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Abstract Permanent magnet synchronous motor (PMSM) drive systems are receiving increasing attention due to their superior control quality and efficiency. Optimizing the control parameters are key to achieve the high-performance operation of PMSMs. Although heuristic algorithms demonstrate excellent optimization outcomes in simulations, there are still challenges in deploying optimization schemes in practical drives. In this study, a real-time online deployable control parameter optimization scheme is proposed. The optimization effect is evaluated through the system step response performance, and a framework for deploying optimization algorithms within the driver is developed. A fault suppression mechanism is also designed to mitigate overshoot and vibration issues caused by suboptimal solutions. The proposed scheme is validated on a rapid prototyping control platform. Experimental results confirm that the scheme exhibits good optimization performances across various operating conditions. The honey badger algorithm employed in this paper shows faster convergence and more stable optimization effects than other optimization algorithms. The optimization effect is improved by 2.2% and its performance in terms of consistency across multiple optimization results has increased by 40%.

Abstract Aiming at the demagnetization fault problem of the permanent magnet synchronous motor (PMSM), a demagnetization fault diagnosis method based on the combination of the principal component analysis (PCA) algorithm, the improved sparrow search algorithm (ISSA), and the probabilistic neural network (PNN) algorithm is proposed. First, the principal components of phase currents are extracted using PCA. Second, ISSA is used to optimize the smoothing coefficients of the PNN algorithm, and the optimized PNN algorithm is combined with PCA to obtain the PCA-ISSA-PNN fault diagnosis model. Finally, the established fault diagnosis model was tested using the current data collected from the experiments and compared with the fault diagnosis indexes and optimization performance of the conventional PNN, PCA-PNN, PCA-GA (genetic algorithm)-PNN, PCA-DA (dragonfly algorithm)-PNN, PCA-GTO (artificial gorilla troop optimizer)-PNN, PCA-AHA-PNN, and PCA-SSA-PNN. The test results show that the fault diagnosis accuracy of PCA-ISSA-PNN reaches 95.83%, and the fault diagnosis indexes are significantly higher than those of PNN, PCA-PNN, PCA-GA-PNN, and PCA-DA-PNN; its optimization performance is also significantly better than that of PCA-GTO-PNN, PCA-AHA-PNN, and PCA-SSA-PNN, which verifies the accuracy and efficiency of the proposed method.

This paper investigates the optimization design of interior permanent magnet synchronous motors (IPMSM) for electric vehicles (EVs). The optimization process of IPMSM involves numerous design parameters, and the optimization objectives often conflict with each other, resulting in a vast design space and difficulties in establishing an accurate mathematical model. The traditional finite element analysis (FEA) optimization methods are time-consuming and computationally intensive, posing a significant challenge to achieving high-performance IPMSM with high torque, high efficiency, low vibration, and low losses. To address this issue, this paper proposes a multi-objective optimization of IPMSM for electric vehicles based on the combinatorial surrogate model and the hierarchical design method. Firstly, a comprehensive sensitivity coefficient method is employed to categorize design variables into two layers: high-sensitivity design variables (HSDVs) and low-sensitivity design variables (LSDVs). Secondly, using the improved Latin hypercube sampling (LHS) method to extract sample data, a high-precision combined surrogate model (RSM + Kriging) is constructed and combined with the non-dominated sorting genetic algorithm II (NSGA-II) optimization algorithm to optimize HSDVs. Meanwhile, the fuzzy inference Taguchi method (FITM) is utilized to optimize the LSDVs. Finally, the performance of the IPMSM before and after optimization has been analyzed through the FEA method, and different optimization methods were introduced for comparison. The results show that compared to other optimization methods, the optimization approach proposed in this paper can effectively enhance the overall performance of the IPMSM. The average torque of the optimized IPMSM increased by 5.22 %, the torque ripple decreased by 77.64 %, and the total losses were reduced by 6.21 %. Furthermore, compared to the traditional FEA method, this method reduces optimization time and improves optimization efficiency without compromising on optimization accuracy.

Background Seed vigor recognized as a quantitative trait is of particular importance for agricultural production. However, limited knowledge is available for understanding genetic basis of wheat seed vigor. Methods The aim of this study was to identify quantitative trait loci (QTL) responsible for 10 seed vigor-related traits representing multiple aspects of seed-vigor dynamics during artificial aging with 6 different treatment times (0, 24, 36, 48, 60, and 72 h) under controlled conditions (48 °C, 95% humidity, and dark). The mapping populations were two wheat introgression lines (IL-1 and IL-2) derived from recipient parent (Lumai 14) and donor parent (Shaanhan 8675 or Jing 411). Results A total of 26 additive QTLs and 72 pairs of epistatic QTLs were detected for wheat seed-vigor traits. Importantly, chromosomes 1B and 7B contained several co-located QTLs, and chromosome 2A had a QTL-rich region near the marker Xwmc667, indicating that these QTLs may affect wheat seed vigor with pleiotropic effects. Furthermore, several possible consistent QTLs (hot-spot regions) were examined by comparison analysis of QTLs detected in this study and reported previously. Finally, a set of candidate genes for wheat seed vigor were predicted to be involved in transcription regulation, carbohydrate and lipid metabolism. Conclusion The present findings lay new insights into the mechanism underlying wheat seed vigor, providing valuable information for wheat genetic improvement especially marker-assisted breeding to increase seed vigor and consequently achieve high grain yield despite of further investigation required.

The new-type tobacco varieties “Zisu” and “Luole” were obtained by distant hybridization between N. tabacum L. var. HHY and Perilla frutescens and Ocimum basilicum, with obviously different chemical composition. Smoking is the major risk factor for COPD, characterized by neutrophil-dominant inflammation. In the present study, rat COPD model was established by cigarette exposure, and the health hazard of three varieties was compared by general condition observation, pathological and morphological evaluation, total and differential cell numeration, and characterization of major inflammatory mediators and MAPK/NF-κB pathway, etc. Rats in “HHY” group developed obvious symptoms such as cough, dyspnea, mental fatigue, etc., but these symptoms were obviously mitigated in “Zisu” and “Luole” groups. H&E staining analysis, including score, MLI, MAN, wt% and WA%, showed that “Zisu” and “Luole” significantly alleviated lung injury and the degree of airway remodeling and emphysema compared to “HHY”. In BALF, the number of total leukocyte and the percent neutrophils in “Zisu” and “Luole” groups were evidently lower than “HHY” group. The levels of inflammatory mediators, such as IL-8, MPO, MIP-2, LTB4, TNF-α and neutrophil elastase, in “HHY” group were obviously higher than “Zisu” and “Luole” groups. The ROS-mediated NF-κB p65 and p38MAPK pathways may play an important role. Results indicated that tobacco introduced perilla and basil genes could remarkably attenuate recruitment, infiltration and activation of neutrophils and intervene in airway inflammation, retarding disease progression, especially “Zisu”. Changes in chemical composition via breeding techniques may be a novel way for tobacco harm reduction.

When a super-large diameter shield tunnel passes through a strongly karst-developed area, in order to ensure the stability of the tunnel and economy of karst reinforcement, the reasonable treatment range for a huge number of karst caves needs to be researched. Based on a karst treatment project of a shield tunnel with a diameter of 14.5 m, this paper studies the influence of intrusive fully filled karst caves on the stability of the lining and excavation face by using theoretical calculation. In addition, the safe distance between the tunnel and karst caves outside the tunnel is proposed through numerical simulation, and the corresponding treatment range is obtained. The results show that the bearing capacity of the lining has a certain reserve when the intrusive cave is smaller than a certain size, and the caves filled with plastic or hard plastic clay have sufficient antifracturing ability. Therefore, some small fully filled caves inside the tunnel profile can be left unreinforced. On the other side, the critical safe distance is only 1–2 m for the caves with a size of 3 m, so the outside caves with a size less than 3 m can be left unreinforced in the treatment range farther away from the tunnel. The proposed treatment range is close to similar projects that have been built, indicating that analysis results are reasonable.

The octoploid-cultivated strawberry variety Benihope (Fragaria × ananassa Duch cv. Benihope) is an important commercial plant. It is highly susceptible to different diseases, which ultimately leads to a reduction in yield. Gene-editing methods, such as CRISPR/Cas9, demonstrate potential for improving disease resistance in the strawberry cv. Benihope. Establishing a plant regeneration system suitable for CRISPR/Cas9 gene editing is crucial for obtaining transgenic plants on a large scale. This research established a callus induction and plant regeneration system for Agrobacterium-mediated CRISPR/Cas9 gene editing in strawberry cv. Benihope by evaluating multiple types of explants and various plant growth regulators throughout the entire tissue culture process. The results showed that the efficiency of callus induction is strongly influenced by the type of explant and is highly sensitive to the combination of plant growth regulators. Among the different plant growth regulators employed, thidiazuron (TDZ), in combination with 2,4-dichlorophenoxyacetic acid (2,4-D), effectively induced callus formation and plant regeneration from explants derived from nutrient tissues such as runner tips and crowns. In addition, the regeneration experiment demonstrated that the addition of polyvinylpyrrolidone (PVPP) to the shoot regeneration medium could inhibit tissue browning. The gene-edited plants in which some or all of the Fvb7-1, Fvb7-2, Fvb7-3, and Fvb7-4 genes in the MLO (Mildew resistance Locus O) gene family were knocked out by CRISPR/Cas9 system were obtained by applying the plant regeneration system developed in this study.

Spodoptera frugiperda (Lepidoptera: Noctuidae), a pest with an amazing appetite, damages many crops and causes great losses, especially maize. Understanding the differences in different maize cultivars’ responses to S. frugiperda infestation is very important for revealing the mechanisms involved in the resistance of maize plants to S. frugiperda. In this study, a comparative analysis of two maize cultivars, the common cultivar ‘ZD958’ and the sweet cultivar ‘JG218’, was used to investigate their physico-biochemical responses to S. frugiperda infestation by a pot experiment. The results showed that the enzymatic and non-enzymatic defense responses of maize seedlings were rapidly induced by S. frugiperda. Frist, the hydrogen peroxide (H2O2) and malondialdehyde (MDA) contents of infested maize leaves were significantly increased and then decreased to the level of the control. Furthermore, compared with the control leaves, the puncture force values and the total phenolics, total flavonoids, and 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one contents of infested leaves were significantly increased within a certain time. The superoxide dismutase and peroxidase activities of infested leaves were significantly increased in a certain period of time, while the catalase activities decreased significantly and then increased to the control level. The jasmonic acid (JA) levels of infested leaves were significantly improved, whereas the salicylic acid and abscisic acid levels changed less. Signaling genes associated with phytohormones and defensive substances including PAL4, CHS6, BX12, LOX1, and NCED9 were significantly induced at certain time points, especially LOX1. Most of these parameters changed greater in JG218 than in ZD958. Moreover, the larvae bioassay showed that S. frugiperda larvae weighed more on JG218 leaves than those on ZD958 leaves. These results suggested that JG218 was more susceptible to S. frugiperda than ZD958. Our findings will make it easier to develop strategies for controlling S. frugiperda for sustainable maize production and breeding of new maize cultivars with increased resistance to herbivores.

Drought is one of the most severe abiotic stresses that influence wheat production across the globe. Understanding the molecular regulatory network of wheat in response to drought is of great importance in molecular breeding. Noncoding RNAs influence plant development and resistance to abiotic stresses by regulating gene expression. In this study, whole-transcriptome sequencing was performed on the seedlings of two wheat varieties with contrasting levels of drought tolerance under drought and control conditions to identify long noncoding RNAs (lncRNAs), micro RNAs (miRNAs), and mRNAs related to drought stress and explore the potential lncRNA-miRNA-mRNA regulatory modules in controlling wheat drought stress response. A total of 1515 differentially expressed lncRNAs (DELs), 209 differentially expressed miRNAs (DEMs), and 20462 differentially expressed genes (DEGs) were identified. Of the 20462 DEGs, 1025 were identified as potential wheat drought resistance-related DEGs. Based on the regulatory relationship and expression patterns of DELs, DEMs, and DEGs, 10 DEL-DEM-DEG regulatory modules related to wheat drought stress response were screened, and preliminary expression verification of two important candidate modules was performed. Our results revealed the possible roles of lncRNA-miRNA-mRNA modules in regulatory networks related to drought tolerance and provided useful information as valuable genomic resources in molecular breeding of wheat.

Abstract High vigor seeds have greater yield potential than those with low vigor; however, long-term storage leads to a decline in this trait. The objective of this study was to identify quantitative trait loci (QTLs) for seed vigor-related traits under artificial aging conditions using a high-density genetic linkage map of wheat (Triticum aestivum) and mine the related candidate genes. A doubled haploid population, derived from a cross between Hanxuan 10 × Lumai 14, was used as the experimental material. Six controlled-environment treatments were set up, i.e. the seeds were aged for 0, 24, 36, 48, 60, and 72 h at a high temperature (48 °C) and under high humidity (relative humidity 100%). Eight traits including seed germination percentage, germination energy, germination index, seedling length, root length, seedling weight, vigor index, and simple vigor index were measured. With the prolongation of artificial aging treatment, these traits showed a continuous downward trend and significant correlations were observed between most of them. A total of 49 additive QTLs for seed vigor-related traits were mapped onto 12 chromosomes (1B, 2D, 3A, 3B, 3D, 4A, 4D, 5A, 5B, 5D, 6D, and 7A); and each one accounted for 6.01–17.18% of the phenotypic variations. Twenty-five pairs of epistatic QTLs were detected on all chromosomes, except for 5D, 6A, and 7D, and each epistasis accounted for 7.35–26.06% of the phenotypic variations. Three additive QTL hot spots were found on chromosomes 5A, 5B, and 5D, respectively. 13 QTLs, QGEe5B, QGIe5B, QSLc5B, QSLd5B, QSLf5B, QRLd5B, QRLe5B, QRLf5B, QVId5B, QVIe5B, QVIf5B, QSVId5B, and QSVIe5B, were located in the marker interval AX-94643729 ~ AX-110529646 on 5B and the physical interval 707,412,449–710,959,479 bp. Genes including TRAESCS5B01G564900, TRAESCS5B01G564200, TRAESCS5B01G562600, TraesCS5B02G562700, TRAESCS5B01G561300, TRAESCS5B01G561400, and TRAESCS5B01G562100, located in this marker interval, were found to be involved in regulating the processes of carbohydrate and lipid metabolism, transcription, and cell division during the germination of aging seeds, thus they were viewed as candidate genes for seed viability-related traits. These findings provide the basis for the seed-based cloning and functional identification of related candidate genes for seed vigor.

In the process of predicting the remaining cutter life, the deep-learning method such as convolutional neural network does not consider the time correlation of different degradation states, which directly affects the accuracy of the remaining cutter life prediction. To extract the features with time-series information to predict the remaining cutter life more effectively, this article proposes a new deep neural network, which is named the multi-scale cyclic convolutional neural network. In the multi-scale cyclic convolutional neural network, a multi-scale cyclic convolutional layer is constructed to memorize the degradation state at different moments and to mine the timing characteristics of multiple sensor data. Multi-scale features are extracted through multi-scale convolution, and the convergence of parameters is improved by layer-by-layer training and fine-tuning. Finally, the remaining cutter life is predicted based on the features. The comparison with the published prediction methods of convolutional neural network and recurrent neural network models proves that our method (multi-scale cyclic convolutional neural network) is superior in improving the precision and accuracy of remaining cutter life prediction. This method breaks through the limitations of the convolutional neural network prediction model in this field and provides a theoretical basis for evaluating the remaining service life of the cutter.

The photosynthesis of wheat glumes makes important contributions to the yield. Stomata play a crucial role in regulating photosynthesis and transpiration in plants. However, the genetic base of wheat glume stomata is not fully understood. In this study, stomatal length (SL), stomatal width (SW), stomatal density (SD), potential conductance index (PCI) of stomata, stomatal area (SA), and stomatal relative area (SRA) were measured in different parts of wheat glumes from a doubled haploid (DH) population and their parents. Quantitative trait loci (QTLs) of these traits were anchored on a high-density genetic linkage map of the DH population. A total of 61 QTLs for stoma-related traits were mapped onto 16 chromosomes, and each one accounted for 3.63 to 19.02% of the phenotypic variations. Two QTL hotspots were detected in two marker intervals, AX-109400932∼AX-110985652 and AX-108972184∼AX-108752564, on chromosome 6A. Five possibly candidate genes (TraesCS6A02G105400, TraesCS6A02G106400, TraesCS6A02G115100, TraesCS6A02G115400, and TraesCS6A02G116200) for stoma-related traits of wheat glumes were screened out , according to their predicted expression levels in wheat glumes or spikes. The expression of these genes may be induced by a variety of abiotic stresses. These findings provide insights for cloning and functional characterization of stoma-related candidate genes in wheat glumes.

Background To assess whether acute kidney injury (AKI) is independently associated with hospital mortality in ICU patients with sepsis, and estimate the excess AKI-related mortality attributable to AKI. Methods We analyzed adult patients from two distinct retrospective critically ill cohorts: (1) Medical Information Mart for Intensive Care IV (MIMIC IV; n = 15,610) cohort and (2) Wenzhou (n = 1,341) cohort. AKI was defined by Kidney Disease: Improving Global Outcomes (KDIGO) criteria. We applied multivariate logistic and linear regression models to assess the hospital and ICU mortality, hospital length-of-stay (LOS), and ICU LOS. The excess attributable mortality for AKI in ICU patients with sepsis was further evaluated. Results AKI occurred in 5,225 subjects in the MIMIC IV cohort (33.5%) and 494 in the Wenzhou cohort (36.8%). Each stage of AKI was an independent risk factor for hospital mortality in multivariate logistic regression after adjusting for baseline illness severity. The excess attributable mortality for AKI was 58.6% (95% CI [46.8%–70.3%]) in MIMIC IV and 44.6% (95% CI [12.7%–76.4%]) in Wenzhou. Additionally, AKI was independently associated with increased ICU mortality, hospital LOS, and ICU LOS. Conclusion Acute kidney injury is an independent risk factor for hospital and ICU mortality, as well as hospital and ICU LOS in critically ill patients with sepsis. Thus, AKI is associated with excess attributable mortality.

Abstract AP2/ERF is a plant‐specific transcription factor superfamily regulating plant growth, development and responses to multiple stresses. However, the roles of ERF genes in the growth and development of wheat (Triticum aestivum L.) remain elusive. In this study, a novel ERF gene TaERF73 was cloned from wheat. qRT‐PCR analysis showed that TaERF73 is predominantly expressed in roots. It responds to treatments of auxin, MeJA, ABA, low temperature and drought stresses. Ectopic expression of TaERF73 in rice caused short root length, indicating that TaERF73 is a negative regulator of root growth. Four SNPs were detected in TaERF73‐4B coding region through sequence polymorphism analysis. A dCAPS (derived cleaved amplified polymorphic sequence) molecular marker was developed based on the SNP at 119 bp (G/C) of TaERF73‐4B. Association analysis between genotypes and agronomic traits revealed that Hap‐4B‐2 is a haplotype of TaERF73‐4B associated with shorter plant height, higher thousand‐grain weight and longer root depth. The distributions of haplotypes in ten Chinese major wheat zones suggested that Hap‐4B‐2 has been positively selected in the breeding process. Together, the ERF gene TaERF73 is associated with root depth, plant height and thousand‐grain weight under drought, heat and well‐watered conditions. The molecular marker developed in this study could be a valuable source for marker‐assisted selection and genetic improvement in wheat.

The vibration transmission characteristics of the bearing housing system are crucial for the system fault diagnosis based on vibration signals collected at various measuring points. To study its vibration transmission characteristics, a dynamic model of the rolling bearing housing system based on the elastic interface is established. The interference fit between the bearing outer ring and the bearing housing is modelled by contact pairs. The proposed model is verified by the experimental results, which demonstrate that the interference fit can be better simulated by contact pairs. Based on the comparisons between the vibration signals obtained from the defect point and the measuring points on the bearing surface, the transmission mechanism of the defect excitation and the generation mechanism of the bearing housing structural vibration are clarified. The change law of defect excitation through an interface and the effects of bearing operational conditions (load and speed) on the vibration signals of measuring points are summarized. The results show that the optimal measuring point on the bearing housing surface is the location that is closest to the defect when the bearing housing system is working under light loads or high speeds. However, when under low speeds, the preferred measuring points are the positions where the rigidity of the bearing housing structure is weak. The analysis results provide a theoretical basis for the sensor arrangement and improvement of fault diagnosis accuracy under different operating conditions.

Magnetic biochar (MBC) has the advantages including wide source of raw materials and low cost, and has become a potential adsorbent for water treatment, overcoming the shortcomings of biochar (BC) with the hard separation of solid and liquid. Peanut hull-derived magnetic biochar loaded with Fe _3 O _4 (Fe _3 O _4 /BC) was prepared by co-precipitation method. By means of material characterization and batch processing experiments, material properties and environmental factors affecting adsorption performance were investigated. The adsorption mechanism of Fe _3 O _4 /BC on malachite green (MG) was revealed using adsorption isotherms, adsorption kinetics and thermodynamics. The results showed that Fe _3 O _4 particles were uniformly loaded, the total pore volume was increased, surface oxygen-containing functional groups were formed, and the maximum adsorption capacity of the biochar reached 175.4 mg g ^−1 , 1.6 times of that before modification. In a wide PH range, Fe _3 O _4 /BC showed high adsorption performance for MG, and significant influence from ionic strength wasn’t found. Chemical adsorption was the main adsorption mechanism, including electrostatic interaction, cation exchange, hydrogen bonding and π - π interaction. The study of adsorption mechanism will promote the application of MBC in the removal of organic pollutants from water.

Feature extraction herein refers to using an appropriate wavelet basis to filter vibration signals with the aim to reveal fault transient characteristics, which underlies bearing fault diagnosis. Wavelet transform has developed into a well-established signal processing approach with wide applications in bearing fault diagnosis. Nevertheless, a suitable wavelet basis is essential for wavelet transform to perform its best. So far, numerous wavelet bases are available for bearing diagnosis, most of which, however, have a waveform analogous to that of impulse responses of a single-degree-of-freedom system. In fact, bearings are of multi-degree-of-freedom and not totally rigid. Furthermore, a specific wavelet basis is definitely unable to accommodate all bearing vibrations, given that fault characteristics vary with bearings’ operating conditions and fault types. As such, a simulated wavelet-driven personalized scheme is proposed to improve bearing fault diagnosis for contextualized engineering practical applications. For a specific bearing of interest, personalized finite element models (FEM) with various faults are constructed and corresponding fault-induced responses are then obtained. Afterward, FEM-based wavelet bases are formulated and specified by its discrete values from such responses. Taking NU306 bearing with inner or outer defect for example, FEM-based wavelet basis is applied to the corresponding experimental signals by means of wavelet filtering. The comparisons with adaptive Morlet and impulse wavelet demonstrate that the personalized FEM-based wavelet basis match very well with the fault-induced transients present in experimental bearing vibrations and thus have a promising superiority and expandability.

Implicit large-eddy simulation is employed to simulate the flow in an asymmetric plane diffuser at Re=9000. Flow separation exists near the throat and evolves to large-scale, unsteady separation in the expansion section and the downstream region. An unconventional flow control method, namely, a cylindrical Karman-vortex generator (KVG) with different sizes and locations that induces periodic spanwise vortex shedding, is set upstream of the throat to suppress the flow separation. An appropriately designed KVG can enhance the mixing of the outer flow and the low energy fluid near the wall region by the periodic shedding Karman-vortices, and effectively reduce the separation bubble size. For the present optimal case, the length and height of the separation bubble are decreased 50.4% and 90.9%, respectively. The static pressure recovery coefficient is also increased by about 50%. Moreover, the velocity and total pressure distributions at the end of the expansion section are more uniform with lower fluctuation in the case with KVG installed. An optimal KVG diameter DK is suggested to be 3–4% of the expansion section length LE. The gap ratio to the lower wall G/DK and the length ratio to the throat Lt/DK are suggested to be 2.0–3.0 and 5.0–10.0, respectively.

The discrete element method (DEM) was used to study the behavior of crushable angular gravel in the cyclic soil-structure interface test. Two shapes of agglomerates were simulated by filling two scanned angular gravels with spheres connected by bonds that were given the shear and normal strength complying with Gaussian distribution to simulate random flaws. The proportion of these two shapes to constitute a numerical sample was named composite pattern. Good agreement in terms of macromechanical behavior between DEM simulation and laboratory test results has been attained. Agglomerate breakage is deeply influenced by the interface shearing behavior and mainly occurs on the interface and the space nearby. Graphs of interface after shearing are introduced to directly and clearly reflect microbehavior of breakage. The evolution of microstructure including anisotropies and coordination numbers is significantly influenced by normal stress and agglomerate breakage, and composite pattern determines the magnitudes of shear force anisotropy and coordination numbers. The evolution of contact orientation distribution is the forming cause of the “adjustment phase,” during which once the shearing direction changes, the values of contact normal anisotropy and normal force anisotropy will slump to their nadir and then rise back again.

As one of the most successful applications of image analysis and understanding, face recognition has recently received significant attention, especially during the past few years. In order to construct an autonomous and robust biometric security system, this paper explores the application of face recognition technique in wireless sensor networks. Given the limited technological resources of sensor nodes, new challenges remain to be met. In this work, a facial component-based recognition mechanism is firstly applied to ensure the recognition accuracy. Secondly, in order to address the problem of resource constraints, a distributed scheme based on K-d trees is deployed for both the face image transmission and retrieval. According to the simulation results, the proposed method is capable of achieving considerable energy efficiency, while assuring the recognition accuracy.

Drought is one of the most severe abiotic stresses that influence wheat production across the globe. Understanding the molecular regulatory network of wheat in response to drought is of great importance in molecular breeding. Noncoding RNAs influence plant development and resistance to abiotic stresses by regulating gene expression. In this study, whole-transcriptome sequencing was performed on the seedlings of two wheat varieties with contrasting levels of drought tolerance under drought and control conditions to identify long noncoding RNAs (lncRNAs), micro RNAs (miRNAs), and mRNAs related to drought stress and explore the potential lncRNA-miRNA-mRNA regulatory modules in controlling wheat drought stress response. A total of 1515 differentially expressed lncRNAs (DELs), 209 differentially expressed miRNAs (DEMs), and 20462 differentially expressed genes (DEGs) were identified. Of the 20462 DEGs, 1025 were identified as potential wheat drought resistance-related DEGs. Based on the regulatory relationship and expression patterns of DELs, DEMs, and DEGs, 10 DEL-DEMDEG regulatory modules related to wheat drought stress response were screened, and preliminary expression verification of two important candidate modules was performed. Our results revealed the possible roles of lncRNAmiRNA-mRNA modules in regulatory networks related to drought tolerance and provided useful information as valuable genomic resources in molecular breeding of wheat. [ABSTRACT FROM AUTHOR]

Structural, elastic anisotropy, dynamical, and thermodynamic properties of U2Ti have been studied by employing density functional theory and density functional perturbative theory. The optimized lattice parameters a, c, unit volume V, bulk modulus B, and bond lengths dU-U, dU-Ti of U2Ti are in favorable agreement with the available experimental data and other theoretical values. The elastic constants under pressure were obtained using "energy-strain" method. The polycrystalline modulus, Poisson's ratio, brittle/ductile characteristics, Debye temperature and the integration of elastic wave velocities over different directions, and hardness under pressure are also evaluated successfully. The anisotropy of the directional bulk modulus and the Young's modulus is systematically predicted for the first time. It turns out that U2Ti should be stabilized mechanically up to 100 GPa, this compound just possesses slightly elastic anisotropy at zero pressure; however, the anisotropy becomes more and more significant with the increasing pressure. In particular, the phonon dispersion curves and phonon density of state under pressure are reported for the first time. The Raman and infrared-active phonon modes at Γ point are further assigned. Our results indicate that U2Ti is also stable dynamically up to 100 GPa. Additionally, within the calculated phonon density of states, the thermodynamic properties are predicted. [ABSTRACT FROM AUTHOR]