Global Loop Research Articles

A switched‐capacitor‐assisted wireless power transfer system with regulating TX power and fast global loop

Wireless power transfer systems demand a regulating transmitter (TX) for global loop control and also a regulating receiver (RX) for its local loop. This design broadens the TX output power range, by merging a switched capacitor (SC) circuit with only 3 switches and 1 flying capacitor to boost the output power of the Class-D power amplifier. In addition, the transmitting power can be regulated by the duty ratio of the SC, improving the end-to-end power transfer efficiency under different load conditions. Moreover, the system obtains fast load transient response, with the help of a light-to-heavy load transient enhancement scheme in the TX and the hysteretic control in the RX. Designed in a 0.18-μm BCD process, this work achieves 3.1 W maximum RX output power, 67.6% peak total efficiency, and 50 μs response time during the light-to-heavy load transient simulation.

A factor graph optimization mapping based on normaldistributions transform

This paper aims to achieve highly accurate mapping results and real time pose estimation of autonomous vehicle by using the normal distribution transform (NDT) algoritm. A factor graph optimization algorithm (FGO-NDT) is proposed to address the poor real-time performance and pose drift errors of the NDT algorithm. Smooth point cloud data are obtained by multisensor calibration and data preprocessing. NDT registration is then used for lidar odometry and feature matching. The global navigation satellite system (GNSS) data and loop detection results are added to the factor graph framework as the pose constraint factors to optimize the pose trajectory and eliminate the pose drift error generated during mapping. In addition, a sliding window method is used for map registration to extract a local map to shorten the map loading time. Thus, the real-time performance of creating point cloud maps of large scenes is significantly improved. Several experiments are conducted in different environments to verify the accuracy and performance of the FGO-NDT. The experimental results demonstrate that the proposed method can eliminate the pose estimation error caused by drift, improve the local structure, and reduce and root mean square error.

The Aromatic Character of Diindeno[2,1-b:2',1'-h]biphenylene.

The tropicity of the title system was studied using NICS(1.7)π,zz-XY-scans and current density analysis, showing a global diatropic loop and local dia- and paratropic loops. This aromaticity picture is very different from the one proposed based on NICS(1) and HOMA ( Org. Lett. 2021, 23, 8794-8798). It is predicted that 1 should be suitable for singlet fission applications. It is concluded that local aromatic indices should not be used for the full analysis of multiring conjugated systems.

Simulating the network structures in the Circular Economy and their impact on resilience

Today need for replacing linear-oriented production systems with circular-oriented ones is urgent. Circular Economy production networks promote the continuous reuse of resources and products, recapturing value from by-products and end-of-life resources, and minimising resource leakage out of the systems. However, the design and management of CE production networks, although representing an important issue worldwide, has been scarcely investigated so far. In this study, we argue that CE networks should be resilient to better face with frequent and unpredictable disruptions and that structural characteristics may influence it. Through a simulation model, we investigate how the node degree connectivity, by affecting the formation of local and global loop structures, influences the network resilience to different types of disrupting events. Results of simulation suggest that in absence of disruptions, a random -like network is characterized by the highest number of long and short cycles. Instead, in presence of disruptions, our results suggest that short cycles are more robust when node degree connectivity is uniformly distributed as occurring in random and small-world -like structures. On the contrary, long cycles result more robust when node degree connectivity is power-law shaped as occurring on scale-free -like structures. Theoretical and managerial implications are discussed.

A Novel Energy-Safe Algorithm for Enhancing the Battery Life for IoT Sensors’ Applications

Energy safe is mandatory for all isolated IoT tools, such as in long way roads, mountains, or even in smart cities. If increasing the lifetime of these tools, the rentability of the global network loop becomes more efficient. Therefore, this paper presents a new approach for saving energy inside the source nodes by supervising the state of energy inside each source node and calculating the duty cycle factor. The relationship between these parameters is based on an optimization problem formulation. In this respect, the present paper is designed to propose a new approach that deals with increasing the lifetime of the wireless sensor network (WSN)-attached nodes, as fixed in the application. The newly devised design is based on implementing the IEEE 802.15.4 standard beacon-enabled mode, involving a cluster tree topology. Accordingly, every subgroup is allotted to apply a specifically different duty cycle, depending on the battery’s remaining energy level, which contributes to creating a wide range of functional modes. Hence, various thresholds are defined. Simulation results prove the efficiency of the proposed approach and show the energetic benefit. The proposed flowchart has minimized the consumed energy for the WSN, which improves the battery lifetime and enhances the IoT application’s robustness. Simulations and experiments have been carried out under different conditions and the results prove that the proposed method is a viable solution.

DV-LOAM: Direct Visual LiDAR Odometry and Mapping

Self-driving cars have experienced rapid development in the past few years, and Simultaneous Localization and Mapping (SLAM) is considered to be their basic capabilities. In this article, we propose a direct vision LiDAR fusion SLAM framework that consists of three modules. Firstly, a two-staged direct visual odometry module, which consists of a frame-to-frame tracking step, and an improved sliding window based thinning step, is proposed to estimate the accurate pose of the camera while maintaining efficiency. Secondly, every time a keyframe is generated, a dynamic objects considered LiDAR mapping module is utilized to refine the pose of the keyframe to obtain higher positioning accuracy and better robustness. Finally, a Parallel Global and Local Search Loop Closure Detection (PGLS-LCD) module that combines visual Bag of Words (BoW) and LiDAR-Iris feature is applied for place recognition to correct the accumulated drift and maintain a globally consistent map. We conducted a large number of experiments on the public dataset and our mobile robot dataset to verify the effectiveness of each module in our framework. Experimental results show that the proposed algorithm achieves more accurate pose estimation than the state-of-the-art methods.

Predictions of Chemical Shifts for Reactive Intermediates in CO2 Reduction under Operando Conditions.

The electroreduction of CO2 into value-added products is a significant step toward closing the global carbon loop, but its performance remains far from meeting the requirement of any practical application. The insufficient understanding of the reaction mechanism is one of the major causes that impede future development. Although several possible reaction pathways have been proposed, significant debates exist due to the lack of experimental support. In this work, we provide opportunities for experiments to validate the reaction mechanism by providing predictions of the core-level shifts (CLS) of reactive intermediates, which can be verified by the X-ray photoelectron spectroscopy (XPS) data in the experiment. We first validated our methods from benchmark calculations of cases with reliable experiments, from which we reach consistent predictions with experimental results. Then, we conduct theoretical calculations under conditions close to the operando experimental ones and predict the C 1s CLS of 20 reactive intermediates in the CO2 reduction reaction (CO2RR) to CH4 and C2H4 on a Cu(100) catalyst by carefully including solvation effects and applied voltage (U). The results presented in this work should be guidelines for future experiments to verify and interpret the reaction mechanism of CO2RR.

Fully automated multidisciplinary design optimization of a variable speed turbine

The future electricity market will have large contributions from renewable energy sources such as solar and wind. The intermittent nature of these energy sources creates a need for highly flexible operation of hydropower stations and changes the way we use hydraulic turbines to more off-design operation and more start-stop cycles. These changes challenge the structural integrity of the turbines in a way not seen before, and the next generation of hydro turbines will therefore have to be designed differently to meet this challenge. The goal of this article is to develop a framework for variable-speed Francis turbine design.A fully automated multi-disciplinary design optimization procedure has been developed. As off-design operation is assumed, the runner do not only have to be optimized from a hydraulic point of view, the structural integrity is equally important. The design optimization is therefore based on a blending function of the hydraulic efficiency and the harmonic stress levels at a series of operating conditions. This is to ensure that the turbine is less prone to fatigue, even at off-design operation.The process is fully automated, with no need for human interaction. A MATLAB design code is producing the raw design, every design is then meshed and tested at different operating points in a CFD solver. The pressure field from the fluid analysis is mapped onto the structure and evaluated in an acoustic-harmonic analysis to assess the fluctuating stresses in the turbine blades. A global optimization loop consisting of 15 design parameters is driving the process based on an overall optimization function.The work has been performed as part of the HydroFlex project, and has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 764011.

Demonstration of High-Speed Data Replication Relay Across Multiple Repository Sites Using a Global Loop Path

Demonstration of High-Speed Data Replication Relay Across Multiple Repository Sites Using a Global Loop Path

The cyber-production mechanization control

This article pays your attention to the cyber-production mechanized equipment control problem. There is a scheme proposed of automatic cyber-production segment control, mechanized technological aggregates and multi-chain manipulation systems. The control system is made in a multi-loop mode with a sensor measuring part to correct production automatics functionality errors. Within the technological aggregates there is a physical processes regulation loop in the machine working volume and one for the assembly units being manufactured material tide. There is a control loop in the manipulation system to move the rail chassis base movement and positioning loop of force and momentum regulation with a multi-chain grip. To control the cyber-production segment mechanization they propose a global loop to engage in the company virtual environment the equipment reference models and digital model (twin) of the product being manufactured.

The Pandemic Crisis Shows that the World Remains Trapped in a 'Global Doom Loop' of Financial Instability, Rising Debt Levels, and Escalating Bailouts

In January 2020, I completed a book (Taming the Megabanks: Why We Need a New Glass-Steagall Act) analyzing the financial crises that precipitated the Great Depression of the 1930s and the recent Great Recession. My book argued that the world’s financial system was caught in a “global doom loop” at the beginning of 2020. Bailouts and economic stimulus programs during and after the global financial crisis of 2007-09 (GFC) imposed heavy debt burdens on most governments, and leading central banks were carrying bloated balance sheets. The rescues arranged by governments and central banks during the GFC created a widely-shared expectation that they would continue to intervene to ensure the stability of major financial institutions and important financial markets. That expectation encouraged speculative risk-taking by financial institutions and investors as well as dangerous growth in private and public debts. I warned that the global doom loop was planting the seeds for the “next” financial crisis, which could overwhelm the already strained resources of governments and central banks.The “next” global crisis began only two months later, in March 2020. The rapid spread of the Covid-19 pandemic caused governments in most developed countries to shut down large sectors of their economies and impose social distancing mandates. Many thousands of businesses closed, setting off a downward spiral in economic activity that paralyzed global financial markets. Investors, businesses, and financial institutions “scrambled for cash” and engaged in panicked “fire sales” of financial assets. Governments and central banks in the U.S. and other advanced economies adopted fiscal stimulus measures and financial rescue programs with a size, speed, and scope that far surpassed the emergency actions taken during the GFC.The pandemic financial crisis and the extraordinary responses of governments and central banks demonstrate that policymakers have not addressed the root causes of the GFC. Major financial institutions and financial markets remain highly unstable. They continue to underwrite rapidly rising levels of private and public debts based on their shared expectation of future government bailouts. Governments and central banks have expanded their “safety nets” far beyond banks and now protect the entire financial system, including short-term wholesale credit markets, systemically important nonbanks, and the corporate bond market. As a practical matter, governments and central banks have “bankified” the financial system, thereby undermining market discipline, stimulating dangerous asset bubbles, and increasing social inequality.Our financial system must be reformed so that it no longer promotes unsustainable booms, fueled by reckless growth in private debts, followed by destructive busts that require massive bailouts and huge increases in government debts. My recent book provides a blueprint for needed reforms, including a new Glass-Steagall Act. A new Glass-Steagall Act would break up financial giants by separating banks from the capital markets and by prohibiting nonbanks from financing their operations with functional substitutes for bank deposits. A new Glass-Steagall Act would establish a financial system that is more stable, more competitive, and more responsive to the needs of consumers, communities, and business firms. Properly implemented, a new Glass-Steagall Act would provide the most direct and practical way to break the global doom loop and end the toxic boom-and-bust cycles of the past quarter century.

Hardware-in-the-Loop Methods for Stability Analysis of Multiple Parallel Inverters in Three-Phase AC Systems

Modern electric distribution systems typically contain several feedback-controlled parallel inverters that together form a complex power distribution system. Consequently, a number of issues related to stability arise due to interactions among multiple inverter subsystems. Recent studies have presented methods where the stability and other dynamic characteristics of a paralleled inverter system can be effectively analyzed using impedance measurements. This article presents implementation techniques for comprehensive online stability analysis of grid-connected paralleled inverters using power hardware-in-the-loop measurements based on an OPAL-RT real-time simulator. The analysis is based on simultaneous online measurements of current control loop gains of the inverters and the grid impedance, and aggregated terminal admittance measurements of the inverters. The analysis includes the measurement of the inverters’ aggregated output impedance, inverters’ loop gains, global minor loop gain, and grid impedance. The presented methods make it possible to rapidly evaluate the system on both global and local levels in real time, thereby providing means for online stability monitoring or adaptive control of such systems. Experimental measurements are shown from a high-power energy distribution system recently developed at DNV GL, Arnhem, The Netherlands.

An Adaptive Clock Scheme Exploiting Instruction-Based Dynamic Timing Slack for a GPGPU Architecture

This article presents an adaptive clock scheme to exploit instruction-based dynamic timing slack (DTS) for a general-purpose graphics processor unit (GPGPU) architecture. Based on the developed transitional static timing analysis, the deterministic DTS can be identified for each instruction at different pipeline stages. A critical path (CP) messenger scheme was designed to monitor the runtime utilization of CPs. Both real-time issued instruction information and CP messengers are utilized to determine the runtime DTS margin and guide the cycle-by-cycle clock period adjustment. To apply the proposed adaptive clock on GPGPU, a hierarchical clocking scheme is built including a global phase-locked loop (PLL) and local delay-locked loop (DLL)-based clock generator inside each compute unit (CU). Each CU core contains its own clock domain with adjustable local clocking. In addition, to exploit error-resilient characteristics of the neural network, an elastic pipeline clocking scheme is developed to redistribute the timing margin across pipeline stages for machine learning computations. Measurement results from the implemented open-source GPGPU architecture on a 65 nm CMOS process demonstrate up to 18% performance improvement or equivalent 30% energy saving can be obtained by exploiting the deterministic instruction-based DTS. The proposed elastic pipeline clocking can gain an additional 8% energy saving with small accuracy degradation for neural network inference operations.

CKF-Based Visual Inertial Odometry for Long-Term Trajectory Operations

The estimation error accumulation in the conventional visual inertial odometry (VIO) generally forbids accurate long-term operations. Some advanced techniques such as global pose graph optimization and loop closure demand relatively high computation and processing time to execute the optimization procedure for the entire trajectory and may not be feasible to be implemented in a low-cost robotic platform. In an attempt to allow the VIO to operate for a longer duration without either using or generating a map, this paper develops iterated cubature Kalman filter for VIO application that performs multiple corrections on a single measurement to optimize the current filter state and covariance during the measurement update. The optimization process is terminated using the maximum likelihood estimate based criteria. For comparison, this paper also develops a second solution to integrate VIO estimation with ranging measurements. The wireless communications between the vehicle and multiple beacons produce the ranging measurements and help to bound the accumulative errors. Experiments utilize publicly available dataset for validation, and a rigorous comparison between the two solutions is presented to determine the application scenario of each solution.

Lidar-based system for high-precision localization and real-time 3D map construction

Simultaneous localization and mapping (SLAM) is considered as the core of building high-precision three-dimensional environmental maps. For this, we proposed a high-precision laser-based SLAM system. Aiming at the problem that the point cloud data obtained from laser is not representative and the iterative closest point method for calculating pose transformation is time-consuming, we proposed an efficient and stable matching algorithm. It uses fused feature points to align with the occupancy grid submaps with less registration error and is less time-consuming. Then, to address the problem in which the registration result falls into the local optimum early, we proposed a quadratic registration algorithm. This method effectively improves the initial value of the registration process. Finally, a time consistency and global consistency loop detection algorithm are used to reduce the cumulative error. The system we proposed has been tested on the University of Michigan North Campus Long-Term dataset and Cartographer dataset. Experiments show that our system has good accuracy under low-speed motion conditions (speeds ranging from 1 to 2 m / s).

Respiratory Muscle Fatigue Alters Cycling Performance and Locomotor Muscle Fatigue.

This study aimed to determine if preexisting respiratory muscle fatigue (RMF) alters motoneuronal output, locomotor muscle fatigue, and cycling performance. Eight trained male cyclists performed 5-km cycling time trials after a resistive breathing task that induced RMF and under control conditions (CON). Motoneuronal output was estimated using vastus lateralis surface electromyography, and locomotor muscle fatigue was quantified as the change in potentiated quadriceps twitch force from preexercise to postexercise. Time to complete the time trial was 1.9% ± 0.9% longer in RMF compared with CON (P < 0.001). Estimated motoneuronal output was lower in RMF compared with CON during 1 km (45% ± 11% vs 53% ± 13%, P = 0.004) and 2 km (45% ± 14% vs 51% ± 14%, P = 0.008), but was not different thereafter. Ventilation was lower in RMF compared with CON during 1 km (114 ± 19 vs 135 ± 24 L·min, P = 0.003) and 2 km (136 ± 23 vs 152 ± 31 L·min, P = 0.009); however, ratings of dyspnea were similar. After the 5-km time trial, locomotor muscle fatigue was attenuated in RMF compared with CON (-22% ± 6%, vs -28% ± 7%, P = 0.02). Alterations to dyspnea for a given ventilation seem to have constrained power output during cycling exercise, thereby limiting the development of locomotor muscle fatigue. These findings indicate that the respiratory system is an integral component in a global feedback loop that regulates exercise performance and the development of locomotor muscle fatigue.

A Novel Loop Closure Detection Approach Using Simplified Structure for Low-Cost LiDAR.

Reducing the cumulative error is a crucial task in simultaneous localization and mapping (SLAM). Usually, Loop Closure Detection (LCD) is exploited to accomplish this work for SLAM and robot navigation. With a fast and accurate loop detection, it can significantly improve global localization stability and reduce mapping errors. However, the LCD task based on point cloud still has some problems, such as over-reliance on high-resolution sensors, and poor detection efficiency and accuracy. Therefore, in this paper, we propose a novel and fast global LCD method using a low-cost 16 beam Lidar based on “Simplified Structure”. Firstly, we extract the “Simplified Structure” from the indoor point cloud, classify them into two levels, and manage the “Simplified Structure” hierarchically according to its structure salience. The “Simplified Structure” has simple feature geometry and can be exploited to capture the indoor stable structures. Secondly, we analyze the point cloud registration suitability with a pre-match, and present a hierarchical matching strategy with multiple geometric constraints in Euclidean Space to match two scans. Finally, we construct a multi-state loop evaluation model for a multi-level structure to determine whether the two candidate scans are a loop. In fact, our method also provides a transformation for point cloud registration with “Simplified Structure” when a loop is detected successfully. Experiments are carried out on three types of indoor environment. A 16 beam Lidar is used to collect data. The experimental results demonstrate that our method can detect global loop closures efficiently and accurately. The average global LCD precision, accuracy and negative are approximately 0.90, 0.96, and 0.97, respectively.

CGLFold: a contact-assisted de novo protein structure prediction using global exploration and loop perturbation sampling algorithm.

Regions that connect secondary structure elements in a protein are known as loops, whose slight change will produce dramatic effect on the entire topology. This study investigates whether the accuracy of protein structure prediction can be improved using a loop-specific sampling strategy. A novel de novo protein structure prediction method that combines global exploration and loop perturbation is proposed in this study. In the global exploration phase, the fragment recombination and assembly are used to explore the massive conformational space and generate native-like topology. In the loop perturbation phase, a loop-specific local perturbation model is designed to improve the accuracy of the conformation and is solved by differential evolution algorithm. These two phases enable a cooperation between global exploration and local exploitation. The filtered contact information is used to construct the conformation selection model for guiding the sampling. The proposed CGLFold is tested on 145 benchmark proteins, 14 free modeling (FM) targets of CASP13 and 29 FM targets of CASP12. The experimental results show that the loop-specific local perturbation can increase the structure diversity and success rate of conformational update and gradually improve conformation accuracy. CGLFold obtains template modeling score ≥ 0.5 models on 95 standard test proteins, 7 FM targets of CASP13 and 9 FM targets of CASP12. The source code and executable versions are freely available at https://github.com/iobio-zjut/CGLFold. Supplementary data are available at Bioinformatics online.

A 2.5–28 Gb/s Multi-Standard Transmitter With Two-Step Time-Multiplexing Driver

This brief presents a 2.5 – 28 Gb/s multi-standard transmitter with a two-step time-multiplexing driver. The proposed two-step time-multiplexing driver not only lowers the output parasitic capacitances but also mitigates charge injection by reducing the number of stacks compared with a 4-to-1 time-multiplexing driver. In addition, the proposed transmitter can enhance the bandwidth by avoiding the use of a 1-unit-interval (1-UI) pulse which is one of the main design challenges in high-speed transmitters. It also provides a controllable output swing and a 3-tap feed-forward equalization (FFE) by turning-on and –off the driver slices. The output impedance is calibrated by a background feedback loop, resulting in a good signal integrity. The prototype chip fabricated in a 65-nm CMOS technology consists of a four-channel transmitter and a global all-digital phase-locked loop (ADPLL). One channel of the transmitter with the ADPLL occupies an active area of 0.23 mm2 and consume 213 mW at 28 Gb/s.

P1486Semi-automated volume-strain loops: a new tool in TTE to assess diastolic dysfunction

Abstract Aim This work aims to evaluate a novel semi-automatic tool for the assessment of volume-strain loops by transthoracic echocardiography (TTE). The proposed method was evaluated on a typical model of left ventricular (LV) diastolic dysfunction: the cardiac amyloidosis. Method 18 patients with proved cardiac amyloidosis were compared to 19 controls, from a local database. All TTE were performed using Vivid E9 or E95 ultrasound system. The complete method includes several steps: 1) extraction of LV strain full traces from apical 4 and 2 cavities views, 2) estimation of LV volume from these two traces by spline interpolations, 3) resampling of LV strain curves, determined for the same cardiac beat, (in apical 4-, 2- and 3- cavities views) as a function of pre-defined percentage increments of LV-volume and 4) calculation of the LV volume-strain loop area. (Figure 1, panel B) Results (Table 1): LVEF was similar between both groups whereas global longitudinal strain was significantly lower in amyloidosis group (−14.4 vs −20.5%; p&lt;0.001). Amyloidosis group had a worse diastolic function with a greater left atrial volume index (51 vs 22ml/m2), a faster tricuspid regurgitation (2.7 vs 2.0 m/s), a greater E/e' ratio (17.3 vs 5.9) with a p&lt;0.001 for all these indices. Simultaneously, the global area of volume-strain loop was significantly lower in amyloidosis group (36.5 vs 120.0%.mL). This area was better correlated with mean e' with r=0.734 (p&lt;0.001) than all other indices (Figure 1, panel A). Table 1 Amyloidosis (N=18) Controls (N=19) p Global strain-volume loop area (%.mL) 36.5±21.3 120.0±54.2 &lt;0.001 Global longitudinal strain (%) −14.4±3.8 −20.5±1.8 &lt;0.001 Left ventricular ejection fraction (%) 62±7 65±5 0.08 Left atrial volume index (ml/m2) 51±22 22±5 &lt;0.001 E/A 1.72±0.97 2.07±0.45 0.17 Mean e' 5.5±1.3 14.4±2.8 &lt;0.001 Mean E/e' 17.3±5.4 5.9±1.4 &lt;0.001 Tricuspid regurgitation velocity (m/s) 2.7±3.8 2.0±0.3 &lt;0.001 Figure 1 Conclusion LV volume-strain loop area appears a very promising new tool to assess semi-automatically diastolic function. Future applications will concern the integration of LV volume-strain loop area as novel feature in machine-learning approach.