Random Factors Research Articles

Spatial Variability Characteristics and Influencing Factors of Soil Fluoride in the Western Nansihu Lake Basin

The western plain of the Nansihu Lake Basin (NLB) is an important agricultural economic zone in Shandong Province, where there is a high content of fluoride in soils. Studying the content and influencing factors of fluoride in soils is of great significance for the maintenance of regional eco-logical security and human health. This study takes the farmland soils in the west of NLB as the research focus and uses a method based on GIS and geostatistics to quantitatively analyze the spatial variation characteristics of soil total fluoride and water-soluble fluoride contents to draw a map showing their spatial distribution. The effects on the spatial distribution of soil total fluoride and water-soluble fluoride were analyzed from the aspects of geomorphological type, soil parent material (stratigraphic lithology), crop type, and groundwater fluoride concentration, among others, and the correlation between groundwater and soil fluoride contents was also analyzed. Our study results in the following findings: (1) The average content of total fluoride in topsoil in the study area is 652.8 mg/kg, the national background value is exceeded in 99.5% of the sampling sites, and the background value of Shandong Province is exceeded in 98.7% of the sampling sites. The average water-soluble fluoride is 15.2 mg/kg and exceeds 5.0 mg/kg in 94.3% of the sampling sites. Topsoils have high values of total fluoride and water-soluble fluoride. (2) The total fluoride and water-soluble fluoride in topsoils exhibit moderate spatial variability, indicating that their spatial distribution is the result of structural factors such as soil parent materials and man-made random factors such as fluorinated fertilizers. (3) In the 2 m vertical profile of shallow soils, total fluoride and water-soluble fluoride increase with the increase in soil viscosity, and the water-soluble fluoride has the characteristics of surface aggregation due to the influence of soil adsorption. Because fluoride ions as ligands are easily adsorbed and form fluoride complexes with other ions such as aluminum ions, the water-soluble fluoride shows the characteristics of surface aggregation and fractionation. (4) The analysis of influencing factors reveals that the lithology of Quaternary strata, geomorpho-logical types, and planting crop types have significant effects on the distribution of the total fluoride and water-soluble fluoride in the topsoils, and the distribution of the groundwater soluble fluoride in the topsoils is not related to that in groundwater. Our study provides data and technical support for improving both the soil environmental quality and water quality of the eastern route of the South-to-North Water Transfer Project, thus helping to promote the sustainable development of the social economy and ecological environment in the NLB.

Personalized fuzzy semantic model of PHFLTS: Application to linguistic group decision making

The proportional hesitant fuzzy linguistic term set (PHFLTS) has been effectively employed in analyzing the group’s hesitancy in linguistic group decision making (LGDM). The application of PHFLTS assists in capturing the individual’s hesitancy across diverse time periods. It is acknowledged that a single word could potentially convey various meanings to different decision makers, such differences can be proficiently managed by utilizing personalized individual semantic (PIS) models. Previous approaches for calculating PIS failed to incorporate the individual’s updating preference information over time, which increases the risk that the computation of PIS is affected by random factors in a specific moment. In our current research, individual linguistic preference gathered over a time period are leveraged to form the PHFLTS. Additionally, a consistency driven optimization model based on PHFLTS is formulated to obtain PIS of linguistic terms. Subsequently, a fuzzy representation model termed as the fuzzy envelope of PHFLTS is introduced to facilitate the computation with words processes, integrating PHFLTS in LGDM. The practicality and legitimacy of these proposed models are evaluated through a comparative analysis. Lastly, these proposed models are tested and applied in a dedicated case study to further prove their usefulness and efficacy.

Effect of heterogeneity of particle properties on the mechanical properties of sandy soil materials

The random arrangement of particle composition or the heterogeneity of the particles' inherent properties is what causes the variability of mechanical parameters in sandy soils. Combining the discrete element method with random field theory, a random discrete coupling modeling method is refined, in which a rolling resistance contact model was used to take into account the rolling friction characteristics of sand soil particles. Four random discrete element models (RDEM) are developed for typical working situations taking into account the two random field factors, i.e., the coefficient of variation and fluctuation range. The Monte Carlo method is employed to simulate the triaxial RDEM, and the stress-strain relations, parameters of strength and deformation are analyzed. The effects of the coefficient of variation (Cov) and fluctuation range (δ) on the variability of mechanical characteristics are studied. The results show that the mean shear modulus G, peak friction angle φp, and critical friction angle φc of random heterogeneous samples decline while the mean Poisson's ratio μ increases as the Cov increases. The mean values of parameters of deformation and strength of random heterogeneous samples eventually approach those of homogeneous samples as the δ increases.

Efficacy of high dose systemic versus combined (systemic and intratympanic) corticosteroid therapy in idiopathic sudden sensorineural hearing loss: A prospective randomized trial and risk factor analysis

The pathophysiology and the proper treatment of idiopathic sudden sensorineural hearing loss (ISSNHL) are an ongoing subject of debate. Locally or systemic administered corticosteroids are the most accepted drugs of treatment in reference to ISSNHL (idiopathic sudden sensorineural hearing loss), however, no strong evidence nor guidelines regarding their effectiveness yet exists.In our prospective, randomized, controlled trial 78 participants were enrolled. Patients were randomly assigned based on the day of admission to two groups according to treatment: group SS (n = 43) received intravenous systemic methylprednisolone alone, and group CT (n = 35) received intratympanic dexamethasone + systemic methylprednisolone. The primary outcome was to compare the hearing outcomes between the treatment groups based on different, widely accepted categories (Siegel, Kanzaki, modified Siegel and PTA4 gain). In consideration of the secondary outcome, we examined the effect of the various risk factors on the hearing improvement.No differences were detected regarding hearing improvement between the two groups, based on any criteria [Siegel's criteria (p = 0.604); Kanzaki's criteria (p = 0.720); modified Siegel's criteria (p = 0.524) and PTA 4 gain (p = 0.569)]. However, several clinical factors such as vertigo (p = 0.039), or cardiovascular comorbidity (p = 0.02) and the severity of initial hearing loss (p = 0.033) were found to bear a significant impact upon the hearing outcome.To the best of our knowledge, this is the first randomized controlled trial comparing high dose systemic and combination corticosteroid therapy in ISSNHL patients. Our findings suggest coexisting cardiovascular comorbidity, vertigo and severity of the initial hearing loss may bear a significantly higher impact upon hearing improvement, than the additional intratympanic steroid administration.The presented trial was registered in the European Union Drug Regulating Authorities Clinical Trials Database (name: Combinated systemic and intratympanic steroid therapy in idiopathic sudden sensorineural hearing loss, No.: 2017–000658-20) and with the ethical approval of The National Institute of Pharmacy and Nutrition (OGYÉI) (protocol No.: 7621, on 2017.02.16.)

The effect of advanced footwear technology on elite male marathon race speed.

The aim of this study was to explore the ergogenic effect of advanced footwear technology (AFT) upon world-class male marathon running speed. A retrospective analysis of 99 world-class male marathon runners' performances between 2012 and 2021 was undertaken, providing a sample size of 971 performances, split into two footwear groups: AFT (n = 299) and traditional (n = 672). Additionally, details regarding the year of the marathon performance and racecourse were extracted. A mixed model for repeated measures (MMRM) analysis were undertaken identifying athlete (Wald Z = 2.821; p = .005) and course (Wald Z = 4.111; p < 0.001) as significant contributors to the variance in marathon running speed and as such were included as random factors with footwear type set as a fixed factor. World-class male marathon running speeds were significantly faster (p < 0.001) when running in AFT (5.441m.s-1) when compared with traditional shoes (5.386m.s-1) with a mean difference of 0.055m.s-1 (95% CI 0.039-0.071m.s-1), translating to an improvement in marathon speed of 1.0% or a 79s improvement in marathon race time. Our findings demonstrate an improvement in world-class male marathon running speed of 1% when running in AFT, a near identical degree of improvement to the male marathon world record ran in AFT. Whilst a 1% improvement in marathon running times associated with AFT is smaller than previously predicted utilizing laboratory-based models, this still reflects a significant degree of improvement at the elite level.

Transmission reliability evaluation of wireless sensor networks considering channel capacity randomness and energy consumption failure

The reliable transmission of data packets is the basis of ensuring the Internet of Things applications. Therefore, how to ensure the transmission reliability of wireless sensor networks has already become a hotspot. However, the existing researches ignore the effects of multiple fault modes and random factors on transmission reliability. Firstly, in the node reliability modeling, few studies have considered the effects of random failure and energy consumption failure comprehensively. Secondly, in the link reliability modeling, existing studies ignore the effect of the channel capacity randomness, which can lead to the erroneous estimation of transmission reliability. To overcome the above shortcomings, we propose a more realistic transmission reliability model. Firstly, considering the comprehensive effects of two failure modes, we establish a new node reliability model to better characterize the node performance. Secondly, considering the channel capacity randomness, we propose an improved SNR-Capacity connection model by deriving the one-hop connectivity probability, which can better characterize the link reliability. Then, we propose a transmission reliability evaluation model, and give the corresponding exact and approximate algorithms for its solution. Finally, taking the military Internet as an example, the effectiveness of the proposed method is verified.

Psychosocial stress in children with Tourette syndrome and chronic tic disorder

BackgroundThis study aimed to understand the longitudinal relationship between psychosocial stress with tic exacerbation in children with Tourette syndrome (TS) and chronic tic disorder. MethodsConsecutive ratings of tic severity as well as child and parental reports of psychosocial stress were obtained for 373 children (296 males, 77 females; mean age 9y 5mo; SD 3y 3mo) with TS and chronic tic disorder between January 2018 and December 2020. The Yale Global Tic Severity Scale (YGTSS) global severity score, total tic score, and impairment rating were calculated. The stressful events and YGTSS measurements were used and treated as time-varying variables in the analyses. Models that controlled for non-independence among the repeated observations using a random intercept and random slope model were employed. Each participant was treated as a random factor in the modelling. ResultsFamily-related stress, personal relationship stress and school-related stress were independently associated with increasing YGTSS global severity, total tic score, and impairment rating over time. An increased number of stressful events were associated with increased severity of tics. ConclusionFamily, personal relationships, and school-related stress were consistently associated with the exacerbation of tics. Managing these stressful events is important in the treatment of TS and chronic tic disorder.

4 Severity of Retinopathy of Prematurity and Motor Skills Development in Preschoolers

AbstractObjective:Children born preterm are at increased risk of deviation from the typical developmental trajectory. The probability of adverse developmental sequelae is increased in those with history of major perinatal complications. Retinopathy of prematurity (ROP) is a pathological disordered growth of retinal blood vessels occurring in very preterm neonates who require supplemental oxygen. ROP has been linked to intermittent hypoxemic events and blood gas derangements occurring in the Neonatal Intensive Care Unit (NICU), particularly in ventilated infants. Though presence and severity of ROP have been linked to neurodevelopmental impairment, little is known about the relationship between ROP severity and motor development in the preschool age. Because the same hypoxemic events and blood gas changes that lead to severe ROP may also lead to greater developmental deficits in motor control, we hypothesized that ROP severity will be inversely linked to the quality of motor functioning even in NICU graduates without neurological impairments.Participants and Methods:We included 95 preterm (23.6 - 33.6 weeks gestation) preschoolers (49 females, 44 members of twin pairs or triplets). The participants' age ranged from 3.3 - 4.1 years (adjusted for prematurity). ROP screening was conducted during NICU stay and rated from immature retina (0) to grade 4. Motor abilities were assessed with the Peabody Developmental Motor Scales (PDMS-2). Cases with diagnosed perinatal brain pathology (moderate to severe) or cerebral palsy were excluded from analyses.Results:We used linear mixed regression analyses with multiple gestation as a random factor. Severity of ROP was our predictor of interest, whereas socioeconomic status, sex, gestational age, and birth-weight SD served as covariates. Separate analyses were conducted using the PDMS-2 Total Motor, Fine Motor, and Gross Motor Quotients as dependent variables. ROP severity explained a unique portion of the variance in the Total Motor Quotient (F[1, 89] = 5.59, p = .02). Examination of the relationship between ROP severity and motor skill domains yielded a significant association for the Fine Motor Quotient (F[1, 89] = 6.19, p = .015) and a trend for the Gross Motor Quotient (F[1, 89] = 3.64, p = .06).Conclusions:The results of this study reveal that increase in ROP severity is linked to poorer motor skills in preterm-born preschoolers without major disabilities or perinatal diagnosis of moderate to severe brain pathology. This association was evident for both fine and gross motor skills, though only the relationship between ROP severity and the former motor index reached conventional statistical significance. Importantly, ROP severity accounted for a unique portion of the variance in motor performance, over and above the variance explained by other perinatal risk factors. This result is consistent with previous research findings indicating that ROP is linked to the occurrence of multiple, subtle hypoxemic events and 'exposure' to blood gas derangements during NICU stay in very preterm neonates who require respiratory support.

Incidence and risk factors of post-stroke seizures and epilepsy: systematic review and meta-analysis.

Due to variability in reports, the aim of this meta-analysis was to evaluate the incidence and risk factors of post-stroke early seizures (ES) and post-stroke epilepsy (PSE). The MEDLINE, EMBASE and Web of Science databases were searched for post-stroke ES/PSE articles published on any date up to November 2020. Post-stroke ES included seizures occurring within 7 days of stroke, and PSE included at least one unprovoked seizure. Using random effects models, the incidence and risk factors of post-stroke ES and PSE were evaluated. The study was retrospectively registered with INPLASY (INPLASY2023100008). Of 128 included studies in total, the incidence of post-stroke ES was 0.07 (95% confidence interval [CI] 0.05, 0.10) and PSE was 0.10 (95% CI 0.08, 0.13). The rates were higher in children than adults. Risk factors for post-stroke ES included hemorrhagic stroke (odds ratio [OR] 2.14, 95% CI 1.44, 3.18), severe strokes (OR 2.68, 95% CI 1.73, 4.14), cortical involvement (OR 3.09, 95% CI 2.11, 4.51) and hemorrhagic transformation (OR 2.70, 95% CI 1.58, 4.60). Risk factors for PSE included severe strokes (OR 4.92, 95% CI 3.43, 7.06), cortical involvement (OR 3.20, 95% CI 2.13, 4.81), anterior circulation infarcts (OR 3.28, 95% CI 1.34, 8.03), hemorrhagic transformation (OR 2.81, 95% CI 1.25, 6.30) and post-stroke ES (OR 7.24, 95% CI 3.73, 14.06). Understanding the risk factors of post-stroke ES/PSE may identify high-risk individuals who might benefit from prophylactic treatment.

Nested Linear Mixed Models with Repeated Measurement for Analyzing Telecommunication Products

Nested linear mixed model is a model that combines fixed factors and random factors. Observations made over time with the same object being observed are called repeated measurements. This research was conducted to determine the determinant factors of internet data quota sales which are influenced by SA (Sales Area), MC (Mutual Check), PC (Product Category), and time factors using a nested linear mixed model with repeated measurement. SA, PC, and time factors as fixed factors while the MC factor nested in SA as a random factor. The results showed that the interaction effect between three fixed factors, namely between SA, PC, and time have a significant effect on the sales volume of internet data quota. Moreover, variation in the sales volume between MC factors was significant. The interaction between MC and PC, and the interaction between MC and time were significant on the sales volume of internet data quota.

Failure time prediction for vehicle dynamics under performance degradation of dampers and track evolution

During long-term service, railway vehicles will experience damper performance degradation and track evolution, both have significant effects on the vehicle dynamics performance. This study aims to develop a mathematical model for assessing the failure time of the vehicle system dynamics when considering two random factors. As for the methodology, Wiener processes are used to propose a damper degradation model. Moreover, a continuous-time Markov chain is adopted to describe the state transaction of the track irregularities. In addition, the Monte Carlo method is employed to sample the dynamic responses of the vehicle using stochastic parameters. Finally, the Bayesian theory is utilized to establish the reliability model of the Weibull mixtures under the Dirichlet process prior. The results are obtained through a numerical example: the dampers’ individual differences directly affect effect on the rate of degradation of the vehicle dynamics performance. Furthermore, different indexes positively correlate with each other, mixture models are composed of a small number of components, and Weibull mixtures closely approximate the distribution of the failure time. Compared to other dampers, the anti-yaw dampers have a more significant impact on the vehicle system dynamics. Other results show that each type of damper can adopt a uniform replacement period whereas anti-yaw dampers should be more effectively monitored.

229 Effect of Two Sources of Zinc on Growth Performance and Gut Health of Piglets with a Low or Normal Birth Weight

Abstract Zinc (Zn) is an essential trace element for piglets. The study aimed to compare effects of two Zn sources on piglets divided into two body weight (BW) categories. At birth, piglets were weighed and divided into low BW (LBW &amp;lt; 1 kg) or normal BW (NBW &amp;gt; 1 kg). At weaning (25 days of age, d 0), 64 piglets were divided into 4 groups (8 replicates of 2 piglets/group) as follows: 1) LBW piglets fed a standard diet plus 120 ppm of Zn from ZnSO4, 2) NBW piglets fed a standard diet plus 120 ppm of Zn from ZnSO4 (CO), 3) LBW piglets fed standard diet plus 120 ppm of Zn from a potentiated Zn source (HiZox, HZ), and 4) NBW piglets fed a standard diet plus 120 ppm of Zn from a potentiated Zn source HZ. Growth performance was measured at d 0, d 9, d 14, and d 21. The fecal index was recorded daily. On d 9 and d 21, one piglet per replicate was slaughtered. Blood and gut tissue were collected to evaluate the immune and inflammatory status of the piglets. The groups were arranged using a 2 x 2 factorial design, considering the class of birth BW (LBW and NBW) and the diet (CO and HZ). For the diarrhea index, a generalized linear mixed model fitting a Poisson distribution was used. Other variables were analyzed with a linear mixed model, in which the diet, class of BW and their interaction were included as fixed factors and litter of origin was included as a random factor. Piglets from the NBW group had consistently greater BW throughout the study (P &amp;lt; 0.01) than LBW piglets. The treatment HZ tended to improve BW gain from d 0 to d 9 and from d 9 to d 14 (P &amp;lt; 0.10), and significantly influenced the G:F ratio (P &amp;lt; 0.05). The fecal index was decreased by HZ from d 0 to d 14, and from d 0 to d 21 (P &amp;lt; 0.01), particularly for LWB piglets (P-interaction &amp;lt; 0.01). Haptoglobin and reactive oxygen metabolites decreased from d 9 to d 21 (P &amp;lt; 0.01) in serum. Expression of the NFKB-2 gene was less in NBW piglets than in LBW piglets and in HZ groups. In conclusion, potentiated Zn positively influenced the growth performance of LBW and NBW piglets.

Some Evidence That Truth-Tellers Are More Attractive Than Liars.

Despite the prevalence of deception, people rarely doubt others' sincerity. However, indirect evaluations of liars and truth-tellers may differ even in the absence of suspicion about veracity. Across three studies, we provide evidence for the truth attraction effect in two samples of target stimuli and three samples of participant judges. Target people are perceived as more attractive when telling the truth versus when they lie, an effect mediated by target warmth and openness. The truth attraction effect is stronger for female targets (vs. males); however, it is unaffected by the gender of the judge. Findings suggest people may be more likely to approach truth-tellers versus liars, even when not actively judging veracity. We discuss the challenges and benefits of treating both targets and participants as random factors in linear mixed-effect analyses and join the chorus of calls to increase the number of target stimuli in deception research.

Effect of random factors on liquid flow over the sheets of a structured packing

Effect of random factors on liquid flow over the sheets of a structured packing

A stochastic predator–prey model with distributed delay and Ornstein–Uhlenbeck process: Characterization of stationary distribution, extinction, and probability density function

As the evolution of species relies on not only the current state but also the past information, it is more reasonable and realistic to take delay into an ecological model. This paper deals with a stochastic predator–prey model that considers the distribution delay and assume that the intrinsic growth rate and the death rate in the model are governed by Ornstein–Uhlenbeck process to simulate the random factors in the environment. Based on the existence and uniqueness of the global solution to the model and the boundedness of the order moments of the solution, several conditions are established to analyze the survival of the species. Specifically, a criteria for the existence of the stationary distribution to the stochastic system is established by constructing some suitable Lyapunov functions. And the analytical expression of the probability density function of the model around the quasi‐equilibrium is obtained. Furthermore, the extinction of species in the model is also explored. Finally, numerical simulations are carried out to illustrate the theoretical results obtained in this paper.

Spatial point pattern of the baobab (Adansonia digitata) in semi-arid savanna, Southeast Zimbabwe

Species distribution modelling based on bioclimatic variables to understand habitat suitability and changes in range dominates studies on the spatial distribution of baobabs, which limits our understanding of how the small-scale plant–plant interactions influence the spatial point pattern of this keystone species in semi-arid regions of sub-Saharan Africa. Here, we investigated the spatial distribution of the baobab in two protected areas, Chipinge Safari Area (CSA) and Save Valley Conservancy (SVC) which lie in the semi-arid Southeastern lowveld of Zimbabwe. CSA was previously a sparsely human populated area before its proclamation as a protected area, has a small number of herbivores and baboons, and has no elephants, while SVC has a high density of elephants (1.5 km−2) and large number of herbivores. At each site, 1 km2 plots, SVC (n = 4) and CSA (n = 3), were established for spatial analysis. In each plot, we recorded the spatial location, elevation, height, diameter at breast height, and canopy cover of each baobab. Spatial point-pattern was assessed using both the inhomogeneous transformed L-function for Ripley's K-function and the pair-correlation function. Baobabs in SVC were larger (height, canopy cover, and basal area) relative to those in CSA. At both sites, baobabs were clustered at small spatial scale (0–50 m), indicating that competition was insufficient to cause density-dependent thinning that can lead to even distribution as we expected. The distribution of small baobabs was independent of large baobabs, which reflects the importance of other environmental factors such as site conditions and seed dispersal rather than nurse-protégé on seedling establishment. The random distribution pattern of adult baobabs could be the legacy effects of these random factors and processes at establishment. Overall, our study shows that the distribution of baobabs is not dependent on local plant–plant interactions, but most likely from larger scale random pattern forming factors and processes such as seed dispersal and environmental heterogeneity.

Fault diagnosis of gas turbine generator bearings using enhanced valuable sample strategy and convolutional neural network

Gas turbine bearings operate continuously under complex and harsh conditions such as high temperatures, high pressures and high speeds. Bearing fault monitoring data often exhibits anomalies, noise, missing values, and strong coupling and non-linearity due to real-world random factors. In addition, the traditional convolutional neural network (CNN) is still limited by the scarcity of labeled samples in real-world conditions and cannot fully extract fault features. To address the complexities of strongly coupled fault data, inconsistent data quality, and the shortage of authentic labeled samples, this paper presents a novel method for bearing fault diagnosis. This method utilizes an enhanced valuable sample strategy in conjunction with CNNs, integrating data enhancement and active learning (AL) for preprocessing to create valuable training sets for the networks. At the outset, random dropout and scaling jitter operations are applied to the original data, effectively removing anomalies and gaps in the fault signals. This process simultaneously emulates variations in the frequency spectrum and amplitude of vibration signals under real operating conditions, thereby enhancing the quality of gas turbine bearing fault data. Subsequently, the method incorporates AL techniques, iteratively selecting unlabeled data samples with the highest information value, and annotating them using support vector machines. This strategy creates a valuable training dataset that further enhances the fault diagnosis capabilities of the model. In the subsequent phase, a three-dimensional CNN is employed to extract fault feature information efficiently from the fault data, culminating in precise fault classification. In order to validate the effectiveness and superiority of the algorithm, validation and comparison analyses were carried out using the Case Western Reserve University and XJTU open datasets. To evaluate the practical effectiveness, a gas turbine main bearing dataset collected in a real environment, named the BaiChuan dataset, is used for the engineering validation of the proposed method.

Evaluation and spatial convergence of carbon emission reduction efficiency in China's power industry: Based on a three-stage DEA model with game cross-efficiency

Reducing carbon emissions is essential for achieving sustainable development in China. In this study, we developed a framework for measuring carbon emission reduction considering both thermal power and clean energy generation perspectives. Subsequently, we constructed a three-stage data envelopment analysis (DEA) model with game cross-efficiency to eliminate the influence of external environmental factors, random factors, and regional competition. Thereafter, we calculated the carbon emission reduction efficiencies (CEREs) of the power industries of 30 provinces in China from 2010 to 2020. Based on this, we conducted temporal and spatial analyses of the carbon emission reduction amount (CERA), evaluated CERE, compared different DEA models, and assessed spatial convergence effects. The evaluation results of CERE across 30 provinces, cities, and autonomous regions in China showed that: (1) although China's CERA increased, substantial regional differences exist in the carbon emission reduction structure. (2) The overall average CERE ranged from 0.485 to 0.737. Since 2016, the highest CERE values have been observed in southwest China, followed by the eastern coastal and central regions, while the northwestern region experienced notable fluctuations. (3) The three-stage DEA model with game cross-efficiency, which eliminates the influence of competition and external environmental factors, can be used to accurately measure CERE. (4) CERE has a spatial convergence effect on China's power industry and is promoted by energy structure, upgrading of industrial structure and government interventions. These findings provide important insights for optimizing the carbon emissions reduction structure and improving CERE.

A dual-branch siamese spatial-spectral transformer attention network for Hyperspectral Image Change Detection

The convolutional neural networks have recently gained widespread attention in Hyperspectral Image Change Detection (HSI-CD) due to their outstanding feature extraction ability. However, limited by the inherent network backbones, the convolutional neural networks (CNNs) fail to mine the sequence attributes and model the intricate relationships of spectral signatures. In contrast, transformers are proficient at learning sequence information owing to the powerful self-attention mechanisms. The two backbone structures exhibit complementary spatial and spectral feature extraction strengths, respectively. Inspired by this, we propose a dual-branch siamese spatial–spectral transformer attention network (DBS3TAN) for HSI-CD. The main idea is to fully exploit the advantages of CNNs and transformers for spatial and spectral feature extraction. More importantly, we devise the two key modules, i.e., the spatial attention module and the spatial–spectral transformer module. The former utilizes depthwise separable convolutions and attention mechanisms to emphasize the features of dual-temporal HSIs from the spatial perspective. The latter focuses on the sequence attributes of spectral signatures and mines the spatial characteristics from adjacent pixels. We employ the weighted contrastive loss function to separate the changed and unchanged pixels more reliably and set the random weight factors to balance the contributions of the two branches. Finally, the threshold values judgment is used to obtain the ultimate detection maps. We conduct extensive experiments to evaluate the DBS3TAN on three HSI datasets, demonstrating its superior performances than compared methods qualitatively and quantitatively. The source code will be available at https://github.com/zhangyiyan001/DBS3TAN.

County-Scale Spatial Distribution of Soil Nutrients and Driving Factors in Semiarid Loess Plateau Farmland, China

Characterized by a topography of thousands of ravines, the Loess Plateau has highly complex spatial variability in terms of soil nutrients. Therefore, it is of considerable importance to study the soil nutrient spatial distribution, driving factors of precise fertilizer management, and the strategic use of soil nutrient resources. In 2017, 242 soil samples were taken from the semiarid Anding district farming region in northern China. The spatial variability and factors influencing soil nutrients were studied using statistical and geostatistical methods. The results showed that the mean soil organic matter (SOM), total nitrogen (TN), available phosphorus (AP), available potassium (AK), and pH values were averaged at 12.64 g·kg−1, 0.84 g·kg−1, 23.20 mg·kg−1, 188.87 mg·kg−1, and 8.60, respectively. The nugget-to-sill ratios for the semi-variograms of SOM, TN, AP, and AK varied from 25.84 to 49.93%, while the coefficients of variation varied from 24.53 to 69.44%, revealing that all four indicators exhibited considerable variability, and that the samples’ geographical variability was produced by a combination of random and structural factors. Overall increasing trends were exhibited from the middle to the northeast and southwest in the distributions of SOM, TN, and AP. The spatial distribution of AK displayed the opposite trend, increasing from the southwest to north and southeast. The texture of the tillage layer was the main factor directly affecting SOM, and explained 8% of its variation. The distribution of TN was mainly influenced by the irrigation method and water source type. AP and AK contents differed significantly between the two parent materials, three textures, and three topography types at the level of p &lt; 0.01. In conclusion, the regional soil fertility was poor, spatial heterogeneity was moderate, and influencing factors were complex, highlighting the need to adopt precise fertilization management and adopting land management measures according to the actual influencing factors of each nutrient, thereby contributing to the enhancement of regional fertility.