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【Objective】 Sap flow in stems is an approximation of transpiration. It changes with the environment and can be used to help irrigation management. The purpose of this paper is to investigate the intra-annual change in sap flow in the stems of jujube grown in an arid oasis in Xinjiang province, China. 【Method】 The jujube was irrigated by micro sprinkler irrigation; the sap flow was measured continuously using a needle-type stem flow meter for one year, from which we analyzed the change in water consumption of the jujube during its active growth and dormant periods. 【Result】 ①Solar radiation affected the sap flow most and their correlation in the four active growth periods was RD1=0.924, RD2=0.939, RD3=0.943 and RD4=0.915, respectively. In winter when the crop stopped growing, air humidity affected the sap flow more and their correlation coefficient in the five growth periods was RC1=0.699, RC2=0.923, RC3=0.841, RC4=0.918 and RC5=0.618, respectively. ②During the active growing and dormant periods, the durations in which the sap flow was detectable using the meter was 14 h and 9 h, respectively. ③During the active growth seasons, the sap flow peaked from 12:00 to 15:30 pm, while during dormancy it maximized from 03:00 am to 06:00 am in the first two seasons and from 07:00 am to 10:00am in the last two seasons. ④The water consumption during the active growth seasons was ranked in the order of D3>D4>D2>D1, while in dormancy the rank was C1> C5>C3>C2>C4. 【Conclusion】 The annual water consumption of the jujube was approximately 3 994.03 L, in which the consumption during the dormancy, which lasted for 183 days, was 777.30 L, accounting for 19.46% of the total water consumption of the tree.

This paper proposes a novel Switching Chaotic Coupled Map Lattices (SCCML) system based on Elementary Cellular Automata (ECA) to address issues found in Coupled Map Lattices (CML) systems such as period windows, poor lattice correlation, and limited chaotic behavior parameters. The system uses a bidirectional coupling method and introduces two ECA with different rules to continuously alter the indexes of the coupled lattices and the underlying chaotic mapping. This approach effectively mitigates correlation issues in CML systems. At the same time, the iterative results of ECA are cascaded with the chaotic mapping as a perturbation of the SCCML system to extend the parameter range of chaotic behavior. The Kolmogorov–Sinai entropy density and universality, bifurcation diagrams, uniformity and correlation are analyzed to investigate the dynamical properties of the proposed system. Theoretical analysis and numerical simulations demonstrate that, compared with other novel spatiotemporal chaotic systems, the proposed system eliminates periodic windows, expands the chaotic behavior parameter range, and decreases the correlation between different lattices. The above experimental results demonstrate the proposed system's excellent potential for cryptosystems and secure communication. Furthermore, an Encrypted Code Index Modulation (E-CIM) scheme based on reversible ECA encryption is proposed to address the problems of limited pseudo-random sequence resources and low spectrum utilization in direct sequence spread spectrum systems. The proposed scheme uses a chaotic sequence with good correlation and randomness generated by the SCCML spatiotemporal chaos system as the spreading code sequence. In the scheme, the information bits are divided into two parts, namely modulation bits and mapping bits. The modulation bits are mapped to points on the modulation constellation diagram. The mapping bits are encrypted using reversible ECA, and the mapped bits before and after encryption are mapped as spreading sequences with different indexes. Simulation and analysis show that under the same spectrum efficiency conditions, the BER performance of E-CIM is superior to that of the Code Index Modulation (CIM) and Generalized Code Index Modulation (GCIM) schemes by about 2–4 dB and superior to that of the Nonorthogonal Code Shift Keying and Code Index Modulation (N-CSK-CIM) scheme by about 0.5 dB in an additive Gaussian white noise channel when the BER is 10 − 5 . [ABSTRACT FROM AUTHOR]

Magnetization constitutes an efficacious physical treatment technique applicable to saline water. The new spiral flow magnetizer, in conjunction with the cyclic magnetization process, has the effect of maximizing effective magnetization time and thereby achieving the optimal magnetization results. Based on this, saline water (0.27, 3, 6, and 10 g L−1) was treated with different levels of magnetization (0, 0.2, 0.4 and 0.6 T), and the effects of magnetized saline water (MSW) drip irrigation on loamy-sand soil moisture, soluble salt infiltration, and redistribution characteristics were studied through a vertical soil column simulation experiment. The results showed that the wetting front migration in MSW drip irrigation experiments exhibited minimal variation during soil water infiltration, and a notable change during redistribution with the experimental duration of 0.27 and 3g L−1 saline water treatments being significantly different (p < 0.05). Treating saline water with different mineralization levels with magnetization demonstrated water retention (0.27 g L−1 excluded) and salt drainage characteristics; calculated soil water storage increased by 1.58–14.19% and salt storage decreased by 0.22–7.66%. The optimal magnetization intensity for low-mineralization (0.27 and 3 g L−1) saline water was 0.2 T and for high-mineralization (6 and 10 g L−1) it was 0.6 T. The adsorption and exchange of cations (19.58–32.12%) by the optimum MSW treatments was greater than that of anions (9.46–14.15%); specifically, the relative exchange capacity of Ca2+ and Mg2+ in cations was more than K+ and Na+, while HCO3− and SO42− in anions was more than Cl−. This study provides theoretical and technical support for the irrigation of farmland with poor-quality water, as well as for the development of magnetized water irrigation technology. [ABSTRACT FROM AUTHOR]

The rapid growth of deepfake technology, generating realistic manipulated media, poses a significant threat due to potential misuse. Therefore, effective detection methods are urgently needed to prevent malicious use, as current approaches often focus on single modalities or the simple fusion of audio–visual signals, limiting their accuracy. To solve this problem, we propose a deepfake detection scheme based on bimodal temporal feature prediction, which innovatively introduces the idea of temporal feature prediction into the audio–video bimodal deepfake detection task, aiming at fully exploiting the temporal laws of audio–visual modalities. First, pairs of adjacent audio–video sequence clips are used to construct input quadruples, and a dual-stream network is employed to extract temporal feature representations from video and audio, respectively. A video prediction module and an audio prediction module are designed to capture the temporal inconsistencies within each single modality by predicting future temporal features and comparing them with reference features. Then, a projection layer network is designed to align the audio–visual features, using contrastive loss functions to perform contrastive learning and maximize the differences between real and fake video modalities. Experiments on the FakeAVCeleb dataset demonstrate superior performance with an accuracy of 84.33% and an AUC of 89.91%, outperforming existing methods and confirming the effectiveness of our approach in deepfake detection. [ABSTRACT FROM AUTHOR]

Leaf width is a key determinant of planting density and photosynthetic efficiency. In an effort to determine which genes regulate maize plant leaf width, we performed a genome-wide association study (GWAS) of 1.49 × 106 single nucleotide polymorphisms (SNPs) in 80 sequenced backbone inbred maize lines in Jilin Province, China, based upon phenotypic leaf width data from two years. In total, 14 SNPs were identified as being significantly related to leaf width (p < 0.000001), with these SNPs being located on chromosomes 1, 2, 3, 5, 6, 7, 8, and 9. A total of five candidate genes were identified within a mean linkage disequilibrium (LD) distance of 9.7 kb, with a significant SNP being identified within the Zm00001d044327 candidate gene. RNA was then isolated from 12 different inbred maize lines from this GWAS study cohort and was used to conduct qPCR analyses which revealed significant differences in Zm00001d044327 expression among strains exhibiting significant differences in leaf width. Based on an assessment of EMS mutant lines harboring a conserved amino acid stop mutation and two non-synonymous mutations in Zm00001d044327 that exhibited a narrow leaf width, these data suggested that Zm00001d044327 is a key regulator of maize leaf width. [ABSTRACT FROM AUTHOR]

The response of a DPbS3200 infrared detector irradiated by a nanosecond pulsed laser and CW laser has been investigated to study laser-induced interference. A laser interference experiment system was constructed to measure the time-varying response signal. A nanosecond pulsed laser and a CW laser of 10 Hz were used, with a 1064 nm wavelength and a millimeter-scale irradiation spot diameter. Firstly, the characteristics of transient interference signals induced by pulsed lasers were analyzed. Then, the characteristics of response signal interference by both CW laser and pulsed laser irradiation were further investigated. The results showed that the pulsed laser only produced transient interference. However, the CW laser led to a significant amplitude reduction of the response signal, which could continuously interfere in the operating time. For transient interferences, the amplitude of the interference signal increased linearly with the laser fluence. The relation between the pulse repetition rate of the incident laser and the operating frequency of the detector determined the numbers of transient interference signals in one response period; for the interference induced by both the CW laser and pulsed laser, CW laser interference played a leading role when CW laser power density increased to 4.1 W/cm2 or more. As the CW laser fluence reached 6.1 W/cm2, the PbS infrared detector was no longer able to detect any signal, which caused temporary blindness. In the end, a probit model was used to determine the interference threshold. [ABSTRACT FROM AUTHOR]

The development of a crop production strategy through the use of a crop model represents a crucial method for the assurance of a stable agricultural yield and the subsequent enhancement thereof. There are currently no studies evaluating the suitability of the AquaCrop model for the drip irrigation of Gossypium barbadense in Southern Xinjiang, which is the primary planting region for Gossypium barbadense in China. In order to investigate the performance of the AquaCrop model in simulating the growth of cotton under mulched drip irrigation, the model was locally calibrated and validated according to different irrigation thresholds during a key growth period of two years. The results of the simulation for total soil water (TSW), crop evapotranspiration (ETc), canopy coverage (CC), aboveground biomass (Bio), and seed cotton yield demonstrated a high degree of correlation with the observed data, with a root mean square error (RMSE) of <11.58%. The Bio and yield simulations demonstrated a high degree of concordance with the corresponding measured values, with root mean square error (RMSE) values of 1.23 t ha−1 and 0.15 t ha−1, respectively. However, the predicted yield declined in the verification year, though the prediction error remained below 15%. Furthermore, the estimated evapotranspiration (ETc) value demonstrated a slight degree of overestimation. Generally, the middle and late stages of cotton growth led to an overestimation of the TSW content. However, the prediction error was less than 13.99%. Through the calculation of each performance index of the AquaCrop model, it is found that they are in the acceptable range. In conclusion, the AquaCrop model can be employed as a viable tool for predicting the water response of cotton to drip irrigation under mulched film in Southern Xinjiang. Based on 64 years of historical meteorological data, three years were selected as scenarios for simulation. Principal component analysis (PCA) showed that, in a local wet year in Southern Xinjiang, the irrigation quota was 520 mm, and the irrigation cycle was 6 days/time. In normal years, the irrigation quota was 520 mm, with an irrigation cycle of 6 days/time. In dry years, the irrigation quota was 595 mm, with an irrigation cycle of 10 days/time. This allowed for higher seed cotton yields and irrigation water productivity, as well as the maximization of cotton yields and net revenue in the arid oasis area of Southern Xinjiang. [ABSTRACT FROM AUTHOR]

BackgroundAnalyzing the nuclear electrical circuit in time domain can help to obtian the voltage value at any moment based on the appropriate initial voltage by using recursive method.PurposeThis study aims to obtain the correct output waveform of nuclear signal forming circuit by using iteration method instead of recursive method.MethodsFirst of all, the circuit current equation and the S-K low-pass filter circuit equivalent model were established according to Kirchhoff's current law (KCL) and node voltage method. Then the resistant devices were converted to non-resistant devices by equivalent substitution, and the digital solution was obtained by the iterative method. Finally, ihe initial value problem of recursive method was discussed, and the errors between recursive solution and iterative solution of C-R differential circuit and R-C integral circuit in nuclear signal forming circuit were analyzed.ResultsComparison results verify that the iterative method can solve the initial value problems of nuclear signal forming circuit. Iterative solution and the number of iterations are affected by iteration accuracy.ConclusionsThe error between the iterative method and the analytic solution is small. The higher the set data sampling rate is, the smaller the error is. The accuracy of iterative solution is adjustable, and almost the same effect as the recursive solution.is achieved.

BackgroundIn nuclear radiation measurement, nuclear pulse signal can only process the analog circuit system in sequence, generally, signal distortion appeared.PurposeThis paper proposed inverse C-R algorithm aims at obtaining narrow nuclear pulse signal, implementing baseline elimination, and realizing better precision and high-resolution energy spectrum measurement under high counting rate.MethodThis paper makes detail study in C-R circuit system with Laplace transform and Z-transform, and corresponding continuous and discrete solutions to step signal and minus exponential signal of C-R circuit are presented, besides, considering the difficulty in algorithm deployment in FPGA (Field-Programmable Gate Array) with exponential parameter, Taylor expansion is applied to simplify the discrete response, which an modified discrete solution is also presented, besides, numerical solution of C-R system is also considered, the comparison of the three discrete solutions are simulated with MATLAB. And with suitable transform of C-R numerical solution, inverse C-R numerical solution is obtained, as appropriate choice of parameter, inverse C-R numerical solution can not only eliminate the undershoot in nuclear signal, but also realize the narrowing of the signal.Results & ConclusionsSimulation results presents that the three methods are in consistence in nuclear signal processing, and with suitable parameter setting, inverse C-R system can eliminate the undershoot and narrow the signal, and with accurate baseline estimation, baseline restoration can be realized with modified inverse C-R baseline eliminating algorithm.

In order to avoid the intra- and post-operative risks caused by massive blood loss, there are various clinical methods for evaluating the blood supply of the tumor and the distribution of blood vessels around the tumor before surgery, such as dynamic enhanced CT, dynamic enhanced magnetic resonance imaging, digital subtraction angiography, etc. And there are a variety of pre- and intra-operative methods to reduce tumor bleeding, such as transarterial vertebral tumor embolization, percutaneous or transpedicular injection of Onyx/NBCA, antifibrinolytic drugs, controlled deliberate hypotension, etc. This article reviews on spinal tumor blood supply assessment and the methods to reduce the amount of surgical bleeding.

The rapid advancement of deep learning and large-scale AI models has simplified the creation and manipulation of deepfake technologies, which generate, edit, and replace faces in images and videos. This gradual ease of use has turned the malicious application of forged faces into a significant threat, complicating the task of deepfake detection. Despite the notable success of current deepfake detection methods, which predominantly employ data-driven CNN classification models, these methods exhibit limited generalization capabilities and insufficient robustness against novel data unseen during training. To tackle these challenges, this paper introduces a novel detection framework, ReLAF-Net. This framework employs a restricted self-attention mechanism that applies self-attention to deep CNN features flexibly, facilitating the learning of local relationships and inter-regional dependencies at both fine-grained and global levels. This attention mechanism has a modular design that can be seamlessly integrated into CNN networks to improve overall detection performance. Additionally, we propose an adaptive local frequency feature extraction algorithm that decomposes RGB images into fine-grained frequency domains in a data-driven manner, effectively isolating fake indicators in the frequency space. Moreover, an attention-based channel fusion strategy is developed to amalgamate RGB and frequency information, achieving a comprehensive facial representation. Tested on the high-quality version of the FaceForensics++ dataset, our method attained a detection accuracy of 97.92%, outperforming other approaches. Cross-dataset validation on Celeb-DF, DFDC, and DFD confirms the robust generalizability, offering a new solution for detecting high-quality deepfake videos. [ABSTRACT FROM AUTHOR]