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Stepwise photopolymerization is a miraculous strategy modulating the polymer skeleton and electro-optical properties of light modulators based on liquid crystal/polymer composites. However, owing to the indistinct polymerization mechanism and curing condition discrepancy, the required polymer structures and electro-optical properties are hard to be controlled precisely. Herein, a novel polymer-stabilized liquid crystal film based on acrylate/epoxy resin is proposed, fabricated and the relationships between preparation process, polymer content, polymer morphology and electro-optical properties are studied. The in-situ photopolymerization of acrylate/epoxy resin liquid crystalline polymer is fulfilled using cation photo-initiator UV 6976. The distinct photopolymerization speed between acrylate and epoxy resin benefits the polymer morphology control, and with accurate containment of the polymerization process and polymer composition, the superior electro-optical properties at a higher polymer content are acquired. The polymer morphology and electro-optical properties are influenced by the polymer content and mass ratio between acrylate and epoxy resin. The best electro-optical properties among samples are attained by controlling the mass ratio between acrylate and epoxy resin to 1:1, integrating higher densities of scattering centers and lower anchoring effect. With higher polymer content, the strategy of increasing the mass ratio of E6M benefits the improvement of E-O properties for alleviating polymer density. This work provides insights to stepwise polymerization of liquid crystalline monomers and offers a fancy strategy for the preparation of novel liquid crystal dimming films. [ABSTRACT FROM AUTHOR]

Metal thickness measurements are essential in various industrial applications, yet current non-contact ultrasonic methods face limitations in range and accuracy, hindering the widespread adoption of electromagnetic ultrasonics. This study introduces a novel combined thickness measurement method employing fuzzy logic, with the aim of broadening the applicational scope of the EMAT. Leveraging minimal hardware, this method utilizes the short pulse time-of-flight (TOF) technique for initial thickness estimation, followed by secondary measurements guided by fuzzy logic principles. The integration of measurements from the resonance, short pulse echo, and linear frequency modulation echo extends the measurement range while enhancing accuracy. Rigorous experimental validation validates the method's effectiveness, demonstrating a measurement range of 0.3–1000.0 mm with a median error within ±0.5 mm. Outperforming traditional methods like short pulse echoes, this approach holds significant industrial potential. [ABSTRACT FROM AUTHOR]

A polymer-stabilized liquid crystal (PSLC) device has been a promising candidate in several scenarios like smart vehicle windows and glass curtain walls in recent years due to its remarkable features like a fast switch from the initial transparent state to the scattering state with a rather low driving voltage, high transmittance at off-state, and broad viewing angle. The electro-optical characteristics of PSLC devices are determined by the synergistic attributions of liquid crystal (LC) molecules and the influence of the polymer network exerted on the movement of LC molecules. A systematic study of the influence of the polymer network on the movement of LC molecules is conducted, with the polymer network formed by methoxy/cyano/carboxyl monomers and diacrylate C6M. The polymer network morphology of PSLC film is greatly affected by the molecular structures and content of monoacrylic monomers. Additionally, the electro-optical performance and peel strength of PSLC films could be improved by modulating the molecular structures and morphology of polymer networks. PSLC devices containing carboxyl monomers show enhanced electro-optical performance and peel strength due to their directional filiform topology. This study might provide guidance for optimizing the performance of PSLC devices and establishing the relationship between the molecular structure, polymer network morphology, and electro-optical performance of reverse-mode dimming films. [ABSTRACT FROM AUTHOR]

The scattering of light after passing through a complex medium poses challenges in many fields. Any point in the collected speckle will contain information from the entire target plane because of the randomness of scattering. The detailed information of complex targets is submerged in the aliased signal caused by random scattering, and the aliased signal causes the quality of the recovered target to be degraded. In this paper, a new neural network named Adaptive Encoding Scattering Imaging ConvNet (AESINet) is constructed by analyzing the physical prior of speckle image redundancy to recover complex targets hidden behind the opaque medium. AESINet reduces the redundancy of speckle through adaptive encoding which effectively improves the separability of data; the encoded speckle makes it easier for the network to extract features, and helps restore the detailed information of the target. The necessity for adaptive encoding is analyzed, and the ability of this method to reconstruct complex targets is tested. The peak signal-to-noise ratio (PSNR) of the reconstructed target after adaptive encoding can be improved by 1.8 dB. This paper provides an effective reference for neural networks combined with other physical priors in scattering processes. [ABSTRACT FROM AUTHOR]

Purpose: This study investigates the relationship between product diversification strategy and cost stickiness, focusing on managerial overconfidence as a moderating factor. It aims to address a critical gap in the literature by providing empirical insights grounded in the Resource-Based View (RBV) theory, specifically examining firms listed on the Tehran Stock Exchange. Methodology: Utilizing a sample of 149 companies from the Tehran Stock Exchange in Iran spanning from 2015 to 2021, this study tests two hypotheses: (1) a positive relationship between product diversification and cost stickiness and (2) the amplification of this relationship by managerial overconfidence. Product diversification is quantified using the Herfindahl Index, while managerial overconfidence is measured through an investment-based index derived from capital expenditures. Cost stickiness is assessed by analysing the asymmetric behaviour of costs in response to changes in sales, focusing on how costs tend to remain high even when sales decrease. Findings: The empirical results substantiate both hypotheses, demonstrating a significant positive relationship between product diversification strategy and cost stickiness. Furthermore, managerial overconfidence amplifies this relationship, highlighting the role of internal resources and managerial perceptions in shaping cost behaviour. Originality: This study contributes substantially to the literature by being among the first to empirically examine the interplay between product diversification strategy, cost stickiness, and managerial overconfidence. Extending the RBV theory to cost behaviour and strategic management provides novel insights for scholars and practitioners in entrepreneurship, corporate strategy, and organizational behaviour. The findings underscore the importance of strategic choices and managerial traits in determining cost stickiness, offering valuable implications for financial analysts, auditors, and stakeholders. [ABSTRACT FROM AUTHOR]

There are various methods to evaluate the forming limit of a sheet, and these criteria can be classified as position-dependent, time-dependent, and position-time dependent according to the basis of judgment. However, these criteria have a single function and can only find the forming limit of the sheet and cannot determine the strain distribution, strain change, or fracture location during the sheet forming process. This paper introduces a time–location-dependent method, i.e., the spatial strain rate method, which is used to detect the onset of necking of a sheet. The spatial strain rate is directly based on the strain and can not only find the forming limit of the sheet but also depict the strain distribution and strain variation during the two phases of the experimental process—distributed instability and concentrated instability—as well as predict the location of sheet fracture. The spatial strain rate of AA5083 aluminum alloy of different widths was analyzed and verified in detail via Nakazima experiments using digital image correlation techniques and compared with the guidelines published in the literature in recent years. [ABSTRACT FROM AUTHOR]

As a fast and non-destructive spectroscopic analysis technique, Raman spectroscopy has been widely applied in chemistry. However, noise is usually unavoidable in Raman spectra. Hence, denoising is an important step before Raman spectral analysis. A novel spectral denoising method based on variational mode decomposition (VMD) was introduced to solve the above problem. The spectrum is decomposed into a series of modes (uk) by VMD. Then, the high-frequency noise modes are removed and the remaining modes are reconstructed to obtain the denoised spectrum. The proposed method was verified by two artificial noised signals and two Raman spectra of inorganic materials, i.e., MnCo ISAs/CN and Fe-NCNT. For comparison, empirical mode decomposition (EMD), Savitzky–Golay (SG) smoothing, and discrete wavelet transformation (DWT) are also investigated. At the same time, signal-to-noise ratio (SNR) was introduced as evaluation indicators to verify the performance of the proposed method. The results show that compared with EMD, VMD can significantly improve mode mixing and the endpoint effect. Moreover, the Raman spectrum by VMD denoising is more excellent than that of EMD, SG smoothing and DWT in terms of visualization and SNR. For the small sharp peaks, some information is lost after denoising by EMD, SG smoothing, DWT and VMD while VMD loses fewest information. Therefore, VMD may be an alternative method for Raman spectral denoising. [ABSTRACT FROM AUTHOR]

Multitarget tracking based on multisensor fusion perception is one of the key technologies to realize the intelligent driving of automobiles and has become a research hotspot in the field of intelligent driving. However, most current autonomous-vehicle target-tracking methods based on the fusion of millimeter-wave radar and lidar information struggle to guarantee accuracy and reliability in the measured data, and cannot effectively solve the multitarget-tracking problem in complex scenes. In view of this, based on the distributed multisensor multitarget tracking (DMMT) system, this paper proposes a multitarget-tracking method for autonomous vehicles that comprehensively considers key technologies such as target tracking, sensor registration, track association, and data fusion based on millimeter-wave radar and lidar. First, a single-sensor multitarget-tracking method suitable for millimeter-wave radar and lidar is proposed to form the respective target tracks; second, the Kalman filter temporal registration method and the residual bias estimation spatial registration method are used to realize the temporal and spatial registration of millimeter-wave radar and lidar data; third, use the sequential m-best method based on the new target density to find the track the correlation of different sensors; and finally, the IF heterogeneous sensor fusion algorithm is used to optimally combine the track information provided by millimeter-wave radar and lidar, and finally form a stable and high-precision global track. In order to verify the proposed method, a multitarget-tracking simulation verification in a high-speed scene is carried out. The results show that the multitarget-tracking method proposed in this paper can realize the track tracking of multiple target vehicles in high-speed driving scenarios. Compared with a single-radar tracker, the position, velocity, size, and direction estimation errors of the track fusion tracker are reduced by 85.5%, 64.6%, 75.3%, and 9.5% respectively, and the average value of GOSPA indicators is reduced by 19.8%; more accurate target state information can be obtained than a single-radar tracker. [ABSTRACT FROM AUTHOR]

The primary cause for the limited shelf life of litchi fruit is rapid pericarp browning and decay. This study aims to evaluate the storability of 50 litchi varieties and establish a linear regression model for pericarp browning and decay based on 11 postharvest physical and chemical indices after 9 days of storage at room temperature. The results indicated that the average value of the browning index and decay rate significantly increased to 3.29% and 63.84% of 50 litchi varieties at day 9, respectively. Different litchi varieties showed different variations in appearance indicators, quality indicators, and physiological indicators. Furthermore, principal component analysis and cluster analysis revealed that Liu Li 2 Hao exhibited the highest resistance to storage, whereas Dong Long Mi Li, Jiao Pan Li, E Dan Li 2 Hao, and Ren Shan Li were not resistant. Stepwise multiple regression analysis further demonstrated that the factors were highly correlated with the decay index, with a partial correlation coefficient of 0.437 between the effective index and the decay index. Therefore, pericarp thickness, relative conductivity, pericarp laccase activity, and total soluble solids were significant indicators for the comprehensive evaluation of litchi browning and decay, and relative conductivity was the significant determinant causing fruit browning. These findings provide a new perspective on the sustainable development of the litchi industry. [ABSTRACT FROM AUTHOR]

Fruit acidity determines the organoleptic quality and nutritive value of most fruits. In litchi, although the organic acid composition of pulps is known, the molecular mechanisms and genes underlying variation in fruit acidity remain elusive. Herein, developing pulps of two contrasting litchi varieties, Huaizhi (HZ, low-acidity) and Boye_No.8 (B8, high-acidity), were subjected to metabolomics and transcriptomics, and the dynamic metabolome and transcriptional changes were determined. Measurements revealed that the dominant acidity-related organic acid in litchi pulps is malate, followed in low levels by citrate and tartrate. Variation in litchi pulps' acidity is mainly associated with significant differences in malate and citrate metabolisms during fruit development. Malic acid content decreased by 91.43% and 72.28% during fruit ripening in HZ and B8, respectively. The content of citric acid increased significantly in B8, while in HZ it was reduced considerably. Differentially accumulated metabolites and differentially expressed genes analyses unveiled fumarate, succinate, 2-oxoglutarate, GABA (γ-aminobutyric acid), phosphoenolpyruvate, and citrate metabolisms as the key driving pathways of litchi fruits' acidity variation. The drastic malate and citrate degradation in HZ was linked to higher induction of fumarate and GABA biosynthesis, respectively. Thirty candidate genes, including three key genes (LITCHI026501.m2, fumarase; LITCHI020148.m5, glutamate decarboxylase; and LITCHI003343.m3, glutamate dehydrogenase), were identified for functional studies toward genetic modulation of litchi fruit acidity. Our findings provide insights into the molecular basis of acidity variation in litchi and provide valuable resources for fruit quality improvement. [ABSTRACT FROM AUTHOR]

Inventory leanness requires that firms minimize inventory mistreatment and misuse. A firm performance deteriorates because of high inventory misuse, and because of such an issue, the effect on the firm's credit rating can also be seen. This study examines the effect of inventory leanness on firms' credit ratings. It aims to create an understanding of the relationship between inventory leanness and the firm's financial performance and provides insight into the credit rating system of Pakistan. We analyze secondary Pakistan data between 2008 and 2017. Among the sixty firms on Pakistan Stock Exchange that are rated by PACRA, only thirty-eight have complete data available on their respective websites. By using panel data analysis, the results indicate that inventory leanness and credit ratings are positively related. In an added analysis, we evaluate the financial performance in the context of credit rating by using control variables (size, leverage, and capital intensity ratio) and dummy variables (loss and subordinate debt). Our results are consistent with earlier studies. [ABSTRACT FROM AUTHOR]

Although ~40% of screen-detected prostate cancers (PCa) are indolent, advanced-stage PCa is a lethal disease with 5-year survival rates around 29%. Identification of biomarkers for early detection of aggressive disease is a key challenge. Starting with 52 candidate biomarkers, selected from existing PCa genomics datasets and known PCa driver genes, we used targeted mass spectrometry to quantify proteins that significantly differed in primary tumors from PCa patients treated with radical prostatectomy (RP) across three study outcomes: (i) metastasis ≥1-year post-RP, (ii) biochemical recurrence ≥1-year post-RP, and (iii) no progression after ≥10 years post-RP. Sixteen proteins that differed significantly in an initial set of 105 samples were evaluated in the entire cohort (n = 338). A five-protein classifier which combined FOLH1, KLK3, TGFB1, SPARC, and CAMKK2 with existing clinical and pathological standard of care variables demonstrated significant improvement in predicting distant metastasis, achieving an area under the receiver-operating characteristic curve of 0.92 (0.86, 0.99, p = 0.001) and a negative predictive value of 92% in the training/testing analysis. This classifier has the potential to stratify patients based on risk of aggressive, metastatic PCa that will require early intervention compared to low risk patients who could be managed through active surveillance. [ABSTRACT FROM AUTHOR]