Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

Bias in Generative AI Systems:A 3-Layer Response and Liability Determination

The risk of bias is widely noticed in the entire process of generative artificial intelligence(generative AI)systems.To protect the rights of the public and improve the effectiveness of AI regulations,feasible measures to address the bias problem in the context of large data should be proposed as soon as possible.Since bias originates in every part and various aspects of AI product lifecycles,laws and technical measures should consider each of these layers and take different causes of bias into account,from data training,modeling,and application design.The Interim Measures for the Administration of Generative AI Service(the Interim Measures),formulated by the Office of the Central Cyberspace Affairs Commission(CAC)and other departments have taken the initiatives to govern AI.However,it lacks specific details on issues such as how to prevent the risk of bias and reduce the effect of bias in decision-making.The Interim Measures also fail to take causes of bias into account,and several principles must be further interpreted.Meanwhile,regulations on generative AI at the global level are still in their early stages.By forming a governance framework,this paper could provide the community with useful experiences and play a leading role.The framework includes at least three parts:first,determining the realm of governance and unifying related concepts;second,developing measures for different layers to identify the causes and specific aspects of bias;third,identifying parties with the skills to take responsibility for detecting bias intrusions and proposing a program for the allocation of liabilities among the large-scale platform developers.

Exploring influences and risk of bias of studies on return to sport and work after lateral ankle sprain:A systematic review and metaanalysis

BACKGROUND Lateral ankle sprains are the most common traumatic musculoskeletal injuries of the lower extremity,with an incidence rate of 15%-20%.The high incidence and prevalence highlights the economic impact of this injury.Ankle sprains lead to a high socioeconomic burden due to the combination of the high injury incidence and high medical expenses.Up to 40%of patients who suffer from an ankle sprain develop chronic ankle instability.Chronic instability can lead to prolonged periods of pain,immobility and injury recurrence.Identification of factors that influence return to work(RTW)and return to sports(RTS)after a lateral ankle sprain(LAS)may help seriously reduce healthcare costs.AIM To explore which factors may potentially affect RTW and RTS after sustaining an LAS.METHODS EMBASE and PubMed were systematically searched for relevant studies published until June 2023.Inclusion criteria were as follows:(1)Injury including LAS or chronic ankle instability;(2)Described any form of treatment;(3)Assessment of RTW or RTS;(4)Studies published in English;and(5)Study designs including randomized controlled clinical trials,clinical trials or cohort studies.Exclusion criteria were:(1)Studies involving children(age<16 year);or(2)Patients with concomitant ankle injury besides lateral ankle ligament damage.A quality assessment was performed for each of the included studies using established risk of bias tools.Additionally quality of evidence was assessed using the GRADEpro tool in cases where outcomes were included in the quantitative analysis.A best evidence synthesis was performed in cases of qualitative outcome analysis.For all studied outcomes suitable for quantitative analysis a forest plot was created to calculate the effect on RTW and RTS.RESULTS A total of 8904 patients were included in 21 studies,10 randomized controlled trials,7 retrospective cohort studies and 4 prospective cohort studies.Fifteen studies were eligible for meta-analysis.The overall RTS rate ranged were 80%and 83%in the all treatments pool and surgical treatments pool,respectively.The pooled mean days to RTS ranged from 23-93 d.The overall RTW rate was 89%.The pooled mean time to RTW ranged from 5.8-8.1 d.For patients with chronic ankle instability,higher preoperative motivation was the sole factor significantly and independently(P=0.001)associated with the rate of and time to RTS following ligament repair or reconstruction.Higher body mass index was identified as a significant factor(P=0.04)linked to not resuming sports or returning at a lower level(median 24,range 20-37),compared to those who resumed at the same or higher level(median 23,range 17-38).Patients with a history of psychological illness or brain injury,experienced a delay in their rehabilitation process for sprains with fractures and unspecified sprains.The extent of the delayed rehabilitation was directly proportional to the increased likelihood of experiencing a recurrence of the ankle sprain and the number of ankle-related medical visits.We also observed that 10%of athletes who did return to sport after lateral ankle sprain without fractures described non-ankle-related reasons for not returning.CONCLUSION All treatments yielded comparable results,with each treatment potentially offering unique advantages or benefits.Preoperative motivation may influence rehabilitation after LAS.Grading which factor had a greater impact was not possible due to the lack of comparability among the included patients.

EFFECT OF NEGATIVE BIAS ON DIAMOND NUCLEATION IN MICROWAVE PLASMA ASSISTED CHEMICAL VAPOR DEPOSITION SYSTEM

Effect of direct current negative bias on diamond nucleation in microwave plasma assisted chemical vapor deposition system was discussed. The influence of the magnitude of negative bias value,bias duration and methane concentration in the gas mixture on nucleation density of diamond films was studied respectively. It is demonstrated that direct current negative bias can drastically enhance the diamond nucleation at a suitable value.Long bias duration and high methane concentration are helpful for diamond nucleation.

Stochastic resonance in a bias linear system with multiplicative and additive noise

In this paper, the stochastic resonance in a bias linear system subjected multiplicative and additive dichotomous noise is investigated. Using the linear-response theory and the properties of the dichotomous noise, this paper finds the exact expressions for the first two moments and the signal-to-noise ratio （SNR）. It is shown that the SNR is a non-monotonic function of the correlation time of the multiplicative and additive noise, and it varies non-monotonously with the intensity and asymmetry of the multiplicative noise as well as the external field frequency. Moreover, the SNR depends on the system bias, the intensity of the cross noise between the multiplicative and additive noise, and the strength and asymmetry of the additive noise.

Attributing Analysis on the Model Bias in Surface Temperature in the Climate System Model FGOALS-s2 through a Process-Based Decomposition Method

This study uses the coupled atmosphere–surface climate feedback–response analysis method（CFRAM） to analyze the surface temperature biases in the Flexible Global Ocean–Atmosphere–Land System model, spectral version 2（FGOALS-s2）in January and July. The process-based decomposition of the surface temperature biases, defined as the difference between the model and ERA-Interim during 1979–2005, enables us to attribute the model surface temperature biases to individual radiative processes including ozone, water vapor, cloud, and surface albedo; and non-radiative processes including surface sensible and latent heat fluxes, and dynamic processes at the surface and in the atmosphere. The results show that significant model surface temperature biases are almost globally present, are generally larger over land than over oceans, and are relatively larger in summer than in winter. Relative to the model biases in non-radiative processes, which tend to dominate the surface temperature biases in most parts of the world, biases in radiative processes are much smaller, except in the sub-polar Antarctic region where the cold biases from the much overestimated surface albedo are compensated for by the warm biases from nonradiative processes. The larger biases in non-radiative processes mainly lie in surface heat fluxes and in surface dynamics,which are twice as large in the Southern Hemisphere as in the Northern Hemisphere and always tend to compensate for each other. In particular, the upward/downward heat fluxes are systematically underestimated/overestimated in most parts of the world, and are mainly compensated for by surface dynamic processes including the increased heat storage in deep oceans across the globe.

Bias Momentum Attitude Control System Using Energy/Momentum Wheels

The integrated power and attitude control for a bias momentum attitudecontrol system is investigated. A pair of counter-spinning wheels is used to provide the biasangular momentum and store/ discharge energy for power requirement of the devices on the spacecraft.The roll/yaw motion is controlled by pitch magnetic dipole moment. The torque-based control law ofthe wheels is designed, so that the desired pitch control torque is provided and the operation ofcharging/discharging energy is carried out based on the given power. System singularity in thecontrol law of wheels is fully avoided by keeping the wheels counter-spinning. A power managementscheme using kinetic energy feedback is proposed to keep energy balance, which can avoid wheelsaturation caused by superfluous energy. The minimum moment of inertia of the wheels is limited bythe maximum bias angular momentum and the minimum energy, such constrains are analyzed incombination with the geometrical method. Numerical simulation results are presented to demonstratethe effectiveness of the control scheme.

Indian Ocean SST Biases in a Flexible Regional Ocean Atmosphere Land System(FROALS) Model

The authors examine the Indian Ocean sea surface temperature(SST) biases simulated by a Flexible Regional Ocean Atmosphere Land System(FROALS) model.The regional coupled model exhibits pronounced cold SST biases in a large portion of the Indian Ocean warm pool.Negative biases in the net surface heat fluxes are evident in the model,leading to the cold biases of the SST.Further analysis indicates that the negative biases in the net surface heat fluxes are mainly contributed by the biases of sensible heat and latent heat flux.Near-surface meteorological variables that could contribute to the SST biases are also examined.It is found that the biases of sensible heat and latent heat flux are caused by the colder and dryer near-surface air in the model.

Estimation and Correction of Model Bias in the NASA/GMAO GEOS5 Data Assimilation System:Sequential Implementation

This study presents a simplified multivariate bias correction scheme that is sequentially implemented in the GEOS5 data assimilation system and compared against a control experiment without model bias correction. The results show considerable improvement in terms of the mean biases of rawinsonde observation-minus-background （OmB） residuals for observed water vapor, wind and temperature variables. The time series spectral analysis shows whitening of bias-corrected OmB residuals, and mean biases for rawinsonde observation-minus-analysis （OmA） are also improved. Some wind and temperature biases in the control experiment near the equatorial tropopause nearly vanish from the bias-corrected experiment. Despite the analysis improvement, the bias correction scheme has only a moderate impact on forecast skill. Significant interaction is also found among quality-control, satellite observation bias correction, and background bias correction, and the latter positively impacts satellite bias correction.

Tunable biasing magnetic field design of ferrite tuner for ICRF heating system in EAST

Ion cyclotron range of frequency（ICRF） heating has been used in tokamaks as one of the most successful auxiliary heating tools and has been adopted in the EAST. However, the antenna load will fluctuate with the change of plasma parameters in the ICRF heating process. To ensure the steady operation of the ICRF heating system in the EAST, fast ferrite tuner（FFT） has been carried out to achieve real-time impedance matching. For the requirements of the FFT impedance matching system, the magnet system of the ferrite tuner（FT） was designed by numerical simulations and experimental analysis, where the biasing magnetic circuit and alternating magnetic circuit were the key researched parts of the ferrite magnet. The integral design goal of the FT magnetic circuit is that DC bias magnetic field is 2000 Gs and alternating magnetic field is±400 Gs. In the FTT, E-type magnetic circuit was adopted. Ferrite material is Nd Fe B with a thickness of 30 mm by setting the working point of Nd Fe B, and the ampere turn of excitation coil is 25 through the theoretical calculation and simulation analysis. The coil inductance to generate alternating magnetic field is about 7 m H. Eddy-current effect has been analyzed, while the magnetic field distribution has been measured by a Hall probe in the medium plane of the biasing magnet. Finally, the test results show the good performance of the biasing magnet satisfying the design and operating requirements of the FFT.

Research of Magnetic Bias Control System Based on STATCOM

As the most important style of reactive power compensation system, the research and design control system of static synchronous compensator (STATCOM) is an important aspect of keeping stable and normal operation. This paper analyzes the influences of bias magnetic to STATCOM, and proposes an effective magnetic bias control method and program realization, so reduced to producing two harmonics. It improves the quality and reliability of STATCOM output voltage;Finally, the tests are conducted in the ±500 kVar STATCOM, and the results show the validity and necessity of this compensation method.

Risk of bias and reporting practices in studies comparing VO2max responses to sprint interval vs.continuous training:A systematic review and meta-analysis

Background:It remains unclear whether studies comparing _(max)imal oxygen uptake(VO_(2max))response to sprint interval training(SIT)vs.moderate-intensity continuous training(MICT)are associated with a high risk of bias and poor reporting quality.The purpose of this study was to evaluate the risk of bias and quality of reporting in studies comparing changes in VO_(2max) between SIT and MICT.Methods:We conducted a comprehensive literature search of 4 major databases:AMED,CINAHL,EMBASE,and MEDLINE.Studies were excluded if participants were not healthy adult humans or if training protocols were unsupervised,lasted less than 2 weeks,or utilized mixed exercise modalities.We used the Cochrane Collaboration tool and the CONSORT checklist for non-pharmacological trials to evaluate the risk of bias and reporting quality,respectively.Results:Twenty-eight studies with 30 comparisons(3 studies included 2 SIT groups)were included in our meta-analysis(n=360 SIT participants:body mass index(BMI)=25.9±3.7 kg/m^(2),baseline VO_(2max)=37.9±8.0 mL/kg/min;n=359 MICT participants:BMI=25.5±3.8 kg/m^(2),baseline VO_(2max)=38.3±8.0 mL/kg/min;all mean±SD).All studies had an unclear risk of bias and poor reporting quality.Conclusion:Although we observed a lack of superiority between SIT and MICT for improving VO_(2max)(weighted Hedge’s g=0.004,95%con-fidence interval(95%CI):-0.08 to 0.07),the overall unclear risk of bias calls the validity of this conclusion into question.Future studies using robust study designs are needed to interrogate the possibility that SIT and MICT result in similar changes in VO_(2max).

Impacts of Systematic Precipitation Bias on Simulations of Water and Energy Balances in Northwest America

At high latitudes and in mountainous areas, evaluation and validation of water and energy flux simu-lations are greatly affected by systematic precipitation errors. These errors mainly come from topographic effects and undercatch of precipitation gauges. In this study, the Land Dynamics （LAD） land surface model is used to investigate impacts of systematic precipitation bias from topography and wind-blowing on water and energy flux simulation in Northwest America. The results show that topographic and wind adjustment reduced bias of streamflow simulations when compared with observed streamflow at 14 basins. These systematic biases resulted in a -50%-100% bias for runoff simulations, a -20%-20% bias for evapotranspiration, and a -40%-40% bias for sensible heat flux, subject to different locations and adjustments, when compared with the control run. Uncertain gauge adjustment leads to a 25% uncertainty for precipitation, a 20% 100% uncertainty for runoff simulation, a less-than-10% uncertainty for evapotranspiration, and a less-than-20% uncertainty for sensible heat flux.

Long-term and short-term stability characteristics of receiver inter system bias for BDS3/BDS2

The study of inter-system bias(ISB)is important for multi-system fusion and the performance of different signal compatibility.In this paper,the stability of ISB at the BDS3/BDS2 receiver end is calculated and analyzed for different time spans(DOY 060~090 in 2021)from a total of 31 MGEX and iGMAS stations.We adopted two estimation strategies,random walk and constant approach,using the precision products of orbit and clock bias provided by WUM,the influence of which on ISB was also analyzed.Our results showed that the ISB value varied little within a day,and the mean of daily ISB standard deviation was only 0.037 m when the observation condition was good.The signal reception was continuous,indicating a high ISB stability for one day.If extending the time series to one month,however,the ISB standard deviation calculated by constant approach,in which a constant ISB is estimated on a daily basis was about 0.1 m,and the results of adjacent days were not continuous,with no apparent pattern.Concerning the random walk approach,the obtained ISB time series also had a jump,and the conclusion was the same as that of the constant strategy.Besides,receiver types showed a strong regularity in ISB numerical situation,and the distribution of ISB values corresponding to the same receiver type was relatively close.Therefore,we conclude that the ISB parameters remain stable in the short term(one day)and less stable in the long-term period.It is recommended that the ISB term should be set as a constant estimate every day in BDS3/BDS2 solutions,regardless of receiver type consistency.

Numerical study of the radio-frequency biased accelerating system in ion thrusters

A 2D-3V implicit immersed-finite-element particle-in-cell(IFE-PIC)model is introduced to investigate the radio-frequency(RF)self-bias accelerating system applied in the RF ion thruster.A set of holes in a two-grid system with slit apertures is simulated in Cartesian coordinates.The characteristics of the plasma plume,such as the ion density,the neutralization rate and the ion and electron current density were investigated for different RF voltage amplitudes(600-1200V)and frequencies(6-30 MHz).Furthermore,the performance of the thruster was also carefully studied.The simulation results show that a well-focused plasma beam can be formed when the voltage amplitude is larger than 900 V and the frequency exceeds the reciprocal of ion transit time(≥12 MHz)in our simulation cases.The performance of the system can be evidently improved by increasing the voltage amplitude and the frequency,and the losses of the particle and thrust are reduced correspondingly.The bulk region of the plasma beam downstream shows good quasi-neutrality,and the ions are dominant in the peripheral region when a well-focused state is achieved.The high ion density beamlet in the periphery of the ion beam is closer to the axis when the voltage amplitude is increasing,while it is expanded radially when increasing the frequency.Backstream electrons have been observed upstream,and this mainly occurs in the phase in which the electron cannot escape.

BIASED BEARINGS-ONLY PARAMETER ESTIMATION FOR BISTATIC SYSTEM

According to the biased angles provided by the bistatic sensors, the necessary condition of observability and Cramer-Rao low bounds for the bistatic system are derived and analyzed, respectively. Additionally, a dual Kalman filter method is presented with the purpose of eliminating the effect of biased angles on the state variable estimation. Finally, Monte-Carlo simulations are conducted in the observable scenario. Simulation results show that the proposed theory holds true, and the dual Kalman filter method can estimate state variable and biased angles simultaneously. Furthermore, the estimated results can achieve their Cramer-Rao tow bounds.

The Application of a Meteo-hydrological Forecasting System with Rainfall Bias Correction in a Small and Medium-sized Catchment

Meteo-hydrological forecasting models are an effective way to generate high-resolution gridded rainfall data for water source research and flood forecast.The quality of rainfall data in terms of both intensity and distribution is very important for establishing a reliable meteo-hydrological forecasting model.To improve the accuracy of rainfall data,the successive correction method is introduced to correct the bias of rainfall,and a meteo-hydrological forecasting model based on WRF and WRF-Hydro is applied for streamflow forecast over the Zhanghe River catchment in China.The performance of WRF rainfall is compared with the China Meteorological Administration Multi-source Precipitation Analysis System(CMPAS),and the simulated streamflow from the model is further studied.It shows that the corrected WRF rainfall is more similar to the CMPAS in both temporal and spatial distribution than the original WRF rainfall.By contrast,the statistical metrics of the corrected WRF rainfall are better.When the corrected WRF rainfall is used to drive the WRF-Hydro model,the simulated streamflow of most events is significantly improved in both hydrographs and volume than that of using the original WRF rainfall.Among the studied events,the largest improvement of the NSE is from-0.68 to 0.67.It proves that correcting the bias of WRF rainfall with the successive correction method can greatly improve the performance of streamflow forecast.In general,the WRF/WRF-Hydro meteo-hydrological forecasting model based on the successive correction method has the potential to provide better streamflow forecast in the Zhanghe River catchment.

Modeling and Prediction of Inter-System Bias for GPS/BDS-2/BDS-3 Combined Precision Point Positioning

The combination of Precision Point Positioning(PPP)with Multi-Global Navigation Satellite System(MultiGNSS),called MGPPP,can improve the positioning precision and shorten the convergence time more effectively than the combination of PPP with only the BeiDou Navigation Satellite System(BDS).However,the Inter-System Bias(ISB)measurement of Multi-GNSS,including the time system offset,the coordinate system difference,and the inter-system hardware delay bias,must be considered for Multi-GNSS data fusion processing.The detected ISB can be well modeled and predicted by using a quadratic model(QM),an autoregressive integrated moving average model(ARIMA),as well as the sliding window strategy(SW).In this study,the experimental results indicate that there is no apparent difference in the ISB between BDS-2 and BDS-3 observations if B1I/B3I signals are used.However,an obvious difference in ISB can be found between BDS-2 and BDS-3 observations if B1I/B3I and B1C/B2a signals are used.Meanwhile,the precision of the Predicted ISB(PISB)on the next day of all stations is about 0.1−0.6 ns.Besides,to effectively utilize the PISB,a new strategy for predicting the PISB for MGPPP is proposed.In the proposed strategy,the PISB is used by adding two virtual observation equations,and an adaptive factor is adopted to balance the contribution of the Observed ISB(OISB)and the PISB to the final estimations of ISB.To validate the effectiveness of the proposed method,some experimental schemes are designed and tested under different satellite availability conditions.The results indicate that in open sky environment,the selective utilization of the PISB achieves almost the same positioning precision of MGPPP as the direct utilization of the PISB,but the convergence time of MGPPP is reduced by 7.1%at most in the north(N),east(E),and up(U)components.In the blocked sky environment,the selective utilization of the PISB contributes to more significant improvement of the positioning precision and convergence time than that in the open sky environment.Compared with the direct utilization of the PISB,the selective utilization of the PISB improves the positioning precision and convergence time by 6.7%and 12.7%at most in the N,E,and U components,respectively.

Systematic Approaches of UWB Low-Power CMOS LNA with Body Biased Technique

This paper presents research on a low power CMOS UWB LNA based on a cascoded common source and current-reused topology. A systematic approach for the design procedure from narrow band to UWB is developed and discussed in detail. The power reduction can be achieved by using body biased technique and current-reused topology. The optimum width of the major transistor device M1 is determined by the power-constraint noise optimization with inner parasitic capacitance between the gate and source terminal. The derivation of the signal amplification S21 by high frequency small signal model is displayed in the paper. The optimum design of the complete circuit was studied in a step by step analysis. The measurements results show that the proposed circuit has superior S11, gain, noise figure, and power consumption. From the measured results, S11 is lower than -12 dB, S22 is lower than -10 dB and forward gain S21 has an average value with 12 dB. The noise figure is from 4 to 5.7 dB within the whole band. The total power consumption of the proposed circuit including the output buffer is 4.6 mW with a supply voltage of 1 V. This work is implemented in a standard TSMC 0.18 μm CMOS process technology.

Assessment of the Southern Ocean Sea Surface Temperature Biases in CMIP5 and CMIP6 Models

This work evaluates the performances of climate models in simulating the Southern Ocean(SO)sea surface temperature(SST)by a large ensemble from phases 5 and 6 of the Coupled Model Intercomparison Project(CMIP5 and CMIP6).By combining models from the same community sharing highly similar SO SST biases and eliminating the effect of global-mean biases on local SST biases,the results reveal that the ensemble-mean SO SST bias at 70°-30°S decreases from 0.38℃ in CMIP5 to 0.28℃ in CMIP6,together with increased intermodel consistency.The dominant mode of the intermodel variations in the zonal-mean SST biases is characterized as a meridional uniform warm bias pattern,explaining 79.1% of the intermodel variance and exhibiting positive principal values for most models.The ocean mixed layer heat budget further demonstrates that the SST biases at 70°-50°S primarily result from the excessive summertime heating effect from surface net heat flux.The biases in surface net heat flux south of 50°S are largely impacted by surface shortwave radiation from cloud and clear sky components at different latitudes.North of 50°S,the underestimated westerlies reduce the northward Ekman transport and hence northward cold advection in models,leading to warm SST biases year-round.In addition,the westerly biases are primarily traced back to the atmosphere-alone model simulations forced by the observed SST and sea ice.These results disclose the thermal origin at the high latitude and dynamical origin at the low latitude of the SO SST biases and underscore the significance of the deficiencies of atmospheric models in producing the SO SST biases.