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Abstract The accurate estimation of regional crop yields holds significant importance for optimizing subsequent resource allocation and maximizing economic returns in agriculture. Crop yield can be effectively estimated by assessing the overall growth status through long-term remote sensing observations. However, most previous studies have relied on remote sensing data from one or a few periods for yield estimation, thus lacking a comprehensive description of entire crop growth. Furthermore, past algorithms have not considered their applicability across different observational scales (e.g., unmanned aerial vehicle (UAV)- and satellite-observed). Considering this, we extracted four maize growth process parameters using Leaf Area Index (LAI) obtained from UAV (equipped with multispectral sensor, centimeter-level) and satellite (MODIS, 1 km) observations: PP_a (representing the duration of the crop growth period), PP_b (representing the peak growth stage of the crop), PP_c (representing the initial state of the crop), and LAImax (maximum LAI). These parameters were used to construct a maize yield estimation model applicable at both regional and field scales. The results indicate that the four process parameters extracted in this study can accurately estimate crop yields, with rRMSE = 14.08% at the field-scale and rRMSE = 17.75% at the regional-scale. Among these parameters, PP_a, representing the duration of the crop growth period, and the maximum LAI, are the parameters that individually contribute the most to the estimation accuracy. Moreover, the proposed method exhibited good spatial applicability (field-scale: Moran Index (MI) = -0.18; regional-scale: MI = 0.19). In conclusion, the parameters describing maize growth process derived from long-term-series observations can effectively estimate maize yield across different observation scales. This method not only facilitates the optimization of agronomic practices based on UAV observations but also supports the decision of regional agricultural policies based on satellite observations. Furthermore, crop yield estimation utilizing process-based parameters provides a new perspective for related studies.

To investigate the factors influencing the colonoscopy screening behavior of first-degree relatives of colorectal cancer patients and to provide a basis for formulating screening intervention strategies. In this study, 15 first-degree relatives of colorectal cancer patients in the Department of Medical Oncology of a tertiary hospital in Baoding City from May to July 2024 were selected as the research subjects, and face-to-face semi-structured interviews were conducted. The theme was analyzed and summarized based on the theory of planned behavior and Colaizzi’s 7-step analysis method. Results of this study identified 12 themes from 3 aspects. For behavioral attitudes, 4 themes emerged: (1) Negative screening emotions caused by psychological stress, (2) Lack of awareness of the importance of screening due to cognitive biases, (3) Screening behavior caused by fatalistic views is systematically underestimated, and (4) Affirm the value of early screening. For subjective norms (The impact of external information on screening behavior), 4 themes emerged: (1) Family support, (2) Advice from a healthcare professional, (3) information support from online media, (4) Personal experience and suggestions from friends. For perceived behavior control, 4 themes emerged: (1) Unbearable pain and embarrassment, (2) Busyness of life and work, (3) Medical treatment process and transportation convenience, and (4) Screening costs. The colonoscopy screening behavior of first-degree relatives of colorectal cancer patients is affected by behavioral attitudes, subjective norms (The impact of external information on screening behavior), and perceived behavior control. Clinical medical staff should correct their behavioral cognitive biases from the perspective of first-degree relatives, use positive belief factors to avoid wrong cognition, pay attention to a variety of sources of support, stimulate the self-efficacy of first-degree relatives, and create a suitable environment for colonoscopy screening, to promote the change of colonoscopy screening behavior of first-degree relatives.

Abstract It is important to understand the effects of environmental factors such as air pollution on mitochondrial structure and function, especially when these changes increase cardiovascular disease risk. Although lifestyle choices directly determine many mitochondrial diseases, increasingly, it is becoming clear that the structure and function of mitochondria may be affected by pollutants found in the atmosphere (e.g., gases, pesticides herbicide aerosols, or microparticles). To date, the role of such agents on mitochondria and the potential impact on cardiovascular fitness is neglected. Here we offer a review of airborne stressors and pollutants, that may contribute to impairments in mitochondrial function and structure to cause heart disease.

The variability of natural parameters in border fields is one of the main factors leading to poor irrigation performance. To explore the impact of natural parameter variation on border irrigation performance, a four-year field irrigation experiment was conducted in this study, and the obtained parameters were combined with the WinSRFR V4.1 model to simulate the advance–recession process under different discharge scenarios. Based on the observed and simulated data, the influence of natural parameter variation on the flow process of constant discharge irrigation was analyzed, and thus the optimal observation points for advancing and discharge regulation strategy were further established. The results indicated that in a constant discharge border irrigation system, the irrigation performance index showed a trend of first increasing and then decreasing with the increase in discharge, and the variation range of the reduced section was smaller than that of the increased section. Therefore, the risk of inefficient irrigation caused by flow fluctuations could be reduced to a certain extent by increasing the discharge. Additionally, variability in natural parameters also caused the water advance time to deviate gradually from expectations, and the deviation would be obvious when the flow advanced to the point of 40 m. The adjustment range of the optimal regulation discharge qM was greater than the corresponding optimal constant discharge qD2 under natural parameter variations. In the ideal situation of uniform natural parameters within the border, the optimal discharge regulation scheme could improve the application efficiency, irrigation uniformity, and water storage efficiency to 97.3%, 95.5%, and 96.9%, respectively. The results of this study can provide a theoretical basis for the development of automatic regulation of border irrigation systems.

Understanding the water and carbon cycles within terrestrial ecosystems is crucial for effective monitoring and management of regional water resources and the ecological environment. However, physical models like the SEB- and LUE-based ones can be complex and demand extensive input data. In our study, we leveraged multiple variables (vegetation growth, surface moisture, radiative energy, and other relative variables) as inputs for various regression algorithms, including Multiple Linear Regression (MLR), Random Forest Regression (RFR), and Backpropagation Neural Network (BPNN), to estimate water (ET) and carbon fluxes (NEE) in the Haihe River Basin, and compared the estimated results with the observations from six eddy covariance flux towers. We aimed to (1) assess the impacts of different input variables on the accuracy of ET and NEE estimations, (2) compare the accuracy of the three regression methods, including three machine learning algorithms and Multiple Linear Regression, and (3) evaluate the performance of ET and NEE estimation models across various regions. The key findings include: (1) Increasing the number of input variables typically improved the accuracy of ET and NEE estimations. (2) RFR proved to be the most accurate for both ET and NEE estimations among the three regression algorithms. Of these, the four types of variables used together with RFR resulted in the best accuracy for ET (R2 of 0.81 and an RMSE of 1.13 mm) and NEE (R2 of 0.83 and an RMSE of 2.83 gC/m2) estimations. (3) Vegetation growth variables (i.e., VIs) are the most important inputs for ET and NEE estimation. (4) The proposed ET and NEE estimation models exhibited some variation in accuracy across different validation sites. Despite these variations, the accuracy levels across all six validation sites remained relatively high. Overall, this study lays the groundwork for an efficient approach to agricultural water resources and ecosystem monitoring and management.

The mechanisms of the exposure to fine particulate matter (PM) as a risk factor for pulmonary injury are not fully understood. The transcription factor, NF-E2-related factor 2 (Nrf2), plays a key role in protection lung against PM insult and cancer chemoprevention. In this study, F3-S fly ash particles from a municipal waste incinerator were evaluated as a PM model. We found that F3-S triggered hierarchical oxidative stress responses involving the prolonged activation of the cytoprotective Nrf2 transcriptional program via Keap1 Cys151 modification, and c-Jun NH2-terminal kinase (JNK) phosphorylation at higher doses. In mouse lungs exposed to fly ash particles at a low dose (10–20 mg/kg), Nrf2 signalling was upregulated, while in those exposed to a high fly ash particle dose (40 mg/kg), there was significant activation of JNK, and this correlated with Nrf2 phosphorylation and the downregulation of antioxidant response element (ARE)-driven genes. The JNK inhibitor, SP600125, reversed Nrf2 phosphorylation, and downregulation of detoxifying enzymes. Silencing JNK expression in mouse lungs using adenoviral shRNA inhibited JNK activation and Nrf2 phosphorylation, promoted ARE-driven gene expression, and reduced pulmonary injury. Furthermore, we found that the 452–515 amino acid region within the Neh1 domain of Nrf2 was required for its interaction with P-JNK. We demonstrated that Nrf2 was an important P-JNK target in fly ash-induced pulmonary toxicity. JNK phosphorylated Nrf2, leading to a dysfunction of the Nrf2-mediated defence system.

Effective estimation of crop yields at a regional scale holds significant importance in facilitating decision-making within the agricultural sector, thereby ensuring grain security. However, traditional ground-based measurement techniques suffer from inefficiencies, and there exists a need for a reliable, precise, and effective method for estimating regional rice yields. In this study, we employed four machine-learning techniques: partial least squares regression (PLSR), support vector regression (SVR), random forest regression (RFR), and back propagation neural network (BPNN). We combined these methods with multi-temporal rice NDVI (normalized difference vegetation index) data for rice yield estimation. Following an accuracy evaluation and a spatial analysis, the key findings of our study are as follows. (1) The RFR model emerged as the most accurate for rice yield estimation, achieving an R2 of 0.65, an RMSE of 388.79 kg/ha, and an rRMSE of 4.48%. While PLSR and SVR demonstrated comparable accuracy, they were both inferior to RFR. (2) Using the top seven predictors with the highest importance rankings as inputs for the RFR model (NDVI values on the 6th, 17th, 33rd, 44th, 71st, 90th, and 106th days after the rice transplanting stage) achieved comparable accuracy while reducing information redundancy. (3) The proposed model demonstrated good spatial applicability (MI = −0.03) for rice yield estimation in Jiangsu, China. (4) A high spatial resolution yearly rice yield dataset (1 km) spanning from 2001 to 2020 was generated using the proposed model and is accessible on the Zenodo database. In conclusion, this study has demonstrated the efficacy of combining multi-temporal remote sensing data with machine-learning techniques for accurate rice yield estimation, thereby aiding agricultural authorities and production enterprises in the timely formulation and refinement of cropping strategies and management policies for the ongoing season.

Measurement(s) crop yield and crop water productivity Technology Type(s) remote sensing and machine learning

This paper presents the first universal cloud-based database of recycled aggregate concrete (RAC) durability, named RACBase. The database collects experimental data on the durability of RAC from published literature all over the globe. Each set of data consists of the literature source, materials information, and the unified test result. The resistance to chloride ion attack, carbonation, sulfate attack, and freeze-thaw for RAC is quantified by the passed electric charge, carbonation depth, compressive strength loss, and durability factor, respectively. Based on the web interface, RACBase provides the functions of searching, adding, acquiring, and storing data, and gives the statistical distribution of data for each durability test. Users can freely access RACBase at https://www.racbase.com and browse and upload their data after online registration. One illustration of building a machine learning model for predicting the chloride resistance of RAC is presented to show the potential application of the database. The extreme gradient boosting model shows superiority to the artificial neural network and random forest models with the R2 of 0.975, RMSE of 246.719, and MAPE of 0.081. RACBase enriches the way for users to conduct in-depth research on the durability of RAC and construct performance prediction models.

The near-infrared (NIR) image obtained by an NIR camera is a grayscale image that is inconsistent with the human visual spectrum. It can be difficult to perceive the details of a scene from an NIR scene; thus, a method is required to convert them to visible images, providing color and texture information. In addition, a camera produces so much video data that it increases the pressure on the cloud server. Image processing can be done on an edge device, but the computing resources of edge devices are limited, and their power consumption constraints need to be considered. Graphics Processing Unit (GPU)-based NVIDIA Jetson embedded systems offer a considerable advantage over Central Processing Unit (CPU)-based embedded devices in inference speed. For this study, we designed an evaluation system that uses image quality, resource occupancy, and energy consumption metrics to verify the performance of different NIR image colorization methods on low-power NVIDIA Jetson embedded systems for practical applications. The performance of 11 image colorization methods on NIR image datasets was tested on three different configurations of NVIDIA Jetson boards. The experimental results indicate that the Pix2Pix method performs best, with a rate of 27 frames per second on the Jetson Xavier NX. This performance is sufficient to meet the requirements of real-time NIR image colorization.

To study the effects of straw return and aeration of the water layer on oxygen and redox status in the water column and at different depths in paddy field soil, a short-term incubation experiment was conducted with four treatments: (1) no straw return (NS); (2) straw return without aeration (S); (3) straw return and 30 minutes of aeration per day (SO30); and (4) straw return and 90 minutes of aeration per day (SO90). Compared to NS, S decreased dissolved oxygen (DO) and redox potential (ORP) by 23-58% and 47-53 mV, respectively, and increased active reducing substance (ARS) by 21-46% in the water and soil layers. The aeration treatments increased DO and ORP by 25-120% and 11-86 mV, respectively, and reduced ARS by 5-16% compared to S. The results indicated that straw return to paddy fields exacerbated hypoxia and reducing conditions in the soil. SO90 achieved better effects than SO30 in alleviating the negative impact of straw return by supplying more oxygen, but the effects weakened over time and with soil depth.

The Volume of Fluid (VOF) method is used in two-phase fluid flow problems of ship hydrodynamic calculations, to capture the motion and distribution of the gas–liquid free surface. To ensure solution stability and accuracy, numerical simulations typically require separate mesh refinement for the free surface or a reduced time step, resulting in a significant increase in solution time. This study aims to compare the drag and vessel attitude change calculations of the VOF implicit multi-step method with the traditional single-step method, and to verify the feasibility of the method in the numerical prediction of ship resistance and flow field analysis. The results show that an implicit multi-step method with a reasonable number of internal iterations could obtain results close to those of the single-step method with a reduced time step, and the error in trim angle was relatively large, about 2%, but the solving time was only about half that of the latter. The method could also capture the shape and location of waves on the hull, especially in the vicinity of the ship, while the distribution of the waves in the far field differed from those in the experiments to some extent.

Shortages of water resources and labor make it urgent to improve irrigation efficiency and automation. To respond to this need, this study demonstrates the development of an adaptive border irrigation system. The inflow is adjusted based on the functional relationship between the advance time deviation and the optimal adjustment inflow rate, thereby avoiding the real-time calculation of infiltration parameters required by traditional real-time control irrigation systems. During the irrigation process, the inflow rate is automatically adjusted based only on the advance time deviation of the observation points. The proposed system greatly simplifies the calculation and reduces the requirements for field computing equipment compared with traditional real-time control irrigation systems. Field validation experiments show that the proposed system provides high-quality irrigation by improving the application efficiency, distribution uniformity, and comprehensive irrigation performance by 11.3%, 10.7%, and 11.0%, respectively. A sensitivity analysis indicates that the proposed system maintains a satisfactory irrigation performance for all scenarios of variations in natural parameters, flow rates, and border length. Due to its satisfactory irrigation performance, robustness, facile operation, and economical merit compared with traditional real-time control irrigation systems, the proposed system has the potential to be widely applied.

BackgroundGastric cancer (GC) is one of the most common cancer types, especially in Asian countries. Hyperthermic intraperitoneal chemotherapy (HIPEC) has been shown to improve the progression-free survival among gastric cancer patients with peritoneal metastases; however, not all patients demonstrate response to HIPEC.MethodsBiomarkers are needed to select patients for effective treatment of HIPEC. Here, we performed whole-exome sequencing on tumor samples from 18 gastric cancer patients who received HIPEC treatment and assessed the association between genomic mutation features and progression-free survival. Exome sequencing was further conducted on tumor samples from additional 15 gastric cancer patients as a replication study.ResultsThe tumor mutational burden (TMB) was significantly higher in the group of patients with a better response to HIPEC treatment than that of the others. Kaplan–Meier survival curve showed that patients with high TMB had a significantly longer survival time than that in patients with low TMB. This discovery was validated in the replication cohort. Genes bearing mutations recurrently and selectively in patients with better response to HIPEC were found in the two cohorts.ConclusionWe found that higher TMB is significantly associated with better response to HIPEC. Our results provide useful hints for prognostic stratification of HIPEC treatment.

Soil compaction was largely studied in different scenarios with laboratory and field scale experiments, with various soil conditions and traffic intensities. However, a detailed analysis to better understand the protective role of plant residues or cover crop mulch is still required. A field test was conducted in Northeast Italy aiming to fill this gap. Rye was chosen as a winter cover crop, and growth on a controlled traffic random block experimental field. Four different cover crop mulch treatments were compared to study the effects of root systems: roller crimper, flail mower, bare soil control and harvested biomass control. Four different traffic intensities were used to evaluate the multiple passages with 0, 1, 3, 5 traffic events. During traffic events, the mean normal stress was measured. Penetration resistance was then evaluated after trafficking and soil samples were collected. The obtained results showed a 19.3% cone index increase in bare soil compared to flail mower treatment after the first traffic event, while low differences were found in harvested biomass bulk density during the first and third traffic events. Moreover, mean normal stress increased 16.5% on harvested biomass treatment compared to the flail mower. These findings highlight that the cover crop maintains a lower soil penetration resistance during compaction events, helping the subsequent field operations. Furthermore, roller crimper and flail mower cover crop termination impact soil bearing capacity differently due to different soil moisture content. However, the results showed a low contribution of cover crop mulch on mitigating soil compaction effects during the experiment.

Tris(1,3-dichloro-2-propyl) phosphate (TDCPP) is an organophosphorus flame retardant that has been utilized in recent years as a primary replacement for polybrominated diphenyl ethers (PBDEs) in a wide variety of fire-sensitive applications. However, the impact of TDCPP on the immune system has not been fully determined. As the largest secondary immune organ in the body, the spleen is considered to be an important study endpoint for determining immune defects in the body. The aim of this study is to investigate the effect of TDCPP toxicity on the spleen and its possible molecular mechanisms. In this study, for 28 consecutive days, TDCPP was administered intragastrically (i.g), and we assessed the general condition of mice by evaluating their 24 h water and food intake. Pathological changes in spleen tissues were also evaluated at the end of the 28-day exposure. To measure the TDCPP-induced inflammatory response in the spleen and its consequences, the expression of the critical players in the NF-κB pathway and mitochondrial apoptosis were detected. Lastly, RNA-seq was performed to identify the crucial signaling pathways of TDCPP-induced splenic injury. The results showed that TDCPP intragastric exposure triggered an inflammatory response in the spleen, likely through activating the NF-κB/IFN-γ/TNF-α/IL-1β pathway. TDCPP also led to mitochondrial-related apoptosis in the spleen. Further RNA-seq analysis suggested that the TDCPP-mediated immunosuppressive effect is associated with the inhibition of chemokines and the expression of their receptor genes in the cytokine–cytokine receptor interaction pathway, including four genes of the CC subfamily, four genes of the CXC subfamily, and one gene of the C subfamily. Taken together, the present study identifies the sub-chronic splenic toxicity of TDCPP and provides insights on the potential mechanisms of TDCPP-induced splenic injury and immune suppression.

Gut microbes play a prominent role in many aspects of human health, as seen through the increasing number of related studies. The accumulation of intestinal-flora-related studies enables us to better understand the various relationships between human gut microbes and other factors that affect the human body. However, the existing database does not meet the requirements of scientists to browse or retrieve the latest and most comprehensive published data. Thus, a knowledge base containing data related to gut microbes with updates occurring in real time would be highly valuable. We present a knowledge base of consistently curated relationships between human gut microbes and disease. By continuously and automatically collecting papers published in mainstream journals and using deep learning and NLP methods for entity relationship identification, GDReBase has now integrated 3674 diseases, 687 microbes, 7068 relationships, and 13,553 pieces of evidence from 518,286 papers, a figure that will continue to grow. GDReBase is a convenient and comprehensive resource for gut microbiology research and can be accessed free of charge.

Goblet cell adenocarcinoma (GCA) is a rare amphicrine tumor and difficult to diagnose. GCA is traditionally found in the appendix, but extra-appendiceal GCA may be underestimated. Intestinal adenocarcinoma with signet ring cell component is also very rare, and some signet ring cell carcinomas are well cohesive, having some similar morphological features to GCAs. It is necessary to differentiate GCA from intestinal adenocarcinomas with cohesive signet ring cell component (IACSRCC). The goal of this study is to find occurrence of extra-appendiceal GCA and characterize the histological, immunohistochemical, transcriptional, and immune landscape of GCA. We collected 12 cases of GCAs and 10 IACSRCCs and reviewed the clinicopathologic characters of these cases. Immunohistochemical stains were performed with synaptophysin, chromogranin A, CD56, somatostatin receptor (SSTR) 2, and Ki-67. Whole transcriptome RNA-sequencing was performed, and data were used to analyze differential gene expression and predict immune cell infiltration levels in GCA and IACSRCC. RNA-sequencing data for colorectal adenocarcinoma were gathered from TCGA data portal. Of the 12 patients with GCA, there were 4 women and 8 men. There were three appendiceal cases and nine extra-appendiceal cases. GCAs were immunohistochemically different from IACSRCC. GCA also had different levels of B-cell and CD8+ T-cell infiltration compared to both colorectal adenocarcinoma and cohesive IACSRCCs. Differential gene expression analysis showed distinct gene expression patterns in GCA compared to colorectal adenocarcinoma, with a number of cancer-related differentially expressed genes, including upregulation of TMEM14A, GOLT1A, DSCC1, and HSD17B8, and downregulation of KCNQ1OT1 and MXRA5. GCA also had several differentially expressed genes compared to IACSRCCs, including upregulation of PRSS21, EPPIN, RPRM, TNFRSF12A, and BZRAP1, and downregulation of HIST1H2BE, TCN1, AC069363.1, RP11-538I12.2, and REG4. In summary, the number of extra-appendiceal GCA was underestimated in Chinese patients. GCA can be seen as a distinct morphological, immunohistochemical, transcriptomic, and immunological entity. The classic low-grade component of GCA and the immunoreactivity for neuroendocrine markers are the key points to diagnosing GCA.

Abstract Background Volar locked plate for distal radius fracture is one of the common procedures performed in trauma surgery. There are already some factors which can be used to predict the functional outcome after volar locked plating for distal radius fracture. However their limitations caused that the outcomes couldn’t be satisfactorily predicted. Better factors for predicting the prognosis more precisely are of great interest. The aim of this study is to introduce such a new factor. Methods A total of 56 patients suffered from unilateral distal radius fracture were managed operatively with the volar locked plate. Before operation, all CT scans of the distal radius were obtained. The ratios of soft tissue circumference to bone circumference at the watershed line in the distal radius were calculated based on the preoperative CT scans. Outcomes were evaluated after operation. The correlations between the ratio and the outcomes were analyzed using single factor linear regression analysis. Results Statistically significant linear relationships between the ratio and flexion degrees, extension degrees also patient-rated wrist evaluation (PRWE) scores were discovered. With the increase of the ratios, the flexion and extension range increased and the PRWE scores declined. Conclusions There are obvious linear relationships between the ratio and postoperative wrist flexion-extension degrees also PRWE scores when using volar locked plating for distal radius fracture. So the ratio can be used as a predictor aiding surgeons to predict the outcome.

Abstract Background Joint contracture is a fibrous disease characterized as joint capsule fibrosis that results in joint dysfunction and disability. The purpose of this study was to analyze the biological activities of chaperonin containing T-complex polypeptide (CCT) subunits and to determine the role of CCT chaperone in joint contracture in a rat model. Methods In this study, the rat model of joint contracture was established by immobilizing the rat knee for 8 weeks. Then, fibroblasts were isolated from the posterior joint capsule and were cultured for functional analysis such as qRT-PCR, Western blot, transwell assay, and collagen assay. The effect of CCT subunit was determined by employing a lentivirus containing target gene and transfecting it into fibroblasts. Results Results of qRT-PCR and Western blot showed that among all CCT subunits, CCT6b significantly decreased in the fibroblasts from contractive joints compared to cells from normal joints (p < 0.05). Overexpression of CCT6b by transfection of lentivirus containing CCT6b gene to active fibroblasts significantly inhibited fibrous marker (α-SMA, COL-1) expressions, fibroblast migration, and collagen synthesis (all p < 0.05). Moreover, fibrosis-related chaperone CCT7 expression was decreased with CCT6b overexpression (p < 0.05). Conclusion The biological activities of CCT subunits in fibroblasts from the joint contracture rat model were analyzed in this study. CCT6b significantly decreased in the active fibroblasts, and overexpression of CCT6b significantly inhibited fibroblast functions. These findings indicate that CCT6b appears to be a potential molecular biomarker and therapeutic target for the novel therapies of joint contracture.

Tractive efficiency is essential in tillage operations to optimise traction performance. In this field experiment, the tractor performance was measured under different traction resistance conditions. This study quantified the soil stress, soil bulk density, soil moisture, soil cone index, soil surface disturbance, rolling resistance and slip rate under different numbers of passes and traction conditions. The actual power used under different soil and traction conditions was collected. Fuel consumption and savings were calculated between uncompacted soil, compacted soil and the permanent traffic lane. The results show that soil stress increases in each location as traction and the number of passes increase. Soil’s physical properties increase, such as the soil bulk density, soil cone index and soil surface disturbance. Additionally, the slip rate increases with traction in each soil condition as uncompacted soil, compacted soil and the permanent traffic lane. The results show that the permanent traffic lane has a lower slip rate under different traction conditions than the uncompacted and compacted soil. Furthermore, the permanent traffic lane has less energy consumption with the same traction resistance. The permanent traffic lane saved 25.50%, 29.23% and 42.34% fuel compared to the uncompacted field in 7.85, 14.71 and 24.52 kN traction conditions, respectively. Our results confirm that dynamic factors such as traction and rolling resistance should be considered in soil compaction research rather than static weight only. In practice, the controlled traffic farming (CTF) system or driving the tractor more frequently on the permanent traffic lane should be considered to improve working efficiency and reduce energy consumption.

Inspired by the cactus in nature, a cactus-like cross-sectional structure was proposed to achieve the VIV suppression. The VIV of the elastically mounted cylinder was realized based on the ANSYS Fluent and User Defined Function (UDF). The dynamic motion of the cylinder was solved by the single-step time integration algorithms Newmark-β method. The in-house code was first validated by studying the 2DOF VIV of a circular cylinder with small mass ratio over the range U*=2~13, and the results agree well with the published literature. Then, the performance of surface bulge on VIV suppression was studied and four different coverage ratios (CR) were considered, i.e., 0%, 20%, 33%, and 40%. The VIV of a bulged cylinder can be effectively suppressed. CR20 performs the best in VIV suppression and the suppression efficiency in streamwise and transverse direction are 44.6% and 63.1%, respectively. The mechanism of surface bulge on the VIV suppression is the shift of separation point of the shear layer and vortices form between the surface bulges.

The shortage of water resources makes it urgent to increase agricultural irrigation efficiency. In response to this need, this study develops a real-time adaptive control irrigation (RACI) system for border irrigation. Avoiding the need for traditional real-time control systems to calculate soil infiltration properties in real-time, RACI adjusts the inflow rate based on the difference between the actual and expected advance time. Simulations of the collected data are used to evaluate and analyze the sensitivity of RACI to input parameters, and field experiments were carried out to further verify the irrigation performance and efficiency. The experimental results indicate that RACI delivers an average application efficiency, distribution uniformity, requirement efficiency, and deep percolation of 0.930, 0.884, 0.954, and 0.070, respectively. A sensitivity analysis of irrigation input parameters (infiltration parameter, roughness coefficient, inflow rate, and slope) shows that the irrigation performance of RACI remains satisfactory even when the parameters are varied. Given the satisfactory irrigation performance and robustness and the more facile operation than traditional real-time control systems, RACI has the potential to become widely used.

The upsizing and rapid development of container ships has resulted in many large ships launching in small slipways due to the lagging of advanced equipment. In particular, the dynamic characteristics of these large ships in the longitudinal launching operation under restricted water are yet to be studied in detail. In this study, a ship model to simulate the longitudinal launching process of an 8500 TEU container ship was created based on the URANS method. The ship resistance in calm water was determined and validated against the experimental data. The influence of the stern appendage on the ship’s resistance and the flow field around the hull, with and without the aft poppet, under various water-depth-to-draught ratios was analyzed. A comparison of the ship’s resistance between the numerical and the experimental data shows that the difference is minimal, within 1.5%. The numerical results revealed that the aft poppets change the flow pattern and effectively reduce the pressure drag in the drifting stage. The shallow water causes a restraining effect on the ship. The proposed analytical approach in the numerical analysis, considering the aft poppet and the water depth, could provide a better simulation for a large ship’s longitudinal launching operation.

BackgroundMolecular characteristics are essential for the classification and grading of gliomas. However, diagnostic classification of midline glioma is still debatable and substantial molecular and clinical heterogeneity within each subgroup suggested that they should be further stratified. Here, we studied the mutation landscape of Chinese midline glioma patients in hope to provide new insights for glioma prognosis and treatment.MethodsTissue samples from 112 midline glioma patients underwent next-generation sequencing targeting 425 cancer-relevant genes. Gene mutations and copy number variations were investigated for their somatic interactions and prognostic effect using overall survival data. Pathway-based survival analysis was performed for ten canonical oncogenic pathways.ResultsWe identified several currently established diagnostic and prognostic biomarkers of glioma, including TP53 (33%), EGFR (26%), TERT (24%), PTEN (21%), PIK3CA (14%), ATRX (14%), BRAF (13%), and IDH1/2 (6%). Among all genetic aberrations with more than 5% occurrence rate, six mutations and three copy number gains were greatly associated with poor overall survival (univariate, P < 0.1). Of these, TERT mutations (hazard ratio [HR], 3.00; 95% confidence interval [CI], 1.37–6.61; P = 0.01) and PIK3CA mutations (HR, 2.04; 95% CI, 1.08–3.84; P = 0.02) remained significant in multivariate analyses. Additionally, we have also identified a novel MCL1 amplification (found in 31% patients) as a potential independent biomarker for glioma (multivariate HR, 2.78; 95% CI, 1.53–5.08; P < 0.001), which was seldom reported in public databases. Pathway analyses revealed significantly worse prognosis with abnormal PI3K (HR, 1.81; 95% CI, 1.12–2.95; P = 0.01) and cell cycle pathways (HR, 1.97; 95% CI, 1.15–3.37; P = 0.01), both of which stayed meaningful after multivariate adjustment.ConclusionsIn this study, we discovered shorter survival in midline glioma patients with PIK3CA and TERT mutations and with abnormal PI3K and cell cycle pathways. We also revealed a novel prognostic marker, MCL1 amplification that collectively provided new insights and opportunities in understanding and treating midline gliomas.

A new reduction–diffusion method for preparing submicron-sized Sm2Fe17N3 was developed. First, submicron-sized α-Fe/Sm2O3 composite precursors with good dispersibility were prepared directly by ultrasonic spray pyrolysis and hydrogen reduction (USP-HR). Then, the precursor was successfully converted into Sm2Fe17N3 powder by Ca reduction–diffusion and nitridation. The results displayed that the precursor prepared by USP-HR was a monodisperse homogeneous composite of spherical particles of α-Fe and Sm2O3. α-Fe and Sm2O3 exist in an intercalated structure in the composite spherical particles. This creates conditions for the preparation of ultrafine Sm2Fe17N3 particles with uniform sizes and dispersity. The results show that Sm2Fe17N3 is a single-phase, composed of submicron-sized particles with no other impurity phases. The physical property measurement system shows that the coercivity of 0.616 ± 0.347 µm particles reaches 14.7 kOe.

Through a comparative analysis, we confirm that the value of the dark channel pixels of the smoke image is higher than the non-smoke image. It means that the dark channel of the smoke image has more elaborate information of the smoke, which is of great benefit to our detailed feature extraction of smoke. On this background, we propose a dual convolution network using dark channel prior for image smoke classification (DarkC-DCN) for the image smoke classification. In DarkC-DCN, basing on the AlexNet, and through continuous structural improvement and optimization, we improve a detailed CNN to extract the detailed features of dark channel images. Similarly, to extract the general features in the image, we further design another residual network based on the AlexNet, which is the main framework of the entire network. To ascertain the robustness of the network, the two channels are trained separately for various inputs. In addition, we perform feature fusion before the common fully connected layer. In the experiment, we also add some non-smoke data similar to smoke in the public smoke data set for data expansion. The experimental results indicate that the model has a good performance in general. The accuracy value reaches 98.56%.

Winter irrigation is important for wheat in meeting crop water requirements in spring, but it alters soil moisture dynamics and affects soil N2O production and emission. To assess the effects of winter irrigation on soil N2O emissions in a winter wheat field, an in situ experiment was conducted from 1 October 2019 to 1 March 2020 with one control treatment (CK) and five levels of winter irrigation quantities (irrigated to 60%, 70%, 80%, 90%, 100% of the soil water holding capacity, namely WHC60–WHC100, respectively). The results showed that winter irrigation had an impact on soil N2O emission. The emission peaks were not investigated immediately after winter irrigation, but at two days after, which were increased by 4.3–17.0 μg·m−2·h−1 under WHC60–100 treatments compared to the CK. The cumulative N2O emissions after winter irrigation from WHC60–100 were 1.1–3.9 times higher than that of CK, indicating that the cumulative N2O emission has an increase trend with the increase of soil water content regulated by irrigations. Pearson correlation analysis showed that the correlation between soil N2O flux and soil temperature were moderate with correlation coefficients of about 0.65. While the correlation between soil N2O flux and soil water content was poor during the investigate winter season with correlation coefficients ranging between 0.08 and 0.25. Future studies should focus on the general N2O emission responses to winter irrigation and environmental factors with the support of experiment data from several winter seasons.

Background/Aims: Hexavalent chromium [Cr(VI)] pollution has become a global concern for both ecosystems and human health. Our previous study revealed Cr(VI) could induce both apoptosis and autophagy in L-02 hepatocytes. Here, we sought to explore the underlying mechanism of Cr(VI)-induced autophagy and its exact role in cell death. Methods: Autophagy ultrastructure was observed under transmission electron microscope (TEM), autophagy flux was measured with double-tagged mCherry-green fluorescent protein (GFP)-microtubule-associated protein 1 light chain 3 (LC3) assay, long-lived protein degradation assay, and LC3II expression assay in the presence of lysosomal inhibitor, bafilomycin A1 (BafA1). Reactive oxygen species (ROS) level was determined using fluorescent probe dichloro-dihydrofluorescein diacetate (DCFH-DA). The expression levels of Beclin-1, LC3, p62/ SQSTM1, and AKT-mammalian target of rapamycin (mTOR) pathway-related molecules including phosphorylation (p)-AKT, AKT, p-mTOR, and mTOR were examined using real-time polymerase chain reaction (RT-PCR) and western blotting. Apoptosis was determined using Annexin V- fluorescein isothiocyanate (FITC)/propidium iodide (PI) staining. Results: Our results demonstrated Cr(VI) exposure activated autophagy in L-02 hepatocytes, as evidenced by the accumulation of autophagosomes, the increase of LC3-II and degradation of p62/ SQSTM1, and the enhanced overall degradation of proteins. We also confirmed Cr(VI)-induced LC3-II elevation mainly came from autophagy induction rather than lysosomal degradation impairment. ROS-AKT-mTOR pathway was associated with Cr(VI)-induced autophagy, and ROS scavenger N-acetylcysteine (NAC) pretreatment inhibited Cr(VI)-induced autophagy by alleviating the inhibition of the AKT-mTOR pathway. Autophagy inhibitors 3-methyladenine (3-MA) and chloroquine diphosphate (CDP) promoted Cr(VI)-induced apoptotic death. Conclusion: These findings indicated Cr(VI)-induced autophagy protected L-02 hepatocytes from apoptosis through the ROS-AKT-mTOR pathway.

Background/Aims: Previous studies have shown that oxidative damage is a main contributor to disc nucleus pulposus (NP) cell apoptosis. Aquaporin-3 (AQP-3) facilitates reactive oxygen species (ROS) scavenging and thus alleviates oxidative injury in other cells. This study aims to investigate the role and mechanism of AQP-3 in regulating NP cell apoptosis under oxidative damage. Methods: Rat NP cells were treated with H2O2 for 48 hours, while control NP cells were free of H2O2. Recombinant AQP-3 lentiviral vectors were used to investigate the effect of enhanced AQP-3 expression levels in NP cells. NP cell apoptosis was assessed by flow cytometry, caspase-3 activity, gene expression of apoptosis-related molecules (Bax, Bcl-2 and caspase-3), and protein expression of cellular apoptosis markers (cleaved PARP and cleaved caspase-3). Additionally, intracellular ROS content and activity of the p38 MAPK pathway were evaluated. Results: Compared with the control NP cells, oxidative damage in the treatment cells significantly increased cell apoptosis ratios and caspase-3 activity, upregulated gene expression of Bax and caspase-3, downregulated gene expression of Bcl-2, and increased protein expression of cleaved PARP and cleaved caspase-3, as well as increased intracellular ROS content and activity of the p38 MAPK pathway. However, AQP-3 overexpression partly alleviated cell apoptosis, decreased intracellular ROS content, and inhibited the p38 MAPK pathway in NP cells under oxidative damage. Conclusion: Oxidative damage can significantly downregulate AQP-3 expression. Enhancing AQP-3 expression in NP cells partly attenuates cellular apoptosis through regulating the p38 MAPK pathway under oxidative damage.

In order to clarify the response characteristics of tillering and nitrogen (N) uptake and utilization under micro-nano bubble aeration irrigation and nitrogen fertilizer level, the nitrogen uptake and utilization characteristics, tillering and yield of early rice under different irrigation methods and nitrogen levels were investigated. The results showed that micro-nano bubble aerated irrigation and nitrogen fertilizer have substantial influence on tillering of early rice, and the effect of N fertilizer was greater than the effect of oxygen. Nitrogen accumulation increased by 6.75-10.79% in micro-nano bubble aerated irrigation treatment compared with the conventional irrigation. The application of N in treatment of micro-nano bubble aerated irrigation and 160 kg N/ha fertilizer used (W1N1) was 90% of the treatment of micro-nano bubble aerated irrigation and 180 kg N/ha fertilizer used (W1N2), while the yield decreased by only 0.31%. The study indicated that the adoption of an appropriate deficit N rate combine with micro-nano bubble aerated irrigation can be an effective means to reduce non-beneficial N consumption, achieve higher crop yield and N utilization efficiency.

In this paper, the problem of estimating the spatial parameters of multiple coherently distributed linear chirp sources is considered. In the fractional Fourier domain, a novel low-complexity algorithm based on the MUSIC criterion is proposed to estimate the central angle and the extension width. For small extension width scenarios, the 2-D spatial angle search in traditional estimators for the distributed sources estimation is replaced by a two-step 1-D MUSIC search which dramatically decreases the computational complexity. In the case of chirp signals with different frequency parameters, sources can be separated, and the spatial parameters of each source can be estimated individually. When sources cannot be separated, this problem can be considered as a classical direction-of-arrival estimation of multiple signals. In addition, the central angle estimation does not require any assumption on the distribution of angular spread. Simulation results show that the proposed algorithm obtains comparable performance in the parameters estimation accuracy for small extension width scenarios with the reduced complexity compared with our previous work.

5G as an evaluative mobile communication network is expected to respond to the traffic volume explosion and the diverse demands for communication. For the deployment of 5G, there have been many researches of heterogeneous network, especially they employ for named data networking (NDN). As a future network architecture, NDN focuses on the content, where forwarding information base (FIB) performs name-based forwarding to achieve the communications. In this paper, a novel FIB named B-MaFIB is proposed to enhance the performance of NDN router that well supports heterogeneous network toward 5G, which is designed based on an improved index called a bitmap-mapping bloom filter (B-MBF). Owing to the B-MBF, the B-MaFIB can dynamically allocate memory to effectively reduce the memory consumption. The experimental results indicate that for 2 million names based on 5G, B-MaFIB: 1) only consumes memory with 112.079 MB, reaching 50% memory reduction and 2) achieves a throughput of 1.099 million searches per second, obtaining at least six times speedup over the other schemes, which provides a potential in the deployment of NDN router.

Insufficient water resources restrict wheat production in the North China Plain, so it is urgent and essential to improve the border irrigation performance and water use efficiency. This study developed a predesigned varied-discharge irrigation scheme in the closed-ended border. Field treatments, including continuous-discharge (CD), increased-discharge (ID) and decreased-discharge (DD) border irrigation tests, were conducted to evaluate the irrigation performance of the proposed varied-discharge scheme. The DD border irrigation treatment had great application efficiency (AE), distribution uniformity (DU) and requirement efficiency (RE), and its comprehensive evaluation indicator (Y) was also significantly higher than other treatments. DD treatment achieved the average AE, DU, RE and Y values of 91.4%, 95.5%, 99.5% and 95.4%, respectively. Furthermore, the hydraulic simulation model WinSRFR was used to optimize the scheme of predesigned varied-discharge border irrigation, and sensitivity analyses of infiltration parameters, roughness coefficient, slope and inflow rate were carried out. The results indicate that the predesigned varied-discharge border irrigation scheme can improve the irrigation performance, and the DD border irrigation scheme has more satisfactory robustness than that of the ID border irrigation scheme.

State-of-the-art radio frequency identification (RFID)-based indoor autonomous vehicles localization methods are mostly based on received signal strength indicator (RSSI) measurements. However, the accuracy of these methods is not high enough for real-world scenarios. To overcome this problem, a novel dual-frequency phase difference of arrival (PDOA) ranging-based indoor autonomous vehicle localization and tracking scheme was developed. Firstly, the method gets the distance between the RFID reader and the tag by dual-frequency PDOA ranging. Then, a maximum likelihood estimation and semi-definite programming (SDP)-based localization algorithm is utilized to calculate the position of the autonomous vehicles, which can mitigate the multipath ranging error and obtain a more accurate positioning result. Finally, vehicle traveling information and the position achieved by RFID localization are fused with a Kalman filter (KF). The proposed method can work in a low-density tag deployment environment. Simulation experiment results showed that the proposed vehicle localization and tracking method achieves centimeter-level mean tracking accuracy.

The relay reliability has an impact on the reliability of the entire electric vehicle system. This paper contributes to propose the improving fireworks algorithm optimizing the grey neural network model to predict the relay lifetime. This paper shows how the mutation operation and mapping operation in the fireworks algorithm are used to improve the convergence ability and running speed; the convergence performance and running speed of improved fireworks algorithm are tested with standard test function and compared with fireworks algorithm; and the grey neural network model−improved fireworks algorithm is used to predict the relay life and compared with grey model, grey neural network, and grey neural network model−fireworks algorithm. The results show that the convergence accuracy of the improved fireworks algorithm is better than the fireworks algorithm. The running time of improved fireworks algorithm is the shortest; the improved fireworks algorithm−grey neural network model has the best prediction effect and the root mean square error value is 6.75% smaller than the fireworks algorithm−grey neural network model.

Prior studies are lacking which address permutation flow shop scheduling problems and hybrid flow shop scheduling problems together to help firms find the optimized scheduling strategy. The permutation flow shop scheduling problem and hybrid flow shop scheduling problems are important production scheduling types, which widely exist in industrial production fields. This study aimed to acquire the best scheduling strategy for making production plans. An improved fireworks algorithm is proposed to minimize the makespan in the proposed strategies. The proposed improved fireworks algorithm is compared with the fireworks algorithm, and the improvement strategies include the following: (1) A nonlinear radius is introduced and the minimum explosion amplitude is checked to avoid the waste of optimal fireworks; (2) The original Gaussian mutation operator is replaced by a hybrid operator that combines Cauchy and Gaussian mutation to improve the search ability; and (3) An elite group selection strategy is adopted to reduce the computing costs. Two instances from the permutation flow shop scheduling problem and hybrid flow shop scheduling problems were used to evaluate the improved fireworks algorithm’s performance, and the computational results demonstrate the improved fireworks algorithm’s superiority.

A type of conductive graphite/cellulose composite film used for chemical vapor-sensing material was prepared at room temperature in the ionic liquid 1-butyl-3-methylimidazolium chloride ([BMIm]Cl). Graphite was pretreated with both oxidation and reduction processes. Due to the use of N,N-carbonyldiimidazole (CDI), as a covalent cross-linking agent in [BMIm]Cl, there were limited chemical bonds between the graphite and cellulose. The composite film was analyzed using Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, and X-ray photoelectron spectroscopy (XRD). When these conducting films were exposed to certain organic vapors, their electrical resistances quickly changed, showing gas sensitivity. The percolation threshold of the conducting film was about 5 wt%. The gas-sensing behavior of these films in solvent were the opposite of those gas-sensing materials based on a non-polar polymer matrix. A typical negative vapor coefficient (NVC) was observed when the film was placed in polar organic solvents such as methanol, ethanol, and acetone.

The paper presents a joint subcarrier-pair based resource allocation algorithm in order to improve the efficiency and fairness of cooperative multiuser orthogonal frequency division multiplexing (MU-OFDM) cognitive radio (CR) systems. A communication model where one source node communicates with one destination node assisted by one half-duplex decode-and-forward (DF) relay is considered in the paper. An interference-limited environment is considered, with the constraint of transmitted sum-power over all channels and aggregate average interference towards multiple primary users (PUs). The proposed resource allocation algorithm is capable of maximizing both the system transmission efficiency and fairness among secondary users (SUs). Besides, the proposed algorithm can also keep the interference introduced to the PU bands below a threshold. A proportional fairness constraint is used to assure that each SU can achieve a required data rate, with quality of service guarantees. Moreover, we extend the analysis to the scenario where each cooperative SU has no channel state information (CSI) about non-adjacent links. We analyzed the throughput and fairness tradeoff in CR system. A detailed analysis of the performance of the proposed algorithm is presented with the simulation results.

Intimate partner violence (IPV) is the most common form of violence against women worldwide. IPV during pregnancy is an important risk factor for adverse health outcomes for women and their offspring. However, the prevalence of IPV during pregnancy is not well understood in China. The objective of this study was to estimate the pooled prevalence of IPV during pregnancy in China using a systematic review and meta-analysis.Systematic literature searches were conducted in PubMed, Web of Science, CNKI, Wanfang, Weipu and CBM databases to identify relevant articles published from the inception of each database to January 31, 2016 that reported data on the prevalence of IPV during pregnancy in China. The Risk of Bias Tool for prevalence studies was used to assess the risk of bias in individual studies. Owing to significant between-study heterogeneity, a random-effects model was used to calculate the pooled prevalence and corresponding 95% confidence interval, and then univariate meta-regression analyses were performed to investigate the sources of heterogeneity. Subgroup analysis was conducted to explore the risk factors associated with IPV during pregnancy.Thirteen studies with a total of 30,665 individuals were included in this study. The overall pooled prevalence of IPV during pregnancy was 7.7% (95% CI: 5.6-10.1%) with significant heterogeneity (I2 = 97.8%, p < 0.001). The results of the univariate meta-regression analyses showed that only the variable "sample source" explained part of the heterogeneity in this study (p < 0.05). The characteristics "number of children" and "unplanned pregnancy" were determined as risk factors for experiencing violence during pregnancy.The prevalence of IPV during pregnancy in China is considerable and one of the highest reported in Asia, which suggests that issues of violence against women during pregnancy should be included in efforts to improve the health of pregnant women and their offspring. In addition, a nationwide epidemiological study is needed to confirm the prevalence estimates and identify more risk factors for IPV during pregnancy.

The second and the third sentences of the abstract are changed and the shorter abstract is given as follows. To recover the nonstationary signal in complicated noise environment without distortion, a novel general design of fractional filter is proposed and applied to eliminate the Wigner cross-term. A time-frequency binary image is obtained from the time-frequency distribution of the observed signal and the optimal separating lines are determined by the support vector machine (SVM) classifier where the image boundary extraction algorithms are used to construct the training set of SVM. After that, the parameters and transfer function of filter can be determined by the parameters of the separating lines directly in the case of linear separability or line segments after the piecewise linear fitting of the separating curves in the case of nonlinear separability. Without any prior knowledge of signal and noise, this method can meet the reliability and universality simultaneously for filter design and realize the global optimization of filter parameters by machine learning even in the case of strong coupling between signal and noise. Furthermore, it could completely eliminate the cross-term in Wigner-Ville distribution (WVD) and the time-frequency distribution we get in the end has high resolution and good readability even when autoterms and cross-terms overlap. Simulation results verified the efficiency of this method.

Bovine tuberculosis (BTB) is a significant veterinary and financial problem in many parts of the world. Associations between specific host genes and susceptibility to mycobacterial infections, such as tuberculosis, have been reported in several species. The objective of this study was to identify and evaluate the relationship of single-nucleotide polymorphisms (SNPs) in the CARD15 gene with susceptibility to BTB in Chinese Holstein cows. DNA samples from 201 Chinese Holstein cows (103 cases and 98 controls) were collected from Kunming City, Yuxi City, and Dali City in China. SNPs in the CARD15 gene were assessed using polymerase chain reaction (PCR) and restriction fragment length polymorphism-polymerase chain reaction (RFLP-PCR). Case-control association testing and statistical analysis identified six SNPs associated with susceptibility to BTB in Chinese Holstein cows. The frequency of genotypes C/T, A/G, A/G, A/G, C/T, and A/G in E4 (-37), 208, 1644, 1648, 1799, and E10 (+107), respectively, was significantly higher in cases than in controls, and also the alleles C, A, A, G, T, and A, respectively, were associated with a greater relative risk in cases than in controls. The distribution of two haplotypes, TGGACA and CAGACA, was significantly different between cases and controls. Overall, this case-control study suggested that E4 (-37)(C/T), 208(A/G), 1644(A/G), 1648(A/G), 1799(C/T), and E10 (+107)(A/G) in the CARD15 gene were significantly associated with susceptibility to BTB in Chinese Holstein cows and that haplotypes TGGACA and CAGACA could be used as genetic markers in marker-assisted breeding programs for breeding cows with high resistance to BTB.