Preimage Attacks on the Round-reduced Keccak with Cross-linear Structures

In this paper, based on the work pioneered by Aumasson and Meier, Dinur et al., and Guo et al., we construct some new delicate structures from the roundreduced versions of Keccakhash function family. The new constructed structures are called cross-linear structures, because linear polynomials appear across in different equations of these structures. And we apply cross-linear structures to do preimage attacks on some instances of the round-reduced Keccak. There are three main contributions in this paper. First, we construct a kind of cross-linear structures by setting the statuses carefully. With these cross-linear structures, guessing the value of one linear polynomial could lead to three linear equations (including the guessed one). Second, for some special cases, e.g. the 3-round Keccakchallenge instance Keccak[r=240, c=160, nr=3], a more special kind of cross-linear structures is constructed, and these structures can be used to obtain seven linear equations (including the guessed) if the values of two linear polynomials are guessed. Third, as applications of the cross-linear structures, we practically found a preimage for the 3-round KeccakChallenge instance Keccak[r=240, c=160, nr=3]. Besides, by constructing similar cross-linear structures, the complexity of the preimage attack on 3-round Keccak-256/SHA3-256/SHAKE256 can be lowered to 2150/2151/2153 operations, while the previous best known result on Keccak-256 is 2192

Seek Homogeneous Critical Ice Nucleus at Moderate Supercooling

The quantitative investigation and dynamical understanding of homogeneous nucleation remain a topic of intense research in the interdisciplinary subject. From supercooled water, homogeneous ice nucleation will not happen spontaneously until a critical crystallite nucleus (Nc) pre-exists. In this work, we investigate homogeneous ice nucleation with our molecular dynamics software SPONGE. Using metadynamics and two structural-based collective variables, we successfully improve the sampling technic to grow spherical nuclei with various cubicity and sizes in a 23040-water box. First, we perform the first long-term freezing in all-atom simulation, various nuclei freeze out into Isd. Instead of a certain cluster size based on classical nucleation theory, the dynamic behaviors of ice nuclei experience a wide range of intermediate states. We provide a novel critical nucleus diagram to seek the critical nucleus: the main external factor, surface area, contributes to the freezing speed of the ice nucleus; while the key internal factor, the mean tetrahedral order, controls the melting speed instead. The ice nucleation rates of our work are in good agreement with the former simulation data. We provide a brief frame to discuss the structural details of the nucleation decision

Combining spectral and texture feature of UAV image with plant height to improve LAI estimation of winter wheat at jointing stage

IntroductionLeaf area index (LAI) is a critical physiological and biochemical parameter that profoundly affects vegetation growth. Accurately estimating the LAI for winter wheat during jointing stage is particularly important for monitoring wheat growth status and optimizing variable fertilization decisions. Recently, unmanned aerial vehicle (UAV) data and machine/depth learning methods are widely used in crop growth parameter estimation. In traditional methods, vegetation indices (VI) and texture are usually to estimate LAI. Plant Height (PH) unlike them, contains information about the vertical structure of plants, which should be consider.MethodsTaking Xixingdian Township, Cangzhou City, Hebei Province, China as the research area in this paper, and four machine learning algorithms, namely, support vector machine(SVM), back propagation neural network (BPNN), random forest (RF), extreme gradient boosting (XGBoost), and two deep learning algorithms, namely, convolutional neural network (CNN) and long short-term memory neural network (LSTM), were applied to estimate LAI of winter wheat at jointing stage by integrating the spectral and texture features as well as the plant height information from UAV multispectral images. Initially, Digital Surface Model (DSM) and Digital Orthophoto Map (DOM) were generated. Subsequently, the PH, VI and texture features were extracted, and the texture indices (TI) was further constructed. The measured LAI on the ground were collected for the same period and calculated its Pearson correlation coefficient with PH, VI and TI to pick the feature variables with high correlation. The VI, TI, PH and fusion were considered as the independent features, and the sample set partitioning based on joint x-y distance (SPXY) method was used to divide the calibration set and validation set of samples.ResultsThe ability of different inputs and algorithms to estimate winter wheat LAI were evaluated. The results showed that (1) The addition of PH as a feature variable significantly improved the accuracy of the LAI estimation, indicating that wheat plant height played a vital role as a supplementary parameter for LAI inversion modeling based on traditional indices; (2) The combination of texture features, including normalized difference texture indices (NDTI), difference texture indices (DTI), and ratio texture indices (RTI), substantially improved the correlation between texture features and LAI; Furthermore, multi-feature combinations of VI, TI, and PH exhibited superior capability in estimating LAI for winter wheat; (3) Six regression algorithms have achieved high accuracy in estimating LAI, among which the XGBoost algorithm estimated winter wheat LAI with the highest overall accuracy and best results, achieving the highest R2 (R2 = 0.88), the lowest RMSE (RMSE=0.69), and an RPD greater than 2 (RPD=2.54).DiscussionThis study provided compelling evidence that utilizing XGBoost and integrating spectral, texture, and plant height information extracted from UAV data can accurately monitor LAI during the jointing stage of winter wheat. The research results will provide a new perspective for accurate monitoring of crop parameters through remote sensing

Engineered zero-dispersion microcombs using CMOS-ready photonics

Normal group velocity dispersion (GVD) microcombs offer high comb line power and high pumping efficiency compared to bright pulse microcombs. The recent demonstration of normal GVD microcombs using CMOS-foundry-produced microresonators is an important step towards scalable production. However, the chromatic dispersion of CMOS devices is large and impairs generation of broadband microcombs. Here, we report the development of a microresonator in which GVD is reduced due to a couple-ring resonator configuration. Operating in the turnkey self-injection-locking mode, the resonator is hybridly integrated with a semiconductor laser pump to produce high-power-efficiency combs spanning a bandwidth of 9.9 nm (1.22 THz) centered at 1560 nm, corresponding to 62 comb lines. Fast, linear optical sampling of the comb waveform is used to observe the rich set of near-zero GVD comb behaviors, including soliton molecules, switching waves (platicons) and their hybrids. Tuning of the 20 GHz repetition rate by electrical actuation enables servo locking to a microwave reference, which simultaneously stabilizes the comb repetition rate, offset frequency and temporal waveform. This hybridly integrated system could be used in coherent communications or for ultra-stable microwave signal generation by two-point optical frequency division.Comment: 8 pages, 4 figure

In Vivo Delivery of Gremlin siRNA Plasmid Reveals Therapeutic Potential against Diabetic Nephropathy by Recovering Bone Morphogenetic Protein-7

Diabetic nephropathy is a complex and poorly understood disease process, and our current treatment options are limited. It remains critical, then, to identify novel therapeutic targets. Recently, a developmental protein and one of the bone morphogenetic protein antagonists, Gremlin, has emerged as a novel modulator of diabetic nephropathy. The high expression and strong co-localization with transforming growth factor- β1 in diabetic kidneys suggests a role for Gremlin in the pathogenesis of diabetic nephropathy. We have constructed a gremlin siRNA plasmid and have examined the effect of Gremlin inhibition on the progression of diabetic nephropathy in a mouse model. CD-1 mice underwent uninephrectomy and STZ treatment prior to receiving weekly injections of the plasmid. Inhibition of Gremlin alleviated proteinuria and renal collagen IV accumulation 12 weeks after the STZ injection and inhibited renal cell proliferation and apoptosis. In vitro experiments, using mouse mesangial cells, revealed that the transfect ion of gremlin siRNA plasmid reversed high glucose induced abnormalities, such as increased cell proliferation and apoptosis and increased collagen IV production. The decreased matrix metalloprotease level was partially normalized by transfection with gremlin siRNA plasmid. Additionally, we observed recovery of bone morphogenetic protein-7 signaling activity, evidenced by increases in phosphorylated Smad 5 protein levels. We conclude that inhibition of Gremlin exerts beneficial effects on the diabetic kidney mainly through maintenance of BMP-7 activity and that Gremlin may serve as a novel therapeutic target in the management of diabetic nephropathy

Resource allocation and scheduling for scalable video streaming over wireless networks

Scalable video, evolved in a long way of more than 20 years, has attracted significant interest in the past decades in both academia and industry due to its versatility and potential in providing flexible storage and communication services. In contrast to the conventional video coding which encodes a video clip once and for all, the scalable video enables the composition of multiple clips in different specifications into a single bitstream and provides feasible mechanisms to adapt to the changing needs of networks or applications. With the finalization of the scalable extension of legacy H.264/AVC, i.e., Scalable Video Coding (SVC), the exploration on the potentials of coding, adaptation, scheduling and resource allocation becomes more interesting. Especially with the era of mobile internet, the exponential growth in demand for wireless video puts the scalable video to the spotlight, considering its high coding efficiency and feasible rate adaptation capability. Due to the error-prone and resource scarcity nature of the wireless networks, it is critical that efficient and effective resource allocation and packet scheduling schemes can be developed to deal with the underlying challenges. A comprehensive scheme always lies in the joint investigations on the video characteristics and the network specifications. Video content analysis focuses mainly on coding and the optimization of rate-utility (rate-distortion), scalability-rate, scalability-quality (PSNR, MOS, QoE), and so on. Meanwhile, resource allocation and packet scheduling normally consider the specifications of wireless networks from different Open Systems Interconnection (OSI) layers. In this thesis, scalable video streaming over wireless networks is investigated and evaluated in several typical wireless systems, through which we hope to inspire new research on this topic and foster its deployment in practical systems. The main contributions and achievements of this thesis are summarized below: 1. The first contribution of this thesis is the proposal of efficient packet prioritization and scheduling schemes for scalable video streaming over WLANs. The work provides an inspiration on how to apply the conventional unequal error protection strategy into scalable video transmissions and shows a novel way to deal with the network congestion issue in best effort networks. 2. This thesis also devotes to the fast scalable video rate adaptation. The fast adaptation scheme answers for how to obtain the maximal video quality in real-time scalable video adaptation and also provides effective tool to facilitate the video streaming applications. 3. The third contribution concerns a scalable resource allocation framework for SVC video streaming over MIMO-OFDM networks. By skillfully utilizing the feature of scalable video, the scalable framework renders a novel way to tackle the conventional dilemma in fair versus efficient design in multiuser resource allocation problems. 4. Based on a subjective video quality assessment database, the thesis summarizes various scalability adaptation tracks for QoE-aware rate adaptation. This thesis also constructs a rate-QoE model, which favors the understanding of scalable video adaptation and also facilitates the analysis in QoE-aware video streaming.DOCTOR OF PHILOSOPHY (EEE

A comprehensive ensemble model for comparing the allosteric effect of ordered and disordered proteins.

Intrinsically disordered proteins/regions (IDPs/IDRs) are prevalent in allosteric regulation. It was previously thought that intrinsic disorder is favorable for maximizing the allosteric coupling. Here, we propose a comprehensive ensemble model to compare the roles of both order-order transition and disorder-order transition in allosteric effect. It is revealed that the MWC pathway (order-order transition) has a higher probability than the EAM pathway (disorder-order transition) in allostery, suggesting a complicated role of IDPs/IDRs in regulatory proteins. In addition, an analytic formula for the maximal allosteric coupling response is obtained, which shows that too stable or too unstable state is unfavorable to endow allostery, and is thus helpful for rational design of allosteric drugs