Chinese Academy of Science and Technology for Development

Abstract The simultaneous improvement of grain quality and yield of cereal crops is a major challenge for modern agriculture. Here we show that a rice grain yield quantitative trait locus qLGY3 encodes a MADS-domain transcription factor OsMADS1, which acts as a key downstream effector of G-protein βγ dimers. The presence of an alternatively spliced protein OsMADS1 lgy3 is shown to be associated with formation of long and slender grains, resulting in increases in both grain quality and yield potential of rice. The Gγ subunits GS3 and DEP1 interact directly with the conserved keratin-like domain of MADS transcription factors, function as cofactors to enhance OsMADS1 transcriptional activity and promote the co-operative transactivation of common target genes, thereby regulating grain size and shape. We also demonstrate that combining OsMADS1 lgy3 allele with high-yield-associated dep1-1 and gs3 alleles represents an effective strategy for simultaneously improving both the productivity and end-use quality of rice.

BACKGROUND: The authors report the likelihood of treatment failure and the outcomes after salvage therapy among men with prostate cancer who initially either received external-beam radiation therapy (EBRT) or underwent radical prostatectomy (RP). METHODS: Using a national disease registry, the Cancer of the Prostate Strategic Urological Research Endeavor (CaPSURE) database, 5277 men with prostate cancer were identified who initially either underwent RP (4342 men) or received EBRT (935 men). Outcomes after disease recurrence and subsequent salvage therapy were assessed. RESULTS.: Recurrent disease developed in 1590 men (30%), including 1003 patients (23%) in the RP group and 587 patients (63%) in the EBRT group, at a mean of 34 months and 38 months, respectively (P= .003). Patients who had recurrent disease had greater rates of overall death (19% vs 3%; P< .01) and bone metastases (15% vs 1%; P< .01). Data after salvage therapy were available for 1050 patients (620 men in the RP group and 430 men in the EBRT group). Androgen-deprivation therapy (ADT) was the most common salvage treatment in both groups. Overall, 420 men in the RP group (68%) and 319 men in the EBRT group (74%) failed salvage therapy at mean of 43.6 months and 43.8 months, respectively (P= .95). These patients had a greater overall death rate than the 311 patients who did not fail salvage therapy (24.8% vs 6.9%, respectively; P< .001). No survival benefit in terms of prostate cancer-related death (P= .91) was identified with any particular combination of primary and salvage therapy. CONCLUSIONS: Disease recurrence developed in 30% of patients who were treated for prostate cancer, and ADT was the most common salvage therapy used. Patients who failed salvage therapy had worse overall survival, and no survival benefit was noted for any particular combination of primary and salvage therapy.

Abstract Side reactions on zinc metal (Zn) anodes are formidable issues that cause limited battery life of aqueous zinc‐ion batteries (AZIBs). Here, a facile and controllable layer‐by‐layer (LbL) self‐assembly technique is deployed to construct an ion‐conductive and mechanically robust electrolyte/anode interface for stabilizing the Zn anode. The LbL film consists of two natural and biodegradable bio‐macromolecules, chitosan (CS) and sodium alginate (SA). It is shown that such an LbL film tailors the solvation sheath of Zn ions and facilitates the oriented deposition of Zn. Symmetric cells with the four double layers of CS/SA ((CS/SA) 4 –Zn) exhibit stable cycles for over 6500 h. The (CS/SA) 4 –Zn||H 2 V 3 O 8 coin cell maintains a specific capacity of 125.5 mAh g −1 after 14 000 cycles. The pouch cell with an electrode area of 5 × 7 cm 2 also presents a capacity retention of 83% for over 500 cycles at 0.1 A g −1 . No obvious dendrites are observed after long cycles in both symmetric and full cells. Given the cost‐effective material and fabrication, and environmental friendliness of the LbL films, this Zn protection strategy may boost the industrial application of AZIBs.

Cloud computing is a revolutionary computing paradigm, which enables flexible, on-demand, and low-cost usage of computing resources, but the data is outsourced to some cloud servers, and various privacy concerns emerge from it. Various schemes based on the attribute-based encryption have been proposed to secure the cloud storage. However, most work focuses on the data contents privacy and the access control, while less attention is paid to the privilege control and the identity privacy. In this paper, we present a semianonymous privilege control scheme AnonyControl to address not only the data privacy, but also the user identity privacy in existing access control schemes. AnonyControl decentralizes the central authority to limit the identity leakage and thus achieves semianonymity. Besides, it also generalizes the file access control to the privilege control, by which privileges of all operations on the cloud data can be managed in a fine-grained manner. Subsequently, we present the AnonyControl-F, which fully prevents the identity leakage and achieve the full anonymity. Our security analysis shows that both AnonyControl and AnonyControl-F are secure under the decisional bilinear Diffie-Hellman assumption, and our performance evaluation exhibits the feasibility of our schemes.

Modeling and learning of brain activity patterns represent a huge challenge to the brain-computer interface (BCI) based on electroencephalography (EEG). Many existing methods estimate the uncorrelated instantaneous demixing of EEG signals to classify multiclass motor imagery (MI). However, the condition of uncorrelation does not hold true in practice, because the brain regions work with partial or complete collaboration. This work proposes a novel method, termed as a common Bayesian network (CBN), to discriminate multiclass MI EEG signals. First, with the constraints of a Gaussian mixture model on every channel, only related channels are selected to construct a normal Bayesian network. Second, the nodes that have both common and varying edges are selected to construct a CBN. Third, the probabilities on common edges are used to learn about the support vector machine for classification. To validate the proposed method, we conduct experiments on two well-known BCI datasets and perform a numerical analysis of the propose algorithm for EEG classification in a multiclass MI BCI. Experimental results show that the proposed CBN method not only has excellent classification performance, but also is highly efficient. Hence, it is suitable for the cases where a system is required to respond within a second.

Cloud computing is a revolutionary computing paradigm which enables flexible, on-demand and low-cost usage of computing resources. Those advantages, ironically, are the causes of security and privacy problems, which emerge because the data owned by different users are stored in some cloud servers instead of under their own control. To deal with security problems, various schemes based on the Attribute-Based Encryption have been proposed recently. However, the privacy problem of cloud computing is yet to be solved. This paper presents an anonymous privilege control scheme AnonyControl to address not only the data privacy problem in a cloud storage, but also the user identity privacy issues in existing access control schemes. By using multiple authorities in cloud computing system, our proposed scheme achieves anonymous cloud data access and fine-grained privilege control. Our security proof and performance analysis shows that AnonyControl is both secure and efficient for cloud computing environment.

Photocatalytic CO₂ reduction is enhanced by the promoted charge transfer at the interface between TiO₂ and Ti₃C₂ after the <italic>in situ</italic> growth of TiO₂ on Ti₃C₂.

Abstract The growth of dendrites and the hydrogen evolution reaction pose significant challenges to the development of Zn metal aqueous batteries as a promising solution for energy storage. Herein, trisodium nitrilotriacetate (Na 3 NTA) as an electrolyte additive is shown to improve the reversibility of the zinc plating–stripping process. NTA 3− anions possess the potential not only to substitute water molecules in the solvation sheath of Zn 2+ ions but also to construct a zincophilic electrolyte/Zn anode interface and suppress the activity of water molecules for stabilizing the Zn anode. The introduction of Na 3 NTA can effectively suppress side reactions arising from active water decomposition and simultaneously lead to the formation of a well‐defined (002) texture structure. As a result, a Zn||Zn symmetric cell with a modified electrolyte demonstrates a lifespan of up to 3000 h at a cutoff capacity of 1 mA h cm −2 . Furthermore, a Zn||V 2 O 5 full cell exhibits an enhanced capacity retention of 83.2% even after undergoing 8000 cycles. No noticeable dendrites are observed even after long cycles in both symmetric and full cells. Due to the cost‐effective material and ease of fabrication of the Na 3 NTA additive, this electrolyte strategy may promote the industrial application of aqueous zinc ion batteries.

Leaf chlorophyll content (LCC) provides valuable information about the nutrition and photosynthesis statuses of crops. Vegetation index-based methods have been widely used in crop management studies for the non-destructive estimation of LCC using remote sensing technology. However, many published vegetation indices are sensitive to crop canopy structure, especially the leaf area index (LAI), when crop canopy spectra are used. Herein, to address this issue, we propose four new spectral indices (The red-edge-chlorophyll absorption index (RECAI), the red-edge-chlorophyll absorption index/optimized soil-adjusted vegetation index (RECAI/OSAVI), the red-edge-chlorophyll absorption index/ the triangular vegetation index (RECAI/TVI), and the red-edge-chlorophyll absorption index/the modified triangular vegetation index(RECAI/MTVI2)) and evaluate their performance for LCC retrieval by comparing their results with those of eight published spectral indices that are commonly used to estimate LCC. A total of 456 winter wheat canopy spectral data corresponding to physiological parameters in a wide range of species, growth stages, stress treatments, and growing seasons were collected. Five regression models (linear, power, exponential, polynomial, and logarithmic) were built to estimate LCC in this study. The results indicated that the newly proposed integrated RECAI/TVI exhibited the highest LCC predictive accuracy among all indices, where R2 values increased by more than 13.09% and RMSE values reduced by more than 6.22%. While this index exhibited the best association with LCC (0.708** ≤ r ≤ 0.819**) among all indices, RECAI/TVI exhibited no significant relationship with LAI (0.029 ≤ r ≤ 0.167), making it largely insensitive to LAI changes. In terms of the effects of different field management measures, the LCC predictive accuracy by RECAI/TVI can be influenced by erective winter wheat varieties, low N fertilizer application density, no water application, and early sowing dates. In general, the newly developed integrated RECAI/TVI was sensitive to winter wheat LCC with a reduction in the influence of LAI. This index has strong potential for monitoring winter wheat nitrogen status and precision nitrogen management. However, further studies are required to test this index with more diverse datasets and different crops.

Abstract Neuromorphic systems can parallelize the perception and computation of information, making it possible to break through the von Neumann bottleneck. Neuromorphic engineering has been developed over a long period of time based on Hebbian learning rules. The optoelectronic neuromorphic analog device combines the advantages of electricity and optics, and can simulate the biological visual system, which has a very strong development potential. Low‐dimensional materials play a very important role in the field of optoelectronic neuromorphic devices due to their flexible bandgap tuning mechanism and strong light‐matter coupling efficiency. This review introduces the basic synaptic plasticity of neuromorphic devices. According to the different number of terminals, two‐terminal neuromorphic memristors, three‐terminal neuromorphic transistors and artificial visual system are introduced from the aspects of the action mechanism and device structure. Finally, the development prospect of optoelectronic neuromorphic analog devices based on low‐dimensional materials is prospected.

Much research has been conducted to securely outsource multiple parties' data aggregation to an untrusted aggregator without disclosing each individual's privately owned data, or to enable multiple parties to jointly aggregate their data while preserving privacy. However, those works either require secure pair-wise communication channels or suffer from high complexity. In this paper, we consider how an external aggregator or multiple parties can learn some algebraic statistics (e.g., sum, product) over participants' privately owned data while preserving the data privacy. We assume all channels are subject to eavesdropping attacks, and all the communications throughout the aggregation are open to others. We first propose several protocols that successfully guarantee data privacy under semi-honest model, and then present advanced protocols which tolerate up to k passive adversaries who do not try to tamper the computation. Under this weak assumption, we limit both the communication and computation complexity of each participant to a small constant. At the end, we present applications which solve several interesting problems via our protocols.

The nexus between green growth and ecological footprint is associated with crucial environmental implications. But this domain is not examined sufficiently and provides ambiguous findings. Furthermore, these studies have not addressed the role of natural resources, environmental innovation, and ICT in influencing ecological footprint. Our study analyzes the impact of green growth, ICT, environmental innovation, and natural resources on the ecological footprint ofemerging-7 and developed-7 economies. We employed CS-ARDL methodology to draw the long-run and short-run estimates of the said relationships. The obtained findings show that green growth, ICT, and environmental innovation reduce the ecological footprint in emerging economies in the long run. However, natural resources enhance the ecological footprint in emerging economies in the long run. Green growth, ICT, natural resources, and environmental innovation reduce the ecological footprint in the long run in developed economies. Based on these outcomes, the study recommends important policy suggestions.

Carbon nanotubes (CNTs) have attracted wide attention because of their unique structure and properties. However, the prepared CNTs often present agglomeration state, which destroys the excellent properties of single carbon nanotubes and seriously affects the application of carbon nanotubes. How to effectively disperse carbon nanotubes has become an urgent problem to be solved. There are many factors affecting the dispersion of carbon nanotubes. In this paper, the effects of three aspects of surfactant, ultrasonic oscillation and centrifugation on the dispersion of carbon nanotubes and fiscal policies for the development of nano high-tech industry are mainly studied.

The analysis aims to examine the impact of eco-innovation and financial efficiency on CO2 emissions and renewable energy consumption in highly polluted Asian economies, including China, India, Russia, and Japan. For empirical analysis, we have applied the ARDL pooled mean group (ARDL-PMG) model. The long-run estimated coefficient of environmental innovations is positively significant in both renewable energy models and negatively significant in the CO2 emissions model. These results imply that environmental innovations help facilitate renewable energy consumption and reduce CO2 emissions. On the other side, the estimates of financial development are insignificant in both renewable energy and CO2 emissions models. However, the estimates of financial institution efficiency and financial markets are positively significant in both renewable energy and CO2 emissions models, implying that financial institutions and market efficiency increase renewable energy consumption and decrease CO2 emissions.

AIM: To analyze the performance value of high risk factors in population-based colorectal cancer (CRC) screening in China. METHODS: We compared the performance value of the immunochemical fecal occult blood test (iFOBT) and other high risk factors questionnaire in a population sample of 13 214 community residents who completed both the iFOBT and questionnaire investigation. Patients with either a positive iFOBT and/or questionnaire were regarded as a high risk population and those eligible were asked to undergo colonoscopy. RESULTS: The iFOBT had the highest positive predictive value and negative predictive value in screening for advanced neoplasia. The iFOBT had the highest sensitivity, lowest number of extra false positive results associated with the detection of one extra abnormality for screening advanced neoplasias and adenomas. A history of chronic cholecystitis or cholecystectomy, chronic appendicitis or appendectomy, and chronic diarrhea also had a higher sensitivity than a history of adenomatous polyps in screening for advanced neoplasias and adenomas. The sensitivity of a history of chronic cholecystitis or cholecystectomy was highest among the 10 high risk factors in screening for non-adenomatous polyps. A history of chronic appendicitis or appendectomy, chronic constipation, chronic diarrhea, mucous and bloody stool, CRC in first degree relatives, malignant tumor and a positive iFOBT also had higher sensitivities than a history of adenomas polyps in screening for non-adenomatous polyps. Except for a history of malignant tumor in screening for non-adenomatous polyps, the gain in sensitivity was associated with an increase in extra false positive results associated with the detection of one extra abnormality. CONCLUSION: The iFOBT may be the best marker for screening for advanced neoplasias and adenomas. Some unique high risk factors may play an important role in CRC screening in China.

Development of artificial biomaterials by mimicking extracellular matrix of bone tissue is a promising strategy for bone regeneration. Hydrogel has emerged as a type of viable substitute, but its inhomogeneous networks and weak mechanics greatly impede clinical applications. Here, a dual crosslinked gelling system is developed with tunable architectures and mechanics to promote osteogenic capacity. Polyhedral oligomeric silsesquioxane (POSS) is designated as a rigid core surrounded by six disulfide-linked PEG shells and two 2-ureido-4[1H]-pyrimidinone (UPy) groups. Thiol-disulfide exchange is employed to fabricate chemical network because of the pH-responsive "on/off" function. While self-complementary UPy motif is capable of optimizing local microstructure to enhance mechanical properties. Taking the merits of biocompatibility and high-mechanics in periodontal ligament stem cells (PDLSCs) proliferation, attachment, and osteogenesis, hybrid hydrogel exhibits outstanding osteogenic potential both in vitro and in vivo. Importantly, it is the first time that a key epigenetic regulator of ten-eleven translocation 2 (Tet2) is discovered to significantly elevate the continuously active the WNT/β-catenin through Tet2/HDAC1/E-cadherin/β-catenin signaling cascade, thereby promoting PDLSCs osteogenesis. This work represents a general strategy to design the hydrogels with customized networks and biomimetic mechanics, and illustrates underlying osteogenic mechanisms that will extend the design rationales for high-functional biomaterials in tissue engineering.

Artificial intelligence is believed as a disruptive technology, which will change our economy and society significantly in the near future. It can be employed to replace human labors in completing many dangerous and tedious tasks, providing us with more convenient and efficient life. We can benefit a lot from the wide application of this emerging technology. However, there are also potential risks and threats in application of artificial intelligence, which need to be handled in a proper way before extensive usage. In the paper, we make discussions on the security, privacy and ethnic issues in artificial intelligence applications and point out the potential risks and threats. Countermeasures in research, regulation and supervision are suggested and our expectation for artificial intelligence development is given out.

Abstract To investigate temporal and spatial variations in diffusive CH 4 emission from the surface of the Three Gorges Reservoir, CH 4 emissions were measured using the static chamber technique along the mainstream of the reservoir from January to December 2010. The overall average CH 4 flux is 7.93 mg CH 4 m −2 d −1 , which is comparable to those from other temperate reservoirs but significantly lower than those from tropical reservoirs. Seasonal variations showed that CH 4 emission reached the maximum in the summer and turned to the low levels in the other seasons; such variations reflected the seasonal dynamics of temperature, dissolved oxygen, and water velocity. Moreover, the yearly average CH 4 flux decreased from upstream to downstream before the Three Gorges Dam, but CH 4 emission from the surface of the downstream river was higher than that from the surface at Zigui, the upstream water before the Three Gorges Dam. The differences in water velocity and allochthonous input of organic matter probably caused the spatial variations in CH 4 emission. These results indicate that systematic sampling is needed to better estimate CH 4 emission through coverage of the temporal and spatial scales and to better assess the influence of CH 4 emission from the Three Gorges Reservoir on climate change in China, as well as the rest of the world.

Arsenic trioxide (ATO) is approved for treating terminal-stage liver cancer in China. Cryptotanshinone (CT), a STAT3 inhibitor, has exhibited certain anti-tumor potency; however, the use of CT enhanced ATO for treating liver cancer has not been reported. Here we try to elucidate how CT could enhance the efficacy of ATO for treating liver cancer and its correlation to STAT3 in vitro and in vivo. Cell viability of ATO combined with CT was assessed by 1MTT assay. Cell apoptosis induced by ATO combined with CT was detected by Annexin V/PI staining and apoptosis-related proteins were detected by western blotting. STAT3-related proteins were analysis by western blotting analysis and Immunofluorescence assays. Efficacy evaluation of ATO combined with CT on xenograft was carried in nude mice and related proteins were analysis by Immunohistochemistry assays. First we evaluated cell vitality, and our data indicated that the ATO combined with CT showed obvious growth inhibition of Bel-7404 cells compared to ATO or CT alone. Next we found that ATO combined with CT induced cell apoptosis in Bel-7404 cells and upregulated the activation of apoptosis-related proteins cleaved-caspase-3, cleaved-caspase-9, and cleaved-poly(ADP-ribose) polymerase in a time-dependent manner. Next, we found that ATO combined with CT not only inhibited the constitutive levels of phosphorylated-JAK2 and phosphorylated-STAT3Tyr705 but did so in a time-dependent manner. We also found that ATO combined with CT reversed the upregulated expression of phosphorylated-STAT3Tyr705 stimulated by interleukin-6 and downregulated STAT3 direct target genes and the anti-apoptotic proteins Bcl-2, XIAP, and survivin but obviously upregulated the promoting apoptosis proteins Bak,.In vivo studies showed that ATO combined with CT decreased tumor growth. Tumors from ATO combined with CT–treated mice showed decreased levels of phosphorylated-STAT3Tyr705 and the anti-apoptotic protein Bcl-2 but an increased level of pro-apoptotic protein Bax. Our study provides strong evidence that CT could enhance the efficacy of ATO in treating liver cancer both in vitro and in vivo. Downregulation of phosphorylated-STAT3 expression may play an important role in inducing apoptosis of Bel-7404 cells.

Poverty alleviation has attracted extensive attention worldwide. This paper investigated the spatial agglomeration effect and dynamics driving rural education levels (namely, primary education, junior secondary education, and senior secondary education) and rural poverty in 27 provinces of China in 2010-2017. The results of a spatial autoregressive (SAR) model revealed that different education levels have distinct effects on rural poverty, and the impact of compulsory education on rural poverty is greater than that of senior secondary education. We further found that rural poverty in a region is clearly not only internally driven but also impacted by the poverty rate in the surrounding provinces, suggesting that regional poverty alleviation policies should combine regional education differences and learn from poverty alleviation through education experience in surrounding areas. Thus, the findings established in this paper have significant implications for targeted poverty alleviation measures in China by improving education.