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To solve the problem of cumulative errors when robots build maps in complex orchard environments due to their large scene size, similar features, and unstable motion, this study proposes a loopback registration algorithm based on the fusion of Faster Generalized Iterative Closest Point (Faster_GICP) and Normal Distributions Transform (NDT). First, the algorithm creates a K-Dimensional tree (KD-Tree) structure to eliminate the dynamic obstacle point clouds. Then, the method uses a two-step point filter to reduce the number of feature points of the current frame used for matching and the number of data used for optimization. It also calculates the matching degree of normal distribution probability by meshing the point cloud, and optimizes the precision registration using the Hessian matrix method. In the complex orchard environment with multiple loopback events, the root mean square error and standard deviation of the trajectory of the LeGO-LOAM-FN algorithm are 0.45 m and 0.26 m which are 67% and 73% higher than those of the loopback registration algorithm in the Lightweight and Ground-Optimized LiDAR Odometry and Mapping on Variable Terrain (LeGO-LOAM), respectively. The study proves that this method effectively reduces the influence of the cumulative error, and provides technical support for intelligent operation in the orchard environment.
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BACKGROUND: Epidemiological studies have reported that among participants with impaired cognitive, overweight and mild obesity are associated with substantially improved survival, this finding has been termed the "obesity paradox" and has led to uncertainty about secondary prevention. AIMS: To explore whether the association of BMI with mortality differed in different MMSE score, and whether the obesity paradox in patient with cognitive impairment (CI) is real. METHODS: The study used data from CLHLS, a representative prospective population-based cohort study in China, which included 8348 participants aged ≥ 60 years between 2011 and 2018. The independent association between BMI and mortality in differed MMSE score by calculating hazard ratios (HRs) in multivariate Cox regression analysis. RESULTS: During a median (IQR) follow-up of 41.18 months, a total of 4216 participants died. In the total population, underweight increased the risk of all-cause mortality (HRs, 1.33; 95% CI 1.23-1.44), compared with normal weight, and overweight was associated with a decreased risk of all-cause mortality (HR 0.83; 95% CI 0.74-0.93). However, compared to normal weight, only underweight was associated with increased mortality risk among participants with MMSE scores of 0-23, 24-26, 27-29, and 30, and the fully-adjusted HRs (95% CIs) for mortality were 1.30 (1.18, 1.43), 1.31 (1.07, 1.59), 1.55 (1.34, 1.80) and 1.66 (1.26, 2.20), respectively. The obesity paradox was not found in individuals with CI. Sensitivity analyses carried out had hardly any impact on this result. CONCLUSION: We found no evidence of an obesity paradox in patients with CI, compared with patients of normal weight. But underweight individuals may have increased mortality risk whether in the population with CI or not. And overweight/obese people with CI should continue to aim for normal weight.
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Disfunção Cognitiva , Sobrepeso , Humanos , Índice de Massa Corporal , Sobrepeso/complicações , Estudos de Coortes , Magreza/complicações , Fatores de Risco , Estudos Prospectivos , Obesidade/epidemiologia , Disfunção Cognitiva/complicaçõesRESUMO
Temperature and humidity, along with concentrations of ammonia and hydrogen sulfide, are critical environmental factors that significantly influence the growth and health of pigs within porcine habitats. The ability to accurately predict these environmental variables in pig houses is pivotal, as it provides crucial decision-making support for the precise and targeted regulation of the internal environmental conditions. This approach ensures an optimal living environment, essential for the well-being and healthy development of the pigs. The existing methodologies for forecasting environmental factors in pig houses are currently hampered by issues of low predictive accuracy and significant fluctuations in environmental conditions. To address these challenges in this study, a hybrid model incorporating the improved dung beetle algorithm (DBO), temporal convolutional networks (TCNs), and gated recurrent units (GRUs) is proposed for the prediction and optimization of environmental factors in pig barns. The model enhances the global search capability of DBO by introducing the Osprey Eagle optimization algorithm (OOA). The hybrid model uses the optimization capability of DBO to initially fit the time-series data of environmental factors, and subsequently combines the long-term dependence capture capability of TCNs and the non-linear sequence processing capability of GRUs to accurately predict the residuals of the DBO fit. In the prediction of ammonia concentration, the OTDBO-TCN-GRU model shows excellent performance with mean absolute error (MAE), mean square error (MSE), and coefficient of determination (R2) of 0.0474, 0.0039, and 0.9871, respectively. Compared with the DBO-TCN-GRU model, OTDBO-TCN-GRU achieves significant reductions of 37.2% and 66.7% in MAE and MSE, respectively, while the R2 value is improved by 2.5%. Compared with the OOA model, the OTDBO-TCN-GRU achieved 48.7% and 74.2% reductions in the MAE and MSE metrics, respectively, while the R2 value improved by 3.6%. In addition, the improved OTDBO-TCN-GRU model has a prediction error of less than 0.3 mg/m3 for environmental gases compared with other algorithms, and has less influence on sudden environmental changes, which shows the robustness and adaptability of the model for environmental prediction. Therefore, the OTDBO-TCN-GRU model, as proposed in this study, optimizes the predictive performance of environmental factor time series and offers substantial decision support for environmental control in pig houses.
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The use of the black soldier fly has been demonstrated to be effective in the treatment of swine manure. Since the outbreaks of ASFV, prevention procedures, including manure disinfection, have changed dramatically. Glutaraldehyde (GA) and potassium peroxymonosulfate (PPMS) have been shown to be effective in the prevention of this pathogen and are thus widely used in the disinfection of swine manures, etc. However, research on the effects of disinfectants in manures on the growth of BSFL and gut microbiota is scarce. The goal of this study was to determine the effects of GA and PPMS on BSFL growth, manure reduction, and gut microbiota. In triplicate, 100 larvae were inoculated in 100 g of each type of manure compound (manure containing 1% GA treatment (GT1), manure containing 0.5% GA treatment (GT2), manure containing 1% PPMS treatment (PT1), manure containing 0.5% PPMS treatment (PT2), and manure without disinfectant (control)). After calculating the larval weight and waste reduction, the larval gut was extracted and used to determine the microbial composition. According to the results, the dry weights of the larvae fed PT1-2 (PT1: 86.7 ± 4.2 mg and PT2: 85.3 ± 1.3 mg) were significantly higher than those of the larvae fed GT1-2 (GT1: 72.5 ± 2.1 mg and GT2: 70 ± 2.8 mg) and the control (64.2 ± 5.8 mg). There was a 2.8-4.03% higher waste reduction in PT1-2 than in the control, and the waste reduction in GT1-2 was 7.17-7.87% lower than that in the control. In a gut microbiota analysis, two new genera (Fluviicola and Fusobacterium) were discovered in PT1-2 when compared to GT1-2 and the control. Furthermore, the disinfectants did not reduce the diversity of the microbial community; rather, Shannon indices revealed that the diversities of GT1-2 (GT1: 1.924 ± 0.015; GT2: 1.944 ± 0.016) and PT1 (1.861 ± 0.016) were higher than those of the control (1.738 ± 0.015). Finally, it was found that both disinfectants in swine manures at concentrations of 1% and 0.5% may be beneficial to the complexity and cooperation of BSFL gut microbiota, according to an analysis of microbial interactions.
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Continuous tillage cultivation positioning trials can provide the basis for maintaining soil health, improving resource utilization efficiency and crop productivity, and achieving sustainable agricultural development. In this study, changes in soil stability and water-holding capacity characteristics were measured under different tillage cultivations from a multi-year microscopic perspective and analyzed to evaluate selected key indicators. Continuous monitoring of rainfall utilization efficiency and yield was carried out for five years. Here, we discuss the role of conservation tillage in buffering and stabilizing rainfall precipitation pattern on the fluctuation and uncertainty of soil water retention and water supply capacity and soil quality. The study was carried out on dryland areas of the Loess Plateau in northern China with eight tillage systems established in 2016: no-tillage (NT); no-tillage and straw (NTS); subsoiling (SU); subsoiling and straw (SUS); rotary tillage (RT); rotary tillage and straw (RTS); conventional tillage (CT); and conventional tillage and straw (CTS). All treatments were applied in conjunction with continuous cropping for five years. The evaluated soil parameters were mean weight diameter (MWD), geometric mean diameter (GMD), >0.25 mm aggregate content (R0.25) of water-stable aggregates (WSAs), soil moisture characteristic curve (SMCC), specific soil water capacity (Cθ), soil organic matter (SOM), rainfall utilization efficiency (RUE), and maize yields for five consecutive years. The MWD, GMD, and R0.25 of SUS were 27.38%, 17.57%, and 7.68% more than CTS (control), respectively. Overall, SOM, average annual RUE, and average annual yields increased by 14.64%, 11.89%, and 9.59%, respectively, compared with 2016. Our results strongly suggest that conservation tillage can considerably improve these characterization indicators. SUS was more effective than CTS in the 0-40 cm soil layer at hedging against drought in the area, stabilizing crop production, and achieving sustainable agricultural development.
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Solo , Zea mays , Secas , China , ÁguaRESUMO
Objective: This study aimed to investigate the distribution of ideal cardiovascular health (ICH) indicators among the oldest-old and centenarians and explore their relationships with disability and health-related quality of life of this population. Methods: One thousand two centenarians from China Hainan Centenarian Cohort Study and 798 oldest-old from the China Hainan Oldest-old Cohort study were the target subjects in this analysis. ICH status, disability, and health-related quality of life of study subjects were assessed. Findings: The median value of ICH indicators among centenarians and the oldest-old is 4 (4-5) and 3 (3-5), respectively. The ICH indicators with the highest percentage of ideal level/status are fasting plasm glucose (FPG) (90.2% of study subjects are at the ideal level), BMI (89.8% of study subjects are at the ideal level), and smoking (89.4% of study subjects are at the ideal status). The disability rates of basic activities of daily living (BADL) and instrumental activities of daily living (IADL) decrease with the increasing number of ICH indicators. The EQ VAS and EQ-5D score show an increasing trend along with the increasing number of ICH indicators (p < 0.05). After adjusting related covariates, the risk of disability and lower health-related quality of life decreased gradually as the number of ICH metrics increased (p < 0.05). Interpretation: The ICH metrics of centenarians and oldest-old were at a relatively good level, and there was a strong and independent relationship between the number of ICH indicators and disability as well as the lower health-related quality of life.
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The experimentation, molecular dynamics simulation and DFT calculation were used to study the inhibition effects of four scale inhibitors, including polyacrylic acid (PAA), hydrolyzed polymaleic anhydride (HPMA), polyepoxysuccinic acid (PESA) and polyaspartic acid (PASP), on formation and crystal growth of CaCO3 in solutions. According to concentrations of Ca2+ in solutions, the sequence of inhibition effects of scale inhibitors on formation of CaCO3 in the solution was PESA > PASP > HPMA > PAA. Characterization of CaCO3 crystals by XRD and a laser particle size analyzer indicated that the sequence of inhibition effects of scale inhibitors on crystal growth of CaCO3 in solutions was PESA > HPMA > PASP > PAA. Interaction energies between the scale inhibitor molecule and Ca2+, and between the scale inhibitor molecule and the CaCO3 (104) surface indicated that the difference of the inhibition effects was derived from the difference in the interaction energy. The results of DFT calculation indicated that the difference between the interaction energies of these inhibitors and Ca2+ was derived from differences of number and the Mulliken population values of the chemical bonds which formed between the inhibitor molecule and Ca2+ and between the inhibitor molecule and the CaCO3 surface.
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This study presents the inhibitory effects of four scale inhibitors, including polyacrylic acid (PAA), hydrolyzed polymaleic anhydride (HPMA), polyepoxysuccinic acid (PESA) and polyaspartic acid (PASP), on the adsorption of CaCO3 on the surfaces of Fe3O4 and Fe2O3. Samples were characterized using SEM and EDS and the average atomic number ratios of Ca/Fe were calculated. Inhibition effects followed the trend: PESA > PAA > PASP > HPMA and PESA > PASP > HPMA > PAA for Fe3O4 and Fe2O3, respectively. Molecular dynamics simulations based on the adsorption model of the scale inhibitor on the surface and calculations of the adsorption energy between the scale inhibitor molecule and the surface revealed that the relatively high scale inhibitory effect is due to low adsorption energy between the inhibitor molecule and the surface. Density Functional Theory (DFT) calculations of the model after adsorption revealed that the relatively low adsorption energy depends on the number of H-O bonds formed as well as those with higher Mulliken population values between the scale inhibitor and the surface.
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Land use of sewage sludge is the primary disposal method in Shanxi, accounting for 42.66% of all. To determine the ecological risk of heavy metals in sewage sludge, contents of seven heavy metals in sewage sludge from 9 municipal waste water treatment plants (WWTPs) that had the highest application for land use were determined. The order of the measured concentrations was: Zn > Cr > Cu > Ni > Pb > As > Cd, and all heavy metals contents were within the threshold limit values of the Chinese Control Standards for Pollutants in Sludge from Agriculture Use (GB4284-84). Four indices were used to assess the pollution and the ecological risk of heavy metals. By the mean values of the geoaccumulation index (Igeo), heavy metals were ranked in the following order: Cd > Zn > Cu > As > Cr > Ni > Pb. The values showed that the pollution of Zn in station 3 and Cd in station 1, 2, 3, 4, 8 and 9 were heavily; Cu in station 8 and 9, Zn in station 1, 2, 4, 8 and 9 and Cd in station 5 and 7 were moderately to heavily, and the accumulation of other heavy metals were not significant. The single-factor pollution index (PI) suggested that none of the stations had heavy metals contamination, except for Cu in station 9, Zn in station 3 and 8, and Cd in station 1 and 9, which were at a moderate level. According to the results of the Nemerow's synthetic pollution index (PN), sewage sludge from all stations was safe for land use with respect to heavy metals contamination, except for stations 3, 8 and 9, which were at the warning line. The monomial potential ecological risk coefficient (Eri) revealed that heavy metals ecological risks in most stations were low. However, station 9 had a moderate risk for Cu; station 6 had a moderate risk, stations 5 and 7 had high risk, other stations had very high risk for Cd. According to the results of the potential ecological risk index (RI), station 1, 8 and 9 had high risk; station 2, 3, 4, 5 and 7 had a moderate risk, and station 6 had a low risk. The preliminary results indicated that the potential risk of land exposure to heavy metals in sewage sludge was relatively low, with Zn and Cd as the main contributor to the ecological risk for the applying of sewage sludge on land. Additionally, stations 3, 8 and 9 require more attention regarding the land applications related to heavy metals pollution.
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Monitoramento Ambiental , Metais Pesados/química , Esgotos/química , Eliminação de Resíduos Líquidos/métodos , Águas Residuárias/química , China , Cidades , Ecologia , Metais Pesados/toxicidade , Risco , Medição de Risco , Instalações de Eliminação de ResíduosRESUMO
Abstract: To compare the human health risk of heavy metals and As in sewage sludge between adults and children, samples were collected from five wastewater treatment plants (WWTPs) located in the urban district of Taiyuan, the capital of Shanxi. Heavy metals and As in sewage sludge can be ranked according to the mean concentration in the following order: Cu > Cr > Zn > Pb > As > Hg > Cd. Compared with the concentration limit set by different countries, the heavy metals contents in sewage sludge were all within the standard limits, except for the content of As, which was higher than the threshold limit established by Canada. A health risk assessment recommended by the United States Environmental Protection Agency (USEPA) was used to compare the non-cancer risk and cancer risk between adults and children. Based on the mean and 95% upper confidence limit (UCL) of the average daily dose (ADD), heavy metals and As can be ranked in the order of Cu > Cr > Zn > Pb > As > Hg > Cd for adults, and Cu > Cr > Zn > Pb > Hg > As > Cd for children. Moreover, results of ADDingest and ADDinhale indicated that ingestion was the main pathway for heavy metals and As exposure for both adults and children, and the sum of ADD implied that the exposure to all heavy metals and As for children was 8.65 and 9.93 times higher, respectively, than that for adults according to the mean and 95% UCL. For the non-carcinogenic risk, according to the hazard quotient (HQ), the risk of Cu, Hg and Cr was higher than the risk of Zn and Pb. The hazard index (HI) for adults was 0.144 and 0.208 for the mean and 95% UCL, which was less than the limit value of 1; for children, the HI was 1.26 and 2.25, which is higher than the limit value of 1. This result indicated that children had non-carcinogenic risk, but adults did not. Furthermore, ingestion was the main pathway for non-carcinogenic risk exposure by the HQingest and HQinhale. For the carcinogenic risk, Cd and As were classified as carcinogenic pollutants. The values of RISK for the mean and 95% UCL for adults and children all exceeded the limit value of 1 × 10-5, which implied that adults and children had a carcinogenic risk, and this risk was higher for children than for adults. The results of RISK for As and Cd implied that As was the main pollutant for carcinogenic risk. Moreover, the results of RISKingest and RISKinhale indicated that ingestion was the main pathway. Uncertainty analysis was performed, and the risk ranges of it were greater than certainty analysis, which implied that uncertainty analysis was more conservative than certainty analysis. A comparison of the non-carcinogenic risk and carcinogenic risk for adults and children indicated that children were more sensitive and vulnerable than adults when exposed to the same pollutant in the environment.
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Arsênio/análise , Metais Pesados/análise , Esgotos/análise , Poluentes Químicos da Água/análise , Adulto , Criança , China , Cidades , Monitoramento Ambiental/métodos , Humanos , Medição de Risco , Eliminação de Resíduos LíquidosRESUMO
Heavy metals (HMs) in sewage sludge have become the crucial limiting factors for land use application. Samples were collected and analyzed from 32 waste water treatment plants (WWTPs) in the Shanxi Province, China. HM levels in sewage sludge were assessed. The multivariate statistical method principal component analysis (PCA) was applied to identify the sources of HMs in sewage sludge. HM pollution classes by geochemical accumulation index I(geo) and correlation analyses between HMs were also conducted. HMs were arranged in the following decreasing order of mean concentration: Zn > Cu > Cr > Pb > As > Hg > Cd; the maximum concentrations of all HMs were within the limit of maximum content permitted by Chinese discharge standard. I(geo) classes of HMs pollution in order from most polluted to least were: Cu and Hg pollution were the highest; Cd and Cr pollution were moderate; Zn, As and Pb pollution were the least. Sources of HM contamination in sewage sludge were identified as three components. The primary contaminant source accounting for 35.7% of the total variance was identified as smelting industry, coking plant and traffic sources; the second source accounting for 29.0% of the total variance was distinguished as household and water supply pollution; the smallest of the three sources accounting for 16.2% of the total variance was defined as special industries such as leather tanning, textile manufacturing and chemical processing industries. Source apportionment of HMs in sewage sludge can control HM contamination through suggesting improvements in government policies and industrial processes.