STD Values Research Articles

Somatosensory temporal discrimination analysis reveals impaired processing in amyotrophic lateral sclerosis.

While amyotrophic lateral sclerosis (ALS) is primarily characterized as a motor system disorder, there is a growing body of evidence indicating sensory involvement. This study aimed to examine the hypothesis that somatosensory processing is impaired in ALS. Study participants were ALS patients followed at the Neuromuscular Outpatient Unit, as well as healthy volunteers, from March 2021 to July 2023. The Medical Research Council (MRC) sum score was calculated for nine muscle groups bilaterally. The clinical status of patients was evaluated with the ALS Functional Rating Scale-Revised (ALSFRS-R) and the Penn Upper Motor Neuron core. Somatosensory temporal discrimination thresholds (STDTs) were recorded on the medial and lateral parts of both hands. Somatosensory cortex excitability was investigated with the paired somatosensory evoked potentials (SEP) paradigm in a subgroup. Increased STD values were detected in ALS patients compared to controls in both medial (107.66 ± 35 ms vs. 82.7 ± 32.5 ms, p = .001) and lateral (106.5 ± 34.5 ms vs. 82.9 ± 31.3 ms, p = .002) hands. There were no significant differences in STDTs among ALS patients across four regions (medial and lateral parts of the right and left hands). Amplitude ratios obtained from the paired-pulse SEP paradigm were approximately 1 for all interstimulus intervals (ISIs). STDTs did not show any correlations with motor findings or scales. Somatosensory processing appears to be compromised among ALS patients. The lack of correlation between impaired STDT and motor findings implies that it is a purely sensory deficit in ALS.

Comparison of temperature, pressure and specific humidity derived from Sentinel-6 with ERA5 and radiosonde

The temperature, pressure and specific humidity data of Sentinel-6 (S6) products are compared with the ECMWF Reanalysis v5 (ERA5) and radio sounding in 2022. The overall STD of temperature, pressure and specific humidity for S6-ERA5 and S6-Radiosonde are 0.74 ℃, 0.45 hPa, 0.3 g/kg, 1.33 ℃, 0.51 hPa, 0.34 g/kg respectively. The study found that the consistency of these three atmospheric parameters between S6 and ERA5 is better than that between S6 and radiosonde. In the aspect of temporal characteristics, the specific humidity STD of S6-ERA5 decrease successively in summer, autumn, spring and winter. In the aspect of spatial characteristics, S6 has better retrieval ability of temperature values in the troposphere, but the maximum negative bias value of temperature between S6 and ERA5 is −1.57 ℃ at 41.7 km. The pressure bias values of S6 and ERA5 fluctuate greatly below the troposphere. In addition, the STD values of S6-ERA5 and S6-Radiosonde specific humidity data both show the decreasing characteristics in sequence from low to high latitudes.

PENGARUH TELEREHABILITASI SELF CARE OREM TERHADAP MOBILISASI PASIEN PASCA STROKE

Post-stroke patients need to receive telerehabilitation to increase mobility, telerehabilitation approaches Orem's Self Care Theory to increase mobility so that recurrent strokes will be greatly minimized. The research method for this research is Quasi Experimental with a pre-post test design approach and purposive sampling technique. The population is post-stroke patients in the Neurology Polyclinic and Orchid Room at RSUD Dr. R Koesma Tuban numbered 50 patients. 25 people in the control group were given education and 25 people in the intervention group were given a rehabilitation video. The chi square test and normality test were carried out and data analysis used the Mann Whitney test. Mobilization during the pre test with the average score in the control group was 23.72 and the intervention group was 27.28. The Std value. Deviation 10.016 with p value = 0.381. Mobilization during the post test with the average score in the control group was 31.8 and the intervention group was 19.2. The Std value. Deviation 16.427 with p value = 0.002. Based on the results of this study, it was found that there was a significant increase in mobilization scores after being given telerehabilitation in the intervention group. Keywords: Mobilization; Orem's Self Care; Telerehabilitation

Influence of Inter-System Biases on Combined Single-Frequency BDS-2 and BDS-3 Pseudorange Positioning of Different Types of Receivers

The BeiDou Navigation Satellite System (BDS) has developed rapidly, and the combination of BDS Phase II (BDS-2) and BDS Phase III (BDS-3) has attracted wide attention. It is found that there are code ISBs between BDS-2 and BDS-3, which may have a certain impact on the BDS-2 and BDS-3 combined positioning. This paper focuses on the performance of BDS-2/BDS-3 combined B1I single-frequency pseudorange positioning and investigates the positioning performance with and without code ISBs correction for different types of receivers, include geodetic GNSS receivers and low-cost receivers. The results show the following: (1) For geodetic GNSS receivers, the code ISBs of each receiver is about −0.3 m to −0.8 m, and the position deviation is reduced by 7% after correcting code ISBs. The code ISBs in the baseline with homogeneous receivers has a little influence on the positioning result, which can be ignored. The code ISBs in the baseline with heterogeneous receivers is about −0.5 m, and the position deviation is reduced by 4% after correcting code ISBs. (2) The code ISBs in the low-cost receivers are significantly larger than those in the geodetic GNSS receivers, and the impact on the positioning performance of the low-cost receivers is significantly greater than that on the geodetic GNSS receivers. After correcting the code ISBs, the position deviation of low-cost receivers can be reduced by around 12% for both undifferenced and differenced modes. (3) For low-cost receivers, correcting the code ISBs can increase the number of epochs successfully solved, which effectively improves the low-cost navigation and positioning performance. (4) The carrier-phase-smoothing method can effectively reduce the distribution dispersion of code ISBs and make the estimation of ISBs more accurate. The STD values of estimated code ISBs in geodetic GNSS receivers are reduced by about 40% after carrier-phase smoothing, while the corresponding values are reduced by about 7% in low-cost receivers due to their poor carrier-phase observation quality.

Evaluation of Interfacial Structure of Self-Assembled Nanoparticle Layers: Use of Standard Deviation between Calculated and Experimental Drop Profiles as a Novel Method.

The self-assembly of nanoparticles (NPs) at interfaces is currently a topic of increasing interest due to numerous applications in food technology, pharmaceuticals, cosmetology, and oil recovery. It is possible to create tunable interfacial structures with desired characteristics using tailored nanoparticles that can be precisely controlled with respect to shape, size, and surface chemistry. To address these functionalities, it is essential to develop techniques to study the properties of the underlying structure. In this work, we propose an experimental approach utilizing the standard deviation of drop profiles calculated by the Laplace equation from experimental drop profiles (STD), as an alternative to the Langmuir trough or precise microscopic methods, to detect the initiation of closely packed conditions and the collapse of the adsorbed layers of CTAB-nanosilica complexes. The experiments consist of dynamic surface/interfacial tension measurements using drop profile analysis tensiometry (PAT) and large-amplitude drop surface area compression/expansion cycles. The results demonstrate significant changes in STD values at the onset of the closely packed state of nanoparticle-surfactant complexes and the monolayer collapse. The STD trend was explained in detail and shown to be a powerful tool for analyzing the adsorption and interfacial structuring of nanoparticles. Different collapse mechanisms were reported for NP monolayers at the liquid/liquid and air/liquid interfaces. We show that the interfacial tension (IFT) is solely dependent on the extent of interfacial coverage by nanoparticles, while the surfactants regulate only the hydrophobicity of the self-assembled complexes. Also, the irreversible adsorption of nanoparticles and the increasing number of adsorbed complexes after the collapse were observed by performing consecutive drop surface compression/expansion cycles. In addition to a qualitative characterization of adsorption layers, the potential of a quantitative calculation of the parameter STD such as the number of adsorbed nanoparticles at the interface and the distance between them at different states of the interfacial layer was discussed.

D2D Communication Using Distributive Deep Learning with Coot Bird Optimization Algorithm

D2D (Device-to-device) communication has a major role in communication technology with resource and power allocation being a major attribute of the network. The existing method for D2D communication has several problems like slow convergence, low accuracy, etc. To overcome these, a D2D communication using distributed deep learning with a coot bird optimization algorithm has been proposed. In this work, D2D communication is combined with the Coot Bird Optimization algorithm to enhance the performance of distributed deep learning. Reducing the interference of eNB with the use of deep learning can achieve near-optimal throughput. Distributed deep learning trains the devices as a group and it works independently to reduce the training time of the devices. This model confirms the independent resource allocation with optimized power value and the least Bit Error Rate for D2D communication while sustaining the quality of services. The model is finally trained and tested successfully and is found to work for power allocation with an accuracy of 99.34%, giving the best fitness of 80%, the worst fitness value of 46%, mean value of 6.76 and 0.55 STD value showing better performance compared to the existing works.

The Effect of Population Growth on Poverty Through Unemployment in East Java Province in 2017-2021

In 2022, the number of poor people in Java is ranked first in Indonesia, as many as 4. 181. 290 inhabitants (semester one) and 4. 236. 510 inhabitants (second semester). Factors are the cause of population growth and unemployment rates. Thisresearch aims to measure and determine the effect of population growth on poverty through unemployment rate as a mediating variable. Thisresearch uses quantitative methods. Data collection techniques wereobtained from the Central Statistics Agency (BPS) of East Java Province in the form of time series data from 201 to 2021. Data analysis techniques include classical assumption tests, path analysis tests and sobel tests through IBM SPSS Statistics 25 software and online statistics calculators. Theresultsof this research show that population growth has a positive and insignificant effect on poverty. The result of the regression coefficient is a positive direction of 0.324 with a significance value of 0.091 > 0.05. Inaddition, people without progress in other developmental factors will not increaseincome. Population growth has a positive and significant effect on the unemployment rate. Theresulting regression coefficient is a positive direction of 0.225 with a significance value of 0.004 < 0.05. The increase in population cannot be fully absorbed by the company. The unemployment rate has a negative and significant effect on poverty. Theregression coefficient is a negative direction of -0.948 with a significance value of 0.000 < 0.05. Unemployment is not necessarily low or underprivileged. Because they are from families withsufficient income. Population growth on poverty mediated by the unemployment rate is a negative effect and there is no mediated effect. The result of the sobel test obtained an Unstandardized Coefficients B value of -0.213 and an Unstandardized Coefficients Std value. Error of 0.085 > 0.05.

Influence of Residual Quadrupolar Interaction on Quantitative Sodium Brain Magnetic Resonance Imaging of Patients With Multiple Sclerosis.

The purpose of this work was to evaluate the influence of residual quadrupolar interaction on the determination of human brain apparent tissue sodium concentrations (aTSCs) using quantitative sodium magnetic resonance imaging ( 23 Na MRI) in healthy controls (HCs) and patients with multiple sclerosis (MS). Especially, it was investigated if the more detailed examination of residual quadrupolar interaction effects enables further analysis of the observed 23 Na MRI signal increase in MS patients. 23 Na MRI with a 7 T MR system was performed on 21 HC and 50 MS patients covering all MS subtypes (25 patients with relapsing-remitting MS, 14 patients with secondary progressive MS, and 11 patients with primary progressive MS) using 2 different 23 Na pulse sequences for quantification: a commonly used standard sequence (aTSC Std ) as well as a sequence with shorter excitation pulse length and lower flip angle for minimizing signal loss resulting from residual quadrupolar interactions (aTSC SP ). Apparent tissue sodium concentration was determined using the same postprocessing pipeline including correction of the receive profile of the radiofrequency coil, partial volume correction, and relaxation correction. Spin dynamic simulations of spin-3/2 nuclei were performed to aid in the understanding of the measurement results and to get deeper insight in the underlying mechanisms. In normal-appearing white matter (NAWM) of HC and all MS subtypes, the aTSC SP values were approximately 20% higher than the aTSC Std values ( P < 0.001). In addition, the ratio aTSC SP /aTSC Std was significantly higher in NAWM than in normal-appearing gray matter (NAGM) for all subject cohorts ( P < 0.002). In NAWM, aTSC Std values were significantly higher in primary progressive MS compared with HC ( P = 0.01) as well as relapsing-remitting MS ( P = 0.03). However, in contrast, no significant differences between the subject cohorts were found for aTSC SP . Spin simulations assuming the occurrence of residual quadrupolar interaction in NAWM were in good accordance with the measurement results, in particular, the ratio aTSC SP /aTSC Std in NAWM and NAGM. Our results showed that residual quadrupolar interactions in white matter regions of the human brain have an influence on aTSC quantification and therefore must be considered, especially in pathologies with expected microstructural changes such as loss of myelin in MS. Furthermore, the more detailed examination of residual quadrupolar interactions may lead to a better understanding of the pathologies themselves.

A regional scale impact and uncertainty assessment of climate change in the Western Ghats in India.

The general circulation models (GCMs) and emission scenarios (RCP 4.5 and 8.5) have proven to be significantly functional in evaluating the impacts of climate change (CC) on hydrology, although their performance and accuracy varies on a regional scale. The objective of the present study is to evaluate the performance of five CMIP5 GCMs (CanESM2, BNU-ESM, CNRM-CM5, MPI-ESM-LR and MPI-ESM-MR) on a regional scale in the West Flowing River Basins-2 (WFRB-2) in India to model the impact of CC and its scenario uncertainty using reliability ensemble average (REA) method. For quantifying the results, the upper, middle and lower regions of WFRB-2 are separately analysed. The MPIMR and MPILR GCM model shows highest reliability factor range (0.3-0.6) in predicting the annual mean and annual maximum rainfall for most of the grids in the region. The GCM-simulated runoff using VIC (variable infiltration capacity) model is evaluated using statistical parameters such as root mean square error (RMSE), percentage bias (Pbias) and standard deviation (Std). The annual mean (maximum) runoff obtained using REA ensemble shows least RMSE, Pbias and Std values, i.e. 21.08%, 9.10mm and 8.9mm (6%, 39.1mm, 39.1mm), respectively for the middle region, which demonstrates higher reliability of GCM outputs in the flood-prone regions of WFRB-2. Furthermore, the future projection of annual maximum rainfall/runoff shows an increase of 50mm/15mm in the near future (2011-2040) for lower and 20mm/6mm for middle regions, which may cause flooding activities in the lower and middle region of WFRB-2.

VERTICAL ACCURACY ASSESSMENT FOR OPEN-SOURCE DIGITAL ELEVATION MODEL: A CASE STUDY OF BASRAH CITY, IRAQ

Abstract. In the diverse domains of earth observation, elevation data are essential for a wide range of applications with various technical requirements and use cases. The Advanced Spaceborne Thermal Emission and Reflection Radiometer-Global Digital Elevation Model (ASTER GDEM), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), Shuttle Radar Topography Mission (SRTM), and other projects have made a large number of global Digital Elevation Model (DEM) datasets for environmental modelling and studies freely available. Global DEMs have undergone an accuracy review to measure their inherent vertical uncertainty to show how accurate information should be considered while planning and analysing. Comparing the DEMs with highly accurate geodetic control points as the independent reference data one of the best methods in the evaluation process. SRTM 30m, SRTM 90m, ALOS World 3D-30, Aster-GDEM, GMTED2010, and NASADEM are among the worldwide DEMs that were examined. Comparisons are made between 793 geodetic control points values and those from SRTM 30m, SRTM 90m, ALOS World 3D-30, Aster-GDEM, GMTED2010, and NASADEM. The statistical analysis of global DEMs from GPS reference elevations gave us that the accuracy of the ALOS World 3D-30m is much better than other models with RMSE and STD values of 1.2497 and 1.235 m, respectively. In contrast, Aster-GDEM exhibited the highest RMSE and residual error of STD values of 5.793 m and 3.394 m, respectively.

New PM2.5 forecasting system based on combined neural network and an improved multi-objective optimization algorithm: Taking the economic belt surrounding the Bohai Sea as an example

PM2.5 forecasting has always been difficult. Neural networks are widely used in the forecasting of PM2.5, however, the accuracy is not satisfactory due to uncertainty. In order to solve this problem, a new PM2.5 forecasting system based on data preprocessing, combined neural network, and the unconstrained weighting method based on an improved multi-objective optimization algorithm is proposed. A new chaotic map is introduced to our model to improve the traditional population initialization. In addition, a new unconstrained weighting method was proposed, and a combination of MAPE value (prediction accuracy) and STD value (prediction stability) were set as the objective functions. The predicted results of each neural network were judged by statistical index and a dynamic weight was given to different neural networks to achieve the optimal prediction result. We demonstrated the superiority, accuracy and generalization ability of our proposed model through experiments on the PM2.5 data of four cities around the Bohai Economic Belt in China: Beijing, Tianjin, Dalian, and Yantai.

An efficient approach to improve thermal efficiency on a low-speed two-stroke marine diesel engine

To increase the intensity of the swirl motion and further optimize the combustion characteristics, an efficient approach named cylinder gas recirculation (CGR) is proposed in this study. The effects of the CGR strategy on the swirl motion, process of fuel/air mixing, combustion characteristics, and energy distribution are investigated. Compared to the original case, the simulation results show that the CGR strategy can increase the swirl ratio with a 131.8 % increase at TDC, and the mass of cylinder recirculated gas only accounts for 3.65 % of the total mass of the charge in the cylinder. The enhanced swirl motion can improve the fuel/air mixing effect, and further optimize subsequent combustion characteristics. On the one hand, the STD value of the cases using the CGR strategy becomes smaller compared to the original case, showing the better mixing process of the fuel and surrounding charge in the cylinder. On the other hand, the enhanced swirl motion accelerates the combustion rate, specifically, the duration of CA50 ∼ CA90 of the CGR case and CGR-optimal case is reduced by 42.96 %, and 51.96 %, respectively. In the end, compared to the original case, the gross indicated work under the CGR and CGR-optimal case is increased by 0.61 % and 2.4 %, and the effective power output increases by 1.24 % and 4.84 %, respectively, which proves that the CGR strategy has great potential in improving thermal efficiency and reducing fuel consumption.

Optimal fuzzy based economic emission dispatch of combined heat and power units using dynamically controlled Whale Optimization Algorithm

The significance and purpose of this multi-objective Combined Heat and Power Economic Emission Dispatch (MO-CHPEED) problem aims to determine the optimal generator output of the co-generation systems, in which two conflicting objectives of the fuel cost and mass of emissions are to be simultaneously minimized. The nonlinear and nonconvex nature of the objective functions needs a good optimization technique to handle it. This paper proposes a Dynamically Controlled Whale Optimization Algorithm (DCWOA) to solve the multi-objective non-convex MO-CHPEED problem in fuzzy environment. The proposed DCWOA is an improved variant of the traditional WOA method by adding dynamically controlled constriction function. Both the conflicting objectives of fuel cost and mass of emissions are handled using Fuzzy Framework. To highlight the performance of the proposed technique, it is tested on the latest CEC test functions and three different MO-CHPEED case studies. The results obtained by proposed DCWOA after 100 independent trails on latest CEC test functions and compared with latest different published methods show the effectiveness and robustness of the proposed method for getting better average and STD values. Moreover, proposed DCWOA is also tested on different dimensioned MO-CHPEED test functions after 100 independent trails and compared with latest techniques. Again the most compromise results given by proposed DCWOA highlights the supremacy of the proposed method in terms of the getting better fitness and best compromise solution obtained and the convergence traits of the MO-CHPEED problem.

Motor Imagination of Lower Limb Movements at Different Frequencies.

Motor imagination (MI) is the mental process of only imagining an action without an actual movement. Research on MI has made significant progress in feature information detection and machine learning decoding algorithms, but there are still problems, such as a low overall recognition rate and large differences in individual execution effects, which make the development of MI run into a bottleneck. Aiming at solving this bottleneck problem, the current study optimized the quality of the MI original signal by “enhancing the difficulty of imagination tasks,” conducted the qualitative and quantitative analyses of EEG rhythm characteristics, and used quantitative indicators, such as ERD mean value and recognition rate. Research on the comparative analysis of the lower limb MI of different tasks, namely, high-frequency motor imagination (HFMI) and low-frequency motor imagination (LFMI), was conducted. The results validate the following: the average ERD of HFMI (−1.827) is less than that of LFMI (−1.3487) in the alpha band, so did (−3.4756 < −2.2891) in the beta band. In the alpha and beta characteristic frequency bands, the average ERD of HFMI is smaller than that of LFMI, and the ERD values of the two are significantly different (p=0.0074 < 0.01; r = 0.945). The ERD intensity STD values of HFMI are less than those of LFMI. which suggests that the ERD intensity individual difference among the subjects is smaller in the HFMI mode than in the LFMI mode. The average recognition rate of HFMI is higher than that of LFMI (87.84% > 76.46%), and the recognition rate of the two modes is significantly different (p=0.0034 < 0.01; r = 0.429). In summary, this research optimizes the quality of MI brain signal sources by enhancing the difficulty of imagination tasks, achieving the purpose of improving the overall recognition rate of the lower limb MI of the participants and reducing the differences of individual execution effects and signal quality among the subjects.

Minat Beli Konsumen Teh Botol Kemasan terhadap Variasi Produk dan Kemasan Produk

This study aimed to determine the effect of product variation, product packaging, and the effect of both (product variation, and product packaging) on ​​consumer buying interest in Sosro bottled tea at Lesehan Pak Gendut. This research used an Associative Quantitative research design. The data analysis technique used is the SPSS version 23.0 application, using data testing, and statistical testing. The results showed that product variation, product packaging, and their influence (product variation, and product packaging) respectively had Mean&gt;Std values. Dev. (41,840&gt;4,45091; 41,380&gt;4,96062; 41,300&gt;4,85399). The conclusion is that product variations and product packaging indicate an influence on consumer buying interest in bottled tea sosro at Lesehan Pak Gendut simultaneously and partially.&#x0D; Keywords: Product Packaging, Consumer Buying Interest, Product Variation

Validation of GNSS-derived global ionosphere maps for different solar activity levels: case studies for years 2014 and 2018

Ionosphere Associate Analysis Centers (IAACs) of the International GNSS Service (IGS) independently produce global ionosphere maps (GIMs) of the total electron content (TEC). The GIMs are based on different modeling techniques, resulting in different TEC levels and accuracies. In this study, we evaluated the accuracy and consistency of the IAAC GIMs during high (2014) and low (2018) solar activity periods of the 24th solar cycle. In our study, we applied two different evaluation methods. First, we carried out a comparison of the GIM-derived slant TEC (STEC) with carrier phase geometry-free combination of GNSS signals obtained from 25 globally distributed stations. Second, vertical TEC (VTEC) from GIMs was compared to altimetry-derived VTEC obtained from the Jason-2 and Jason-3 satellites and complemented for plasmaspheric TEC. The analyzed GIMs obtained STEC RMS values reaching from 1.98 to 3.00 TECU and from 0.96 to 1.29 TECU during 2014 and 2018, respectively. The comparison to altimetry data resulted in VTEC STD values that varied from 3.61 to 5.97 TECU and from 1.92 to 2.78 TECU during 2014 and 2018, respectively. The results show that among the IAACs, the Center for Orbit Determination in Europe global maps performed best in low and high solar activity periods. However, the highest accuracy was obtained by a non-IGS product—UQRG GIMs provided by Universitat Politècnica de Catalunya. It was also shown that the best results were obtained using a modified single layer model mapping function and that the map time interval has a relatively small influence on the resulting map accuracy.

Deriving drought indices from MODIS vegetation indices (NDVI/EVI) and Land Surface Temperature (LST): Is data reconstruction necessary?

Droughts pose significant economic and ecological concerns, and considering climate change projections, timely monitoring and early warning based on satellite observations must be realized at regional to global scales. Nevertheless, whether data reconstruction is necessary to produce high-quality satellite-based time series data for drought monitoring and the data reconstruction approaches to be applied, if necessary, remain unclear. We attempted to fill this knowledge gap by investigating three widely used data reconstruction approaches, i.e., the Savitzky–Golay filter, harmonic analysis of time series (HANTS) and Whittaker Smoother, across the Lancang–Mekong river basin through the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and MOD11A2 products for 2001–2018 and Google Earth Engine cloud platform. Several remote sensing drought indices based on the unreconstructed and reconstructed vegetation indices (VIs) and Land Surface Temperature (LST) were retrieved for basin-wide drought detection. The performance of the examined reconstruction approaches was evaluated using three statistical indices (coefficient of determination (R2), standard deviation of bias (BIAS(std)) and mean squared error (MSE)), spatial consistency with the reference dataset and capability to characterize the drought events. Data reconstruction considerably enhanced the drought index performances for drought detection; however, reconstruction was not necessary in all situations. The reconstructed drought indices exhibited higher R2 values (by 10.6–10.8%), lower BIAS(std) values (by −1.7– −12.5%), and smaller MSE values (by −5.8– −13.4%) compared to those of unreconstructed indices. For most evaluation indicators, HANTS outperformed the other methods, and Vegetation Condition Index (VCI) and Vegetation Health Index (VHI) outperformed the other drought indices. The findings highlight the importance of data reconstruction to detect and characterize drought events and the dependency of the performance of reconstruction methods on drought indices and evaluation metrics when using MODIS time series data.

Estimation and Analysis of BDS2 and BDS3 Differential Code Biases and Global Ionospheric Maps Using BDS Observations

Following the continuous and stable regional service of BDS2, the BDS3 officially announced its global service in July 2020. To fully take advantage of the new multi-frequency BDS3 signals in ionosphere sensing and positioning, it is essential to understand the characteristics of the differential code bias (DCB) of new BDS3 signals and BDS performance in global ionospheric maps (GIMs) estimation. This article presents an evaluation of the characteristics of 13 types of BDS DCBs and the accuracy of BDS-based GIM based on the data provided by the International GNSS Service (IGS) and International GNSS Monitoring and Assessment System (iGMAS) for the first time. The GIMs and DCBs are estimated by the APM (Innovation Academy for Precision Measurement Science and Technology) method in a time efficient manner, which can be divided into two main steps. The first step is to produce GIMs based on BDS observations at the B1I, B2I and B3I signals, and the second step is to estimate DCBs among the other frequency bands by removing the ionospheric delay using the precomputed GIMs. Good agreement is found between the APM-based satellite DCB estimates and those from the Chinese Academy of Sciences (CAS) and the German Aerospace Center (DLR) at levels of 0.26 ns and 0.18 ns, respectively. The results, spanning one month, show that the stability of BDS DCB estimates among different frequency bands are related to the contributed observations, and the receiver DCB estimates represent larger STD values than the satellite DCB estimates. The differences in receiver DCB estimates between BDS2 and BDS3 are found to be related to the types of receivers and antennas and firmware version, and the bias of the JAVAD receivers reaches 1.03 ns. The results also indicate that the difference in the single-frequency standpoint positioning (SPP) accuracy using GPS-based and BDS-based GIMs for ionospheric delay corrections is less than 0.03 m in both the horizontal and vertical directions.

Effects of stocking density on survival, growth and stress resistance of juvenile tambaqui (Colossoma macropomum) reared in a recirculating aquaculture system (RAS)

The effects of different stocking densities (StDs) on growth and stress resistance rate (Rs) to air exposure (to evaluate the health condition of fish) of juvenile Colossoma macropomum in a recirculating aquaculture system (RAS) were investigated. A total of 1064 juveniles (0.35 ± 0.10 g) were stocked in 0.5 (D0.5), 1 (D1), 3 (D3), and 5 animals/L (D5) in four different RASs of four circular tanks (28 L) each, and fed at 10% biomass/day. Growth and survival were assessed at 15, 30, 45 and 60 days. After 60 days, a 75-min air exposure test was conducted for each StD treatment and Rs determined. Regression analyses were performed for growth parameters. At 15 days, weight (W), weight gain (WG), daily weight gain (DWG), feed intake (FI), feed conversion rate (FCR), and specific growth rate (SGR) were highest for D3. At 30 days, FI was highest at the StD values estimated through the derivation of the equation of 3.55 animals/L. At 45 days, WG, DWG, and SGR decreased with increasing StD. At 60 days, W was inversely proportional to StD. Biomass was directly related to StD at the end of all periods. Air exposure stress test found that after 48 h, 72 h, and 96 h, Rs values for D3 and D5 were highest and for D0.5 lowest. Stocking densities of between 3 and 4 animals/L are recommended for the first 30 days, while higher StDs affected weight between 30 and 60 days. Animals at StDs between 3 and 5 animals/L are more resistant.

Assessment of HY-2A GM data by deriving the gravity field and bathymetry over the Gulf of Guinea

Nine cycles of Haiyang-2A (HY-2A) IGDR (Interim Geophysical Data Record) data are used to derive gravity products over the Gulf of Guinea (15° W–5° E, 4° S–4° N). Firstly, the sea surface heights (SSH) and vertical deflections are derived and their precisions are evaluated. The comparison results show that the east component of vertical deflections has a poorer precision than the north component by 4.15 times. A theoretical proof was given to explain this point according to the error propagation rule. Gravity anomalies are then derived from vertical deflections using the remove–restore method. The precision of the derived HY-2A gravity anomalies is evaluated with SIO, DTU13, EGM2008, EIGEN-6C4 products. The results showed that the differences between HY-2A-derived gravity anomalies and these models have mean values larger than 0.5 mGal and std values around 7.0–7.3 mGal. In order to improve the precision, an improved new version of gravity anomalies was derived by assigning a small weight to the east component of vertical deflections, since the precision of which is poorer than the north component. Comparison with the initial model showed that the precision of the new gravity anomalies is an improvement of the initial model by approximately two times. When compared with EGM2008, EIGEN-6C4, SIOv28 and DTU13, the mean values of the differences are close to zero and standard deviation of the differences are around 2.7–3.0 mGal. The improved gravity anomalies were used to invert the bathymetry of the region using the gravity-geologic method. The modeled bathymetry compared well with a previous bathymetric study by the authors that used DTU13 gravity anomalies. It also performed well against ETOPO1 and SRTM15+V2; with difference means, standard deviations and correlation coefficients of 26.67 m, 183.09 m, 0.9562; and 12.26 m, 174.55 m, 0.9590, respectively. This implies that SSH data from HY-2A are geophysically reliable; and hence, can be incorporated with SSH data from other satellite altimeters.