable data transmission. Our simulation results show that the proposed 3D NoC architecture achieves better network performance and power efficiency than 3D Mesh and XNoTs topologies. [Copyright &y& Elsevier]

In this paper, we propose a joint scheme which combines redundant residue number systems (RRNS) with module isolation (MI) for mitigating single event multiple bit upsets (SEMBUs) in datapath. The proposed hardening scheme employs redundant residues to improve the fault tolerance for datapath and module spacings to guarantee that SEMBUs caused by charge sharing do not propagate among the operation channels of different moduli. The features of RRNS, such as independence, parallel and error correction, are exploited to establish the radiation hardening architecture for the datapath in radiation environments. In the proposed scheme, all of the residues can be processed independently, and most of the soft errors in datapath can be corrected with the redundant relationship of the residues at correction module, which is allocated at the end of the datapath. In the back-end implementation, module isolation technique is used to improve the soft error rate performance for RRNS by physically separating the operation channels of different moduli. The case studies show at least an order of magnitude decrease on the soft error rate (SER) as compared to the NonRHBD designs, and demonstrate that \ RRNS+\ MI can reduce the SER from 10^-12 to 10^-17 when the processing steps of datapath are 10^6. The proposed scheme can even achieve less area and latency overheads than that without radiation hardening, since RRNS can reduce the operational complexity in datapath. [ABSTRACT FROM AUTHOR]

We propose an effective scheme based on redundant residue number systems (RRNS) for radiation hardening of datapath in this paper. The proposed hardening scheme employs redundant residues to mitigate soft errors. We use the properties of RRNS, such as independence, parallel and error correction, to establish the radiation hardening architecture for datapath in radiation environments. In the architecture, all of the residues can be processed independently, and most of soft errors in datapath can be corrected with the redundant relationship of the residues at correction module, which is allocated at the end of the architecture. There is not any additional processing in the architecture but correction operation and binary to residue translation. Thus, the proposed scheme has high efficiency when the processing steps of datapath are large. In order to provide protection for the key module in the proposed scheme, correction module, some traditional protection methods, including Guard-gate register triple modular redundancy (G-RTMR), pipeline-level TMR, and module-level TMR, are used to construct the hybrid protection schemes. In the case studies, we find that the RRNS based scheme and the hybrid schemes can reduce soft error rate from 10-12 to 10-17, -18,10-25, and -25-respectively, only with 45.-46.1% area overheads and negligible latency overheads, when the pipeline stages of datapath are 104 and the moduli set with correction capability of one residue is adopted. The case studies also show that the proposed schemes can achieve less area and latency overheads than that of datapath without radiation hardening, because RRNS can reduce the complexity of operations in datapath. [ABSTRACT FROM AUTHOR]

[Display omitted] • A double stirring bars-assisted signal amplification strategy was developed for detecting bacteria. • A branched-chain DNA hybrid structure was immobilized on magnetic microspheres as encoded probes. • Aptamer-embedded tetrahedral DNA nanostructures were modified on one stirring to trigger the target recycling. • The enzyme immobilized on the stirring bar for signal amplification could be reused and lower the usage cost. In this work, we demonstrate a double stirring bars-based signal-amplified strategy for the simultaneous electrochemical detection of Vibrio parahaemolyticus (V.P) and Salmonella typhimurium (S.T). Methylene blue (MB) or ferrocene (Fc) labeled functionalized branched-chain DNA hybrid structure (FBCHS) was immobilized on magnetic microspheres and used as encoded signal tags. The encoded signal tags were hybridized with the aptamer-embedded tetrahedral DNA nanostructures (TDNs), which acted as capture probes, on one gold stirring bar (bar-A). The magnetic signal tags on bar-A could capture V.P and S.T, and their complex was later released into the solution. The composites were then digested by exonuclease I that was modified on another gold stirring bar (bar-B). The released free bacteria participated in the next cycle, from bar-A to bar-B, and generated more magnetic tags for signal amplification. After the reaction, the tags were magnetically enriched on a screen-printed carbon electrode (SPCE), generating two distinct voltametric peaks derived from MB and Fc. Their current intensities could reflect the concentration of V.P and S.T in the samples. Under optimal conditions, the double stirring bars-based signal amplification strategy was able to increase the detection sensitivity with a lower detection limit of 4 and 7 CFU/mL for V.P and S.T, respectively, within a detection range of 10–108 CFU/mL. Importantly, the exonuclease I on the stirring bar (bar-B) for signal amplification was able to be reused up to 50 times and avoided its loss if being directly added in solution, which produced cost savings in terms of used enzymes. [ABSTRACT FROM AUTHOR]

Expectation Propagation (EP)-based Multiple-Input Multiple-Output (MIMO) detector achieves exceptional performance in high-dimensional systems with high-order modulations and flexible antenna configurations. However, based on our studies, the EP MIMO detector cannot achieve superior performance due to the empirical parameter selection, including initial variance and damping factors. According to the influence of the moment matching and parameter selection on the performance of the EP MIMO detector, we propose a modified EP MIMO detector (MEPD). To obtain the initial variance and damping factors which lead to better performance, we adopt a deep learning scheme, the iterative process of MEPD is unfolded to establish MEPNet for parameters training. The simulation results show that MEPD with off-line trained parameters outperforms the original one in various MIMO scenarios. Besides, the proposed MEPD with deep learning parameters selection is more robust than EPD in practical scenarios. [ABSTRACT FROM AUTHOR]

Multiple-input Multiple-output (MIMO) technologies play an important role in modern and future wireless communication systems as they can improve the capacity without increasing the bandwidth. MIMO detection is one of the key technologies for MIMO system designs. MIMO detection schemes based on Message Passing (MP) algorithms have attracted extensive attention in recent years. The MIMO detection scheme based on Expectation Propagation (EP), which is also a kind of MP algorithms, has been proved to achieve the Bayes-optimal performance under the conditions of large system limit and compression rate threshold. However, there is improvement space for the detection performance of the EP algorithm when the conditions are not satisfied, which are the common cases in the practical applications. In this paper, when the conditions of the large system limit and compression rate threshold are not satisfied, we analyze the influences of two factors, the initial parameters selection and the moment matching strategy, on the performance of EP based detection scheme. As a result, we propose an improved EP detection scheme based on optimizing the two factors. Simulation results show that the proposed scheme outperforms the original EP detection scheme in different MIMO scenarios. [ABSTRACT FROM AUTHOR]

The widespread use of chemical herbicides has jeopardized concerns about food safety and ecological consequences. To address these issues and reduce reliance on chemical herbicides, a physical weed control device was developed for the tillering stage in paddy fields. This device features a biomimetic duckbill-like vibration chain that effectively controls weed outbreaks. The chain penetrates the soft surface soil of the paddy field under gravity and rapidly stirs the soil through vibration, leading to the detachment of the weed roots anchored in the surface layer. Simultaneously, the device avoids mechanical damage to rice seedlings rooted in deeper soil. This study aimed to investigate the effects of chain structural parameters (the number of chain rows, vibration amplitude, and length of chains) and operational parameters (vibration frequency and working velocity) on weed control efficiency and rice seedling damage. Through a central composite regression field test, the optimal device structure and operational parameters were determined. The optimization results demonstrated that a vibration amplitude of 78.8 mm, a chain length of 93.47 cm, and 3.4 rows of chains, along with a vibration frequency and working velocity ranging from 0.5 to 1.25 m/s, achieved an optimal weeding effect. Under the optimal parameter combination, field test results demonstrated that approximately 80% of the weeds in the field were effectively cleared. This indicates that the design of the biomimetic duckbill-like vibration chain weeding device exhibits a relatively superior weeding performance, offering a practical solution for the management of weeds in rice fields. [ABSTRACT FROM AUTHOR]

To realize the autonomous operation of a terraced rice sowing robot, a set of sowing robot operation path planning algorithms with universal significance for small, irregular terraced plots is proposed. According to the characteristics of terraces and the agronomic requirements of sowing seeding, the operation path mainly includes parallel operation and boundaries surrounding the operation path. The boundary pre-collision detection method is expounded, and the cyclic detection method judges the U-turn area. The Bézier curve fitting algorithm was used to smooth the boundary wrapping path. To verify the feasibility of the algorithm, four typical irregular small fields located in 666.7-hectare terraces of Sama in Hong He Prefecture, Yunnan Province, were randomly selected, and a field map was obtained through Google Earth. An existing seeding robot was used as a model, and the simulation and comparison tests were carried out with the mainstream EHNS algorithm and boundary polyline algorithm under the ROS-kinetic platform in the Cen Village Scientific Research Base of South China Agricultural University. The actual boundaries of the four fields with the same simulation test were used as the map to verify the field experiment. The simulation test results show that the area coverage of the sowing operation is greater than 93.53% and the replay rate is less than 3.46%, and the field test results show that the area coverage of the sowing operation is greater than 94.33% and the replay rate is less than 3.03%. The simulation test is in good agreement with the field test results, indicating that the algorithm has good adaptability, which meets the requirements of a sowing robot for sowing operation path planning and can provide a certain reference for the path planning of irregular field operation robots in hilly and mountainous areas. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a FPGA implementation architecture for SVM classifier. The architecture is based on the proposed Shared Dot Product Matrix (SDPM) method which computes and stores the dot product of all training data before SVM searching process. We implemented the proposed method by software simulation and hardware implementation. The software simulation of SDPM method achieves twice the speed of LIBSVM, which is one of the most popular SVM implementation libraries. This acceleration mainly results from the reduction of repeat Kernel function calculation. Then the hardware software collaboration architecture for SDPM is also proposed in this paper. Results show that the proposed architecture achieves approximately 30 times faster searching speed compared with LIBSVM. • The contributions of this manuscript are as follows: • We propose a Shared dot product matrix algorithm to reduce the computation complexity of SVM OTPC searching. • Based on the proposed algorithm, we implement it in software and compare the performance with that of LIBSVM. • We also design a hardware software collaboration architecture based on the proposed algorithm to accelerate the searching process. • In our design, the software implementation and LIBSVM is processed by C++. The hardware software collaboration architecture is implemented by FPGA. Test results show that the software implementation can reach 2 times faster than that of LIBSVM. The hardware software collaboration architecture can reach approximately 30 times faster than that of LIBSVM. [ABSTRACT FROM AUTHOR]

Polar codes have received recent attention due to their potential to be applied in advanced wireless communication protocols such as the fifth generation mobile communication system (5G). Among the existing decoding algorithms, Belief Propagation (BP) exhibits high-throughput, low-latency, and soft output with a high hardware cost. Stochastic computing, as a form of approximate computing, provides a potential low-cost implementation solution for the BP algorithm. However, existing stochastic BP decoders suffer from a relatively long decoding latency resulting in low hardware efficiency. In this paper, a novel bit-wise iterative stochastic decoding architecture for the BP algorithm is proposed to improve the throughput and hardware efficiency. By utilizing the frozen bits of polar codes and stochastic computing, multiple novel optimization methods are presented to further speed up convergence and increase the hardware efficiency. [ABSTRACT FROM AUTHOR]