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Background Plant architecture associated with increased grain yield and adaptation to the local environments is selected during wheat (Triticum aestivum) breeding. The internode length of individual stems and tiller length of individual plants are important for the determination of plant architecture. However, few studies have explored the genetic basis of these traits. Results Here, we conduct a genome-wide association study (GWAS) to dissect the genetic basis of geographical differentiation of these traits in 306 worldwide wheat accessions including both landraces and traditional varieties. We determine the changes of haplotypes for the associated genomic regions in frequency in 831 wheat accessions that are either introduced from other countries or developed in China from last two decades. We identify 83 loci that are associated with one trait, while the remaining 247 loci are pleiotropic. We also find 163 associated loci are under strong selective sweep. GWAS results demonstrate independent regulation of internode length of individual stems and consistent regulation of tiller length of individual plants. This makes it possible to obtain ideal haplotype combinations of the length of four internodes. We also find that the geographical distribution of the haplotypes explains the observed differences in internode length among the worldwide wheat accessions. Conclusion This study provides insights into the genetic basis of plant architecture. It will facilitate gene functional analysis and molecular design of plant architecture for breeding.

The construction of a high-quality wheat genome variation map is important to wheat genetic studies and breeding. In this study, we developed the second-generation whole-genome genetic variation map of wheat (VMap 2.0) by integrating whole-genome sequencing data of 1,062 diverse wheat accessions from 20 species/subspecies. VMap 2.0 contains 195.96 million single nucleotide polymorphisms (SNPs), 2.22 million insertions, and 4.72 million deletions, achieving a high density of variation map in which one variant exists in every 73 base pairs on average. By systematically analyzing the phylogenetic relationships and genetic diversity of tetraploid wheat, hexaploid wheat, and diploid goatgrass (Aegilops tauschii), we found that the genetic diversity of wild emmer wheat was 2.4 times higher than that of common wheat. In contrast, the genetic diversity of diploid goatgrass is 7.8 times higher than the D subgenome of hexaploid wheat. With the high-density genetic variations, VMap 2.0 is anticipated to facilitate high-resolution trait dissection and expedite prediction-based breeding of wheat.

Aberrant post-translational modification (PTM) is a key molecular event inciting p53 tumor suppressor function loss or transformation. Here, we report that p53 acetylation, independent of the overall level of p53 expression, predicts improved survival in glioblastoma (GBM). It revealed that acetylation at the C-terminal domain (CTD) reversed tumorigenic gain of function (GOF) of p53 mutants in GBM. An important finding was that acetylation not only strengthened the tumor suppression of wild-type p53, but also reinforced the chemosensitivity of GBM cells with missense mutant p53, as evidenced by attenuated DNA damage repair. Mechanical exploration revealed that the acetylation of p53 in GBM was negatively regulated by Smad1. Smad1 served as an oncoprotein in GBM by promoting tumorigenesis and chemoresistance in a BMP or TGF-β independent manner. It formed a ternary complex with p53 through the MH1 domain and with p300 through the MH2 domain, inhibiting p300-mediated p53 acetylation via competitively binding of the C-terminus of p300. Acetylated Smad1 was identified by p300 at the lysine site 373 (K373). Smad1 acetylation was indispensable due to its transcriptional activity and onco-functions. Collectively, this study highlights that acetylation is critical for p53 and Smad1 functions, and that Smad1 acts as an oncoprotein partially by impairing p53 acetylation in GBM.

Bread wheat expanded its habitat from a core area of the Fertile Crescent to global environments within ~10,000 years. The genetic mechanisms of this remarkable evolutionary success are not well understood. By whole-genome sequencing of populations from 25 subspecies within the genera Triticum and Aegilops, we identified composite introgression from wild populations contributing to a substantial portion (4-32%) of the bread wheat genome, which increased the genetic diversity of bread wheat and allowed its divergent adaptation. Meanwhile, convergent adaptation to human selection showed 2- to 16-fold enrichment relative to random expectation-a certain set of genes were repeatedly selected in Triticum species despite their drastic differences in ploidy levels and growing zones, indicating the important role of evolutionary constraints in shaping the adaptive landscape of bread wheat. These results showed the genetic necessities of wheat as a global crop and provided new perspectives on transferring adaptive success across species for crop improvement.

Intestinal epithelial dysfunction is the foundation of various intestinal and extra-intestinal diseases, while the effects and mechanism of uric acid on the intestinal barrier are little known. TSPO has been shown to be related to the generation of ROS and is involved in regulating inflammation, whether uric acid drives intestinal epithelial dysfunction through TSPO-mediated NLRP3 inflammasome activation is unknown. UOX gene knockout mouse (UOX-/-) were used for models of hyperuricemia. Fluorescein isothiocyanate (FITC)-labeled dextran was used to assess in vivo intestinal permeability. Serum lipopolysaccharide (LPS) and culture supernatants IL-1β were measured using ELISA Kit. IEC-6 exposed to different concentrations of uric acid was used for in vitro experiment. Protein content and mRNA were assessed using Western blotting and Q-PCR, respectively. Intracellular ROS was determined using flow cytometry and fluorescence microscope. Mitochondrial membrane potential was detected on an immunofluorescence. Small interfering RNA transfection was used to assess the interaction between translocator protein (TSPO) and NLRP3 inflammasome. N-acetyl-L-cysteine (NAC) was used as ROS scavenger. Our results showed that hyperuricemia mice were characteristic by increased intestinal permeability. Hyperuricemia upregulated TSPO, increased production of ROS and activated NLRP3 inflammasome, which resulted in lower expression of occludin and claudin-1. In vitro, we showed that soluble uric acid alone increased the expression of TSPO, depolarized mitochondrial membrane potential, increased ROS release and activated NLRP3 inflammasome, which further reduced the expression of occludin and claudin-1. Silencing TSPO suppressed NLRP3 inflammasome activation and increased expression of claudin-1 and occludin, which was accompanied by lower levels of ROS. Scavenging ROS also significantly inhibited NLRP3 inflammasome activation without change of TSPO, indicating that TSPO-mediated NLRP3 inflammasome activation was dependent on ROS. In conclusion, uric acid drives intestinal barrier dysfunction through TSPO-mediated NLRP3 inflammasome.

This paper studies the distributed dimensionality reduction fusion estimation problem for cyber-physical systems with limited bandwidth in presence of eavesdroppers. Since wireless communication is implemented by broadcasting, the eavesdroppers can collude to collect the data through anther communication networks. To protect data privacy, based on the physical processes and local estimation error covariance (EEC) matrix, an insertion method of artificial noise (AN) is developed such that only eavesdroppers’ fusion EEC becomes worse. Meanwhile, the fusion center needs to decode the received signal due to the noise interference, while the successful decoding probability varies with signal to noise ratio. Subsequently, some criteria for the selection probabilities and the successful decoding probabilities are given to guarantee the effectiveness of the AN insertion strategy. Moreover, a sufficient condition of the designed AN power is derived to guarantee the confidentiality. Simulation examples are given to show the effectiveness of the proposed methods.

Deep knowledge of crop biodiversity is essential to improve global food security. Despite bread wheat serving as a keystone crop worldwide, the population history of bread wheat and its wild relatives (a.k.a. wheats) remains elusive. By analyzing whole-genome sequences of 795 wheats, we found that bread wheat originated southwest of the Caspian Sea ∼11,700 years ago and underwent a slow speciation process, lasting ∼3,300 years due to persistent gene flow from wild relatives. Soon after, bread wheat spread across Eurasia and reached Europe, South Asia, and East Asia ∼7,000 to ∼5,000 years ago, shaping a diversified but occasionally convergent adaptive landscape of bread wheat in novel environments. Opposite to cultivated wheat, wild wheat populations have declined by ∼82% in the past ∼2,000 years due to the food choice shift of humans, and likely continue to drop because of the changing climate. These findings will guide future efforts in protecting and utilizing wheat biodiversity to improve global food security.

The molecular mechanism underlying hyperuricemia-induced lipid metabolism disorders is not clear. The purpose of the current study was to investigate the mechanism of lipid disturbances in a hyperuricemia mice model. RNA-Seq showed that differentially expressed genes (DEGs) in the fatty acid synthesis signaling pathway were mainly enriched and CXCL-13 was significantly enriched in protein-protein interaction networks. Western blotting, Q-PCR, and immunofluorescence results further showed that hyperuricemia upregulated CXCL-13 and disturbed lipid metabolism in vivo and in vitro. Furthermore, CXCL-13 alone also promoted the accumulation of lipid droplets and upregulated the expression of FAS and SREBP1, blocking AMPK signaling and activating the PKC and P38 signaling pathways. Silencing CXCL-13 reversed uric-acid-induced lipid droplet accumulation, which further downregulated FAS and SREBP1 expression, inhibited the p38 and PKC signaling, and activated AMPK signaling. In conclusion, hyperuricemia induces lipid metabolism disorders via the CXCL-13 pathway, making CXCL-13 a key regulatory factor linking hyperuricemia and lipid metabolism disorders. These results may provide novel insights for the treatment of hyperuricemia.

BackgroundStructural variations (SVs) pervade the genome and contribute substantially to the phenotypic diversity of species. However, most SVs were ineffectively assayed because of the complexity of plant genomes and the limitations of sequencing technologies. Recent advancement of third-generation sequencing technologies, particularly the PacBio high-fidelity (HiFi) sequencing, which generates both long and highly accurate reads, offers an unprecedented opportunity to characterize SVs and reveal their functionality. Since HiFi sequencing is new, it is crucial to evaluate HiFi reads in SV detection before applying the technology at scale.ResultsWe sequenced wheat genomes using HiFi, then conducted a comprehensive evaluation of SV detection using mainstream long-read aligners and SV callers. The results showed the accuracy of SV discovery depends more on aligners rather than callers. For aligners, pbmm2 and NGMLR provided the most accurate results while detecting deletion and insertion, respectively. Likewise, cuteSV and SVIM achieved the best performance across all SV callers. We demonstrated that the combination of the aligners and callers mentioned above is optimal for SV detection. Furthermore, we evaluated the impact of sequencing depth on the accuracy of SV detection. The results showed that low-coverage HiFi sequencing is capable of generating high-quality SV genotyping.ConclusionsThis study provides a robust benchmark of SV discovery with HiFi reads, showing the remarkable potential of long-read sequencing to investigate structural variations in plant genomes. The high accuracy SV discovery from low-coverage HiFi sequencing indicates that skim HiFi sequencing is an ideal approach to study structural variations at the population level.

Glioblastoma (GBM) is the most common and aggressive brain tumor in adults, characterized by diffuse infiltration, dysplasia, and resistance to therapy. Metabolic remodeling and immunosuppression are typical events which contribute to GBM progression, but the molecular link between these two events remains largely undetermined. Studies have shown that high levels of transforming growth factor-β (TGF-β) and its receptors are associated with glioma malignancy and a poor prognosis. TGF-β plays an important role in cell metabolism and immunity. During tumorigenesis, TGF-β induces a shift in cell metabolism from oxidative phosphorylation to aerobic glycolysis, providing a favorable environment for tumor growth. Locally, TGF-β creates an immunosuppressive microenvironment and promotes the malignant phenotype of GBM. In this review, we aim to link GBM aerobic glycolysis and immunosuppression through TGF-β to provide new ideas for the study of GBM.

The stems of cereal crops provide both mechanical support for lodging resistance and a nutrient supply for reproductive organs. Elongation, which is considered a critical phase for yield determination in winter wheat (Triticum aestivum L.), begins from the first node detectable to anthesis. Previously, we characterized a heavy ion beam triggered wheat mutant qd, which exhibited an altered stem elongation pattern without affecting mature plant height. In this study, we further analyzed mutant stem developmental characteristics by using transcriptome data. More than 40.87 Mb of clean reads including at least 36.61 Mb of unique mapped reads were obtained for each biological sample in this project. We utilized our transcriptome data to identify 124,971 genes. Among these genes, 4,340 differentially expressed genes (DEG) were identified between the qd and wild-type (WT) plants. Compared to their WT counterparts, qd plants expressed 2,462 DEGs with downregulated expression levels and 1878 DEGs with upregulated expression levels. Using DEXSeq, we identified 2,391 counting bins corresponding to 1,148 genes, and 289 of them were also found in the DEG analysis, demonstrating differences between qd and WT. The 5,199 differentially expressed genes between qd and WT were employed for GO and KEGG analyses. Biological processes, including protein-DNA complex subunit organization, protein-DNA complex assembly, nucleosome organization, nucleosome assembly, and chromatin assembly, were significantly enriched by GO analysis. However, only benzoxazinoid biosynthesis pathway-associated genes were enriched by KEGG analysis. Genes encoding the benzoxazinoid biosynthesis enzymes Bx1, Bx3, Bx4, Bx5, and Bx8_9 were confirmed to be differentially expressed between qd and WT. Our results suggest that benzoxazinoids could play critical roles in regulating the stem elongation phenotype of qd.

Vehicle state, including location and motion information, plays an essential role on the Internet of Vehicles (IoV). Accurately obtaining the system state information is the premise of realizing precise control. However, the statistics of system process noise are often unknown due to the complex physical process. It is challenging to estimate the system state when the process noise statistics are unknown. This paper proposes a new adaptive high-degree unscented Kalman filter based on the improved Sage–Husa algorithm. First, the traditional Sage–Husa algorithm is improved using a high-degree unscented transform. A noise estimator suitable for the high-degree unscented Kalman filter is obtained to estimate the statistics of the unknown process noise. Then, an adaptive high-degree unscented Kalman filter is designed to improve the accuracy and stability of the state estimation system. Finally, the target tracking simulation results verify the proposed algorithm’s effectiveness.

Intestinal epithelial dysfunction is the foundation of various intestinal and extra-intestinal diseases, while the effects and mechanism of uric acid on the intestinal barrier are little known. TSPO has been shown to be related to the generation of ROS and is involved in regulating inflammation, whether uric acid drives intestinal epithelial dysfunction through TSPO-mediated NLRP3 inflammasome activation is unknown.UOX gene knockout mouse (UOX-/-) were used for models of hyperuricemia. Fluorescein isothiocyanate (FITC)-labeled dextran was used to assess in vivo intestinal permeability. Serum lipopolysaccharide (LPS) and culture supernatants IL-1β were measured using ELISA Kit. IEC-6 exposed to different concentrations of uric acid was used for in vitro experiment. Protein content and mRNA were assessed using Western blotting and Q-PCR, respectively. Intracellular ROS was determined using flow cytometry and fluorescence microscope. Mitochondrial membrane potential was detected on an immunofluorescence. Small interfering RNA transfection was used to assess the interaction between translocator protein (TSPO) and NLRP3 inflammasome. N-acetyl-L-cysteine (NAC) was used as ROS scavenger.Our results showed that hyperuricemia mice were characteristic by increased intestinal permeability. Hyperuricemia upregulated TSPO, increased production of ROS and activated NLRP3 inflammasome, which resulted in lower expression of occludin and claudin-1. In vitro, we showed that soluble uric acid alone increased the expression of TSPO, depolarized mitochondrial membrane potential, increased ROS release and activated NLRP3 inflammasome, which further reduced the expression of occludin and claudin-1. Silencing TSPO suppressed NLRP3 inflammasome activation and increased expression of claudin-1 and occludin, which was accompanied by lower levels of ROS. Scavenging ROS also significantly inhibited NLRP3 inflammasome activation without change of TSPO, indicating that TSPO-mediated NLRP3 inflammasome activation was dependent on ROS.In conclusion, uric acid drives intestinal barrier dysfunction through TSPO-mediated NLRP3 inflammasome.

This paper is concerned with remote state estimation problem with bandwidth and energy constrained wireless sensor networks(WSNs). To improve the estimation quality under these constrains in addressed system, measurement quantization and event-triggered communication strategies are adopted in WSN. Specifically, quantization strategy and event-triggering mechanism are introduced to describe the set region of original measurements, and a closest ellipsoid approximation of measurement sets method is presented. Subsequently, set-valued Kalman filter based on quantization and event is designed by utilizing the quantizer and trigger information. Finally, an illustrative example is employed to demonstrate the advantages and effectiveness of the proposed methods.

In this work, we study finite-horizon multiple-sensor scheduling for general scalar Gauss-Markov systems, extending previous results where only a class of systems are considered. The scheduling objective is to minimize the terminal estimation error covariance. Only one sensor can transmit its measurement per time instant and each sensor has limited energy. Through building a comparison function and solving its monotone intervals, an efficient algorithm is designed to construct the optimal schedule.

A filter based on characteristic functions is developed in this paper, to fit to a class of non-Gaussian dynamical systems, which state models and measurement models are all nonlinear and multi-dimensional. The new filter overcomes limitations and expands the application of this kind of filter, which is proved to just fit to one special kind of systems with multi-dimensional linear state models and one-dimensional nonlinear measurement models. Firstly, the filter using characteristic function is introduced and its limitation is analysed. Then, we design the new filter to fit to nonlinear states and multi-dimensional measurements. Thirdly, the matrix format of performance index is presented to match to the new filter gain, and the weighting function vector is given to ensure the uniform boundedness of such a performance index. Finally, the new filter gain can be obtained by minimizing this performance index, and the process of filtering design is accomplished. Simulation examples are given to illustrate the effectiveness of the proposed filter design scheme.

This paper designs a novel filter based on characteristic function for multidimensional observation systems, essentially extending the proposed filter, which just fitted to one-dimensional observations. For the dynamic model from grinding process cylindrical workpieces, this filter could result in enhanced and incremental productivity and quality control in manufacturing processes. In the processing of the filter design, a new form of filter will be given to adapt to the multidimensional observations, the matrix format of performance index will be designed to fit to matrix format of filter gain, the selecting range of the weighting function vector will be given to ensure the uniform boundedness of the designed performance index, and the filter gain can be obtained by minimizing the performance index. Finally, we illustrate the effectiveness of the proposed method by simulation examples in the field of the target tracking and the grinding process cylindrical workpieces.

Neural network is an important tool to solve the problem of nonlinear system prediction and control. It has been widely concerned by scholars. However, the existing neural network cannot adaptively allocate the weight of mixed kernel function according to the sample characteristics when it is applied to electric load forecasting. Aiming at this problem, short-term load forecasting algorithm based on adaptive fusion of mixed kernel function is proposed. Firstly, kernel functions are selected from the standard local kernel function and the global kernel function library to form a mixed kernel function. The weight variables and parameters of the kernel function are combined to form a new parameter state vector. Then a nonlinear parameter estimation model is established. Based on this model, the high-order cubature Kalman filter is used to estimate the parameter state, so that the local kernel function and the global kernel function can be adaptively fused. Moreover, the trained neural network is used to predict the load. Finally, the experimental analysis is given based on the actual grid data, and the effectiveness of the adaptive fusion of mixed function algorithm is proved.

Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. The gut microbiota has been demonstrated to play significant roles in the immunity and metabolism of the host. In the present study, we constructed a hyperuricemic mouse model to investigate whether the metabolic disorder caused by hyperuricemia is related to intestinal dysbiosis. A significantly increased intestinal permeability was detected in hyperuricemic mice. The difference in microflora between wild-type and hyperuricemic mice accompanies the translocation of gut microbiota to the extraintestinal tissues. Such a process is followed by an increase in innate immune system activation. We observed increased LPS and TNF-α levels in the hyperuricemic mice, indicating that hyperuricemic mice were in a state of low-grade systemic inflammation. In addition, hyperuricemic mice presented early injury of parenteral tissue and disordered lipid metabolism. These findings suggest that intestinal dysbiosis due to an impaired intestinal barrier may be the key cause of metabolic disorders in hyperuricemic mice. Our findings should aid in paving a new way of preventing and treating hyperuricemia and its complications. NEW & NOTEWORTHY Hyperuricemia is associated with many metabolic diseases. However, the underlying mechanism remains unknown. We constructed a hyperuricemic mouse model to explore the relationship between intestinal dysbiosis and metabolic disorder caused by hyperuricemia.

Cell adhesion was the first step of bone reconstruction. While hydroxyapatite (HA)/graphene composites had been utilized for improving the cell adhesion and bone osteogenesis, the impact of cell adhesion and HA/graphene composites, especially HA/hydrophilic graphene (HG) composites, on internal interaction force and external surface properties remained poorly understood. Here, higher stability HA/HG composites were synthesized without extra ion introduction with in situ self-assembling method. And with XRD, FT-IR, XPS and Raman analyses, the evidences of the formation of HA and the introduction of HG was clear. TEM and SEM images showed the net-like spatial structure due to the internal interaction force between HA and HG, which provided the strain stimulation for cell adhesion. Subsequently, the external surface properties of HA/HG composites demonstrated that the roughness and hydrophilic ability of HA/HG composites could be artificially regulated by increasing the content of HG. Besides, the cell proliferation rate of HA/HG composites had been investigated. Compared to the intrinsic HA, HA/5%HG possessed the higher cell proliferation rate (264.81%) and promoted the spreading and growth of MC3T3-E1 cells. Finally, the regulation mechanism between HA/HG and cell adhesion were illuminated in detail. The excellent regular behavior of HA/HG composites for cell adhesion made them promising candidates for bone reconstruction and repairing. The present work provided the reference for the design of modifiable biomaterials and offered much inspiration for the future research of bone reconstruction engineering.

This paper studies distributed secure fusion estimation problem in presence of eavesdroppers, where an eavesdropper can collect the messages from sensors to the fusion center through communication networks. To prevent eavesdropping, an insertion method of artificial noises is developed based on the fusion estimation error covariance matrix such that: i) The local/fusion estimation error covariance of the eavesdropper is unbounded; ii) The fusion estimation error covariance of the defender is bounded. Moreover, a sufficient condition is derived to guarantee the effective noise insertion strategy. Simulations are given to show the effectiveness of the proposed methods.

This paper considers optimal control data scheduling for finite-horizon linear quadratic regulation (LQR) control of scalar systems with limited controller-plant communication. Both the single-system and multiple-system scenarios are studied. For the first scenario, we derive the necessary and sufficient condition for a comparison function to be positive. Using this condition, the optimality of an explicit schedule is extended from unstable systems in the existing work to general systems. For the second scenario, we are able to construct explicit optimal scheduling policies for three particular classes of problems. Numerical examples are provided to illustrate the proposed results.

Data fusion for nonlinear systems is one of the challenging topics in state estimation and target tracking recently. We study decentralized cubature Kalman fusion in this paper. Cubature Kalman filter (CKF) is a more effective method than the conventional nonlinear filters, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). For most of the practical cases, there are correlative between process and measurement noises (Correlation I) and among measurement noises (Correlation II). So, it is more attractive to design fusion algorithms based on the CKF for the systems with complex correlated noises. Firstly, a cubature Kalman filter with correlation I (CKF-CN) is derived. Secondly, by introducing the EKF with correlated noises (EKF-CN) and its information filter EIF-CN, the CKF-CN is embedded in the EIF-CN framework to get a cubature information filter with correlated noises (CIF-CN). Consequently, a square-root cubature Kalman filter with noise correlation I (SCKF-CN) and the associated information filter SCIF-CN are presented to improve computational performance. Finally, based on the proposed SCIF-CN and matrix diagonalization, a decentralized nonlinear fusion algorithm is proposed for the multisensor system with Correlation I and Correlation II. Simulation examples are demonstrated to validate the proposed filters and fusion algorithms.

In this work, we study finite-horizon multiple-sensor scheduling for general scalar Gauss-Markov systems, extending previous results where only a class of systems are considered. The scheduling objective is to minimize the terminal estimation error covariance. Only one sensor can transmit its measurement per time instant and each sensor has limited energy. Through building a comparison function and solving its monotone intervals, an efficient algorithm is designed to construct the optimal schedule.

Wireless sensor networks (WSNs) fusion systems are usually faced with the communication bandwidth constraints, so it is necessary to adopt quantization. The existing quantization is usually under the assumption of known distribution function of data. However, obtaining the accurate distribution function of data is impossible. Therefore, in this paper, based on the obtained measurements, a kind of non-uniform quantization strategy under the principle of least square sum of quantization error is proposed firstly. Then, the solving method of non-uniform quantizing points based on adaptive quantization interval is presented. Next, we further provide a recursive updating method of quantizing points which include semi real-time update and real-time update. Finally, on the basis of the new method, we establish the Kalman Filter based on the new idea of Non-uniform Quantization and give some analysis of performance, which includes the theoretical part and experiment simulation.

A novel filter design is presented for a class of multivariate nonlinear stochastic systems with uncertain dynamics. The system is subject to non-Gaussian process noises. The entire filter system is proved to be bounded in terms of a specified performance index, provided that the weighting function satisfies a certain condition. An analytical solution of optimal filter gain matrix is also given. Further, the estimation error system is exponentially and ultimately bounded in the mean square sense, even with the presence of system uncertainties. Finally, a simulation example is demonstrated to validate the proposed scheme.