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Hydrophobicity has been developed in many areas, whose potentials in drag reduction at microscale have attracted numerous attentions for expanding the practical applications in fields of on chip devices, materials synthesis, and enhanced heat transfer. In this article, we select polydimethylsiloxane (PDMS) as the base material, whose hydrophobic modifications have been well developed. Among them, hydrofluoric acid treated one shows great performance and leads us to two types of microchannels, the straight and U-shaped, with enhanced hydrophobicity (from 91° to 106°). The coefficients of the pressure drop are experimentally measured with the Reynolds number ranging from 0 to 300. The results illustrate that the drag reduction rate reaches at 37.8% for the straight microchannel and 26.8% for the U-shaped microchannel. With the increase in the Reynolds number, the drag reduction effect stays almost constant for the straight channel, while it decreases gradually for the U-shaped channel. The flow impingement induced by a centrifugal force has an important impact on the slip effect that grows with the Re. Next, we adopt the numerical method and the micro-particle imaging velocimetry measurement to analyze the drag reduction effect from perspectives of the slip length. We successfully derive the slip length model correlating the drag reduction effect. Our results not only achieve substantial drag reduction in PDMS microchannels, but also provide a quantitative correlation between hydrophobicity and drag reduction, offering a feasible strategy for extensive applications at microscale, such as fluid actuation, bio-chip analysis, and highly efficient cooling system. [ABSTRACT FROM AUTHOR]

This paper is concerned with the following L 2 -subcritical Kirchhoff-type equation − a + b ∫ R 2 | ∇ u | 2 d x s Δ u + V (x) u = μ u + β | u | 2 u , x ∈ R 2 , with ∫ R 2 | u | 2 d x = 1 . We give a detailed analysis of the limit property of the L 2 -normalized solution when exponent s tends toward 0 from the right (i.e., s ↘ 0 ). Our research extends previous works, in which the authors have displayed the limit behavior of L 2 -normalized solutions when s = 1 as a ↘ 0 or b ↘ 0 . [ABSTRACT FROM AUTHOR]

Accurately determining the seismic structure of the continental deep crust is crucial for understanding its geological evolution and continental dynamics in general. However, traditional tools such as surface waves often face challenges in solving the trade‐offs between elastic parameters and discontinuities. In this work, we present a new approach that combines two established inversion techniques, receiver function H‐κ stacking and joint inversion of surface wave dispersion and receiver function waveforms, within a Bayesian Monte Carlo (MC) framework to address these challenges. Demonstrated by synthetic tests, the new method greatly reduces trade‐offs between critical parameters, such as the deep crustal Vs, Moho depth, and crustal Vp/Vs ratio. This eliminates the need for assumptions regarding crustal Vp/Vs ratios in joint inversion, leading to a more accurate outcome. Furthermore, it improves the precision of the upper mantle velocity structure by reducing its trade‐off with Moho depth. Additional notes on the sources of bias in the results are also included. Application of the new approach to USArray stations in the Northwestern US reveals consistency with previous studies and identifies new features. Notably, we find elevated Vp/Vs ratios in the crystalline crust of regions such as coastal Oregon, suggesting potential mafic composition or fluid presence. Shallower Moho depth in the Basin and Range indicates reduced crustal support to the elevation. The uppermost mantle Vs, averaging 5 km below Moho, aligns well with the Pn‐derived Moho temperature variations, offering the potential of using Vs as an additional constraint to Moho temperature and crustal thermal properties. Plain Language Summary: Knowing the seismic structure of the deep crust helps us understand Earth's geological history and how continents evolve. However, traditional methods of studying the deep crust face challenges due to tradeoffs that can impact accuracies of the results. In this paper, we present a new approach that combines two existing techniques intending to measure the deep crust more accurately. We tested this method using both synthetic and real data and learned that it works better than previous methods. We applied this method to the Northwestern US and found that the results are aligned with the area's geology, suggesting that the new method is feasible to be applied on a regional scale. The new method provides a more accurate way to study the deep crust and improves the mapping of the uppermost mantle. Key Points: We have developed a new joint inversion approach that incorporates stacking of receiver function multiple phases with multiple data setsThe new approach reduces the trade‐offs and improves the determination of deep crustal shear velocity, Moho, and Poisson's ratioApplication of the new method to the northwestern US produces a more accurate model that exhibits geologically coherent structures [ABSTRACT FROM AUTHOR]

In this paper, we study the constrained minimization problem for an energy functional which is related to a Kirchhoff-type equation. For s = 1 , there many articles have analyzed the limit behavior of minimizers when η > 0 as b → 0 + or b > 0 as η → 0 + . When the equation involves a varying non-local term ∫ R 3 | ∇ u | 2 d x s , we give a detailed limit behavior analysis of constrained minimizers for any positive sequence { η k } with η k → 0 + . The present paper obtains an interesting result on this topic and enriches the conclusions of previous works. [ABSTRACT FROM AUTHOR]

Flowing characteristics of drag reduction are experimentally and numerically investigated with a combination of hydrophobic coating and various cavities in polydimethylsiloxane microchannels. Two typical types of cavities with different geometrical parameters, rectangular and triangular, are studied with a wide range of Reynolds numbers from 0 to 300. A promising hydrophobic processing method is proposed based on a comprehensive performance on surface morphology, water repellency, and structural distortion. In this method, hydrofluoric acid (40 wt. %) is adopted and the corrosion time is set to 5 min. The velocity field and streamlines are acquired by the micro-particle image velocimetry system and numerical models to explain the flow patterns in particular. The slip length is measured as 13.38 μm in the hydrophobic straight channel. For rectangular cavities, the drag reduction rate reaches nearly 14.1% under no-slip condition and 33.2% under slip condition. A critical turning point of the co-effect is found by numerical results when the slip length is about 15 μm, which is also determined by the cavities. The convergent and divergent angles of triangular cavities play a critical role in the pressure drop due to the competition of the vortex and flow impingement. A nonlinear model is developed based on the numerical results to predict Poiseuille number with the relevant important variables for a two-dimensional microchannel. Our results reveal the fundamental physics of flowing characteristics with the co-design of hydrophobicity and microstructures, predicting a composite design method for widespread applications in microfluids. [ABSTRACT FROM AUTHOR]

In this study, we conducted a systematic exploration of a micro-electromagnetic vibration energy harvester with a bi-magnet structure and microelectromechanical systems 3D coils. First, we establish a physical model of stiffness and damping characteristics based on the superposition principle for the bi-magnet structure which has also been verified experimentally. Then, we investigate the influence of magnet gap and air gap on the stiffness and the magnetic flux change rate, mainly focusing on the distance and the potential barrier between the two potential wells. Finally, we fabricate and assemble the bi-magnet VEH prototype and tested the output performance under 1 and 6g excitation, which correspond the intra-well vibration and inter-well vibration, respectively. The tested results show that under 1g excitation, the prototype can output 155.38 μW power with 32 Hz half-power bandwidth and 4939.06 μW·Hz integrated power, which are obviously higher than those for mono-magnet under same excitation. When the excitation raises to 6g, the output power is improved to 362.98 μW with the half power bandwidth and integrated power enhanced to 56 Hz and 9289.96 μW·Hz, respectively. The tested results also prove that the structure proposed in this study can significantly enhance the output performance compared with a mono-magnet structure and other published data. [ABSTRACT FROM AUTHOR]

Granulosa cells (GCs) are essential for follicular growth, oocyte maturation, and steroidogenesis in the ovaries. Interleukin (IL)-11 is known to play a crucial role in the decidualization of the uterus, however, the expression of the IL-11 system (IL-11, IL-11Rα, and gp130) in the bovine ovary and its exact role in GCs have not been extensively studied. In this study, we identified the IL-11 signaling receptor complex in the bovine ovary and investigated the regulatory effects and underlying mechanism of IL-11Rα on the proliferation and steroidogenesis of GCs. We observed that the IL-11 complex was highly expressed in the GCs of large follicles. IL-11Rα knockdown significantly inhibited GC proliferation by inducing cell cycle arrest at the G1 phase, along with a significant downregulation of proliferating cell nuclear antigen (PCNA) and Cyclin D1 (CCND1) protein, and induced GC apoptosis by significantly upregulating the ratio of BCL-2-associated X protein (BAX) and B-cell lymphoma-2 (BCL-2). In addition, IL-11Rα knockdown attenuated the Janus kinase (JAK) 1–signal transducer and activator of transcription 3 (STAT3) signaling, which is related to cell proliferation and apoptosis. Furthermore, the enzyme-linked immunosorbent assay (ELISA) indicated that IL-11Rα silencing decreased the basal and forskolin (FSK)-stimulated secretions of estradiol and progesterone in GC culture medium concomitantly with a remarkable decrease in cytochrome P450 family 19 subfamily A member 1 (CYP19A1) and steroidogenic acute regulatory protein (StAR). We subsequently determined that this reduction in steroidogenesis was in parallel with the decrease in phosphorylations of protein kinase A (PKA) substrates, cAMP-response element binding protein (CREB), extracellular regulated protein kinase (ERK) 1/2, and p38 mitogen-activated protein kinase (MAPK). Taken together, these data indicate that the effects of IL-11/IL-11Rα on the proliferation and steroidogenesis in bovine GCs is mediated by the JAK1-STAT3, PKA-CREB, p38MAPK, and ERK1/2 signaling pathways. Our findings provide important insights into the local action of the IL-11 system in regulating ovarian function. [ABSTRACT FROM AUTHOR]

Visible-infrared person re-identification (VIPR) has great potential for intelligent transportation systems for constructing smart cities, but it is challenging to utilize due to the huge modal discrepancy between visible and infrared images. Although visible and infrared data can appear to be two domains, VIPR is not identical to domain adaptation as it can massively eliminate modal discrepancies. Because VIPR has complete identity information on both visible and infrared modalities, once the domain adaption is overemphasized, the discriminative appearance information on the visible and infrared domains would drain. For that, we propose a novel margin-based modal adaptive learning (MMAL) method for VIPR in this paper. On each domain, we apply triplet and label smoothing cross-entropy functions to learn appearance-discriminative features. Between the two domains, we design a simple yet effective marginal maximum mean discrepancy (M 3 D) loss function to avoid an excessive suppression of modal discrepancies to protect the features' discriminative ability on each domain. As a result, our MMAL method could learn modal-invariant yet appearance-discriminative features for improving VIPR. The experimental results show that our MMAL method acquires state-of-the-art VIPR performance, e.g., on the RegDB dataset in the visible-to-infrared retrieval mode, the rank-1 accuracy is 93.24% and the mean average precision is 83.77%. [ABSTRACT FROM AUTHOR]

Hydrophobicity has been widely reported for its superior behavior in drag reduction, self-cleaning, and anti-corrosion in many areas. Especially in engineering design, the research of the unique property of the slip flow with complex flow patterns is essential for practical applications. In this paper, the flow characteristics of a superhydrophobic U-shaped microchannel are systematically investigated, as the curved part is a fundamental component in microfluids. A slip model is established based on theoretical and experimental solutions. Various types of U-shaped microchannels, radii of curvature, and contact angles are studied with a wide range of Reynolds numbers from 0 to 300. We propose a velocity distribution to examine the non-uniformity of slip velocity on the cross-section. This imbalance is improved with an increase in the apparent contact angle and flow rate, and a decrease in the radius of curvature. The secondary flow and vortices generated by the centrifugal force are enhanced, and their positions are changed due to the slippery boundary. The results show a considerable drag reduction from 10% to 40% with different contact angles. The variation of curvature does not have a decisive impact on the final performance when the surface wettability maintains a steady state. Our research elucidates the physical principle of the slip model in curved channels, showing extensive applications of hydrophobicity in the design of complex microchips and the optimization strategy of heat transfer systems. [ABSTRACT FROM AUTHOR]

Object re‐identification, such as vehicle re‐identification or pedestrian re‐identification, plays a significant role in intelligent video surveillance systems for public security. Due to viewpoint variations and appearance changes, both pedestrians and vehicles usually have complex intra‐class variations. However, most existing object re‐identification methods often use a sample‐level triplet loss function cooperating with a single‐proxy softmax loss function, which could not handle complex intra‐class variations well. In this paper, a sample‐proxy dual triplet (SPDT) loss function is proposed, which works with a multi‐proxy softmax (MPS) loss function. The MPS loss function is in charge of learning multiple proxies to represent a class. The SPDT loss function is responsible for enlarging inter‐class distances as well as shrinking intra‐class distances on both sample and proxy levels. Therefore, the method not only handles multi‐proxy intra‐class variations but also fully learns discrimination on samples and proxies. Experiments on two large datasets, that is, VeRi776 and DukeMTMC‐reID, demonstrate that the method is superior to state‐of‐the‐art object re‐identification approaches. [ABSTRACT FROM AUTHOR]

A miniature integrable transformer is an obstacle to the miniaturization of packaged power supply on chip (PwrSoC). This letter introduces a through-silicon via (TSV) high-aspect-ratio toroidal transformer manufactured using microelectro-mechanical systems and electroplating. The primary coil and secondary coil of the transformer are interleaved on the toroidal core cavity, which is entirely wrapped in silicon, and a 1.2 mm high toroidal Ni-Zn ferrite core is formed. A 15:15 turn transformer is fabricated with a compact coil size of Φ4.1 × 2 mm with an aspect ratio (ratio of TSV depth to diameter) of 20. Measurements show that it has an inductance of 105 to 115 nH in a high frequency range of 1 to 80 MHz and a coupling coefficient of ∼0.7 in the range of 1 MHz to >15 MHz. Compared to that of the transformer without the Ni-Zn ferrite core, the coupling coefficient of the toroidal transformer increases by 40% with an inductance increase of 20%. At a frequency of 14 MHz, the transformer has a maximum quality factor of 16.7. The small size, IC compatible manufacturing process and excellent performance at high-frequency of the transformer proposed, meet the further integrated and miniaturized needs of PwrSoC. [ABSTRACT FROM AUTHOR]

In this study, the performance of an electromagnetic vibration energy harvester (EM-VEH) based on micro-electro-mechanical systems 3D coils was presented theoretically and experimentally. The VEH employs two 3D coils and E-shape iron cores inserted into the coils to reduce the magnetic leakage and to improve the output power. In this structure, the planar spring stiffness and the attraction between the iron core and magnet are nonlinear, which can broad the bandwidth. In the theoretical work, a magnetic dipole model with the integral form was derived to describe the nonlinear interaction and estimate the dynamic response, which agreed well with the finite element method results. The influence of load resistance, excitation acceleration, and initial magnet offset (IMO) was measured and analyzed experimentally. The results showed that the IMO had a significant influence on the output performance. The maximum output power of one coil can reach 57.65 μW for 250 μm IMO based on 1 g excitation with the normalized power density (NPD) of 5.08 μW/cm3 g2, along with a half power bandwidth of 4 Hz. For a smaller IMO of 174 μm, the output power reduced at 22.23 μW with the same excitation condition, while the half power bandwidth was broadened to 13 Hz. With the increase in excitation, the output power and bandwidth can be improved while the NPD reduces. The tested results proved that the structure proposed in this study can significantly enhance the output performance compared with published data. [ABSTRACT FROM AUTHOR]

This paper presents a micro electromagnetic vibration energy harvester (VEH) that uses complementary metal-oxide-semiconductorcompatible 3D micro-electromechanical system coils and a ferromagnetic core to improve efficiency and output power. A systematic model is proposed to describe the nonlinear electromagnetic damping coefficient and nonlinear attraction between the magnet and the ferromagnetic core. The nonlinear model agrees well with the finite element calculation results. Then, a vibration model is established by considering nonlinear stiffness and damping coefficient to obtain the dynamic characteristics and output performance of the system. Furthermore, a numerical method is conducted to systematically investigate the influence of air gap and initial magnet offset under different excitation amplitudes. The simulation results indicate that with a smaller air gap, the output power is higher. Moreover, there is an optimal initial magnet offset in relation to the air gap to maximise the output power of the system. These conclusions and analysis models can be generalised and can be used as a guidance for the designs of similar structural devices. The results also show that the structure proposed in this study can significantly enhance the energy harvesting performance compared with published data of conventional VEHs. [ABSTRACT FROM AUTHOR]

Because of the difficulty in fabricating iron-core solenoid coils by micro electro-mechanical system (MEMS) processes, existing micromotors typically have an axial-flux structure with planar spiral coils or air-core solenoid coils. However, solenoid iron-core microcoils have a higher inductance and a lower magnetic resistivity than spiral coils and air-core solenoid coils. In this study, a radial-flux permanent magnet (PM) micromotor with 3D iron-core MEMS in-chip coils of high aspect ratio was designed and fabricated. The three-phase PM brushless direct current (BLDC) micromotor has four Nd-Fe-B magnet poles on a steel rotor and six solenoid Cu coils of high aspect ratio (coil height/line width = 14) in the silicon stator fabricated using MEMS processes. Iron cores were inserted into the coils, and a low-resistivity magnetic circuit was established. At 100 Hz, the inductance of a 15-turn coil was $13.2\mu \text{H}$. The coils were embedded tightly in the silicon substrate, resulting in a good heat dissipation performance and thus a high current-carrying capacity. The hexagonal sheet-type micromotor weighed 2.25 g with a volume of 586.5 mm3 before bearing packaging. The modeling results showed that at 10000 rpm, the torque was $676\mu \text{N}\cdot \text{m}$ and the power density was 314 W/kg. This micromotor incorporates a conventional large-scale BLDC motor structure and the proposed design will help improve the power density and efficiency of micromotors, thereby broadening their application prospects. [ABSTRACT FROM AUTHOR]

Southwest (SW) China is located in a transition site from the active Tibetan Plateau to the stable Yangtze craton, which has complicated tectonic deformation and severe seismic hazards. We combine data from ambient noise, teleseismic body and surface waves, and petroleum wells and seismic-reflection profiles to better constrain the crustal shear velocity structure in SW China. We jointly invert the Rayleigh wave dispersion (5–40 s period), Rayleigh wave ZH ratio (20–60 s period), and P -wave receiver function for 114 permanent stations with a stepwise linearized joint inversion method. Compared to previous tomography results, we observe higher shear velocity in the sedimentary rocks within the Sichuan Basin, which is consistent with sonic logging measurements. Our model reveals widespread low-velocity zones in the mid-lower crust, and their boundaries correlate well with major fault systems. Between two main mid-crustal low-velocity channels, a prominent high-velocity region surrounded by earthquakes is observed in the inner zone of the Emeishan large igneous province (ELIP) and around the Anninghe-Zemuhe fault zone. These observations are comparable to regional tomography results using very dense arrays. Based on the results, we suggest that mid-lower crustal ductile flow and upper-crustal rigid fault movement play equally important roles in controlling the regional deformation styles and earthquake distribution in SW China. Our results also resolve thick crust–mantle transition zones beneath the eastern Tibetan Plateau and the inner zone of the ELIP due to 'top-down' and 'bottom-up' crust–mantle interactions, respectively. Our new model can serve as a reference crustal model for future high resolution model construction in SW China. [ABSTRACT FROM AUTHOR]

In this letter, we report the design and measurement of a 3D solenoid inductor that is embedded in a Si substrate and can integrate an iron core. Various inductor designs were fabricated with good structural integrity and repeatability via a CMOS-compatible MEMS fabrication process. The average inductance and quality factor peak-to-peak variation of the inductors was below 10%, which indicates that the fabrication process is repeatable. Among the inductors without iron cores, the highest quality factor (37.6 at 21 MHz) was found in a 5-turn inductor, and the highest inductance and inductance density (respectively, 86.6 nH and 21.7 nH/mm2) were found in a 20-turn inductor. Among the iron-core inductors, the 15-turn inductor had an inductance of 1063 nH and an inductance density of 354.3 nH/mm2, nearly 18 times higher than the same design without an iron core, which is the highest inductance density for a MEMS microinductor to the best of our knowledge. This type of inductor is an important component in RF MEMS and electromagnetic power MEMS devices and can improve their performance and efficiency. [ABSTRACT FROM AUTHOR]

• Numerous DEGs were identified after pairwise comparison among samples. • Glycerolipid metabolism was key pathway for non-age-driven lower egg laying rate. • 10 genes were identified as hub genes involved in TAG formation. • TAG transportation was suppressed in chickens with lower egg laying rate. Yolk formation in liver is an important process for egg production in hens. The correlations between egg laying rate decline and liver function changes in Guangxi Ma chickens remain unclear. In this study, a total of 21,750 genes and 76,288 transcripts were identified in the RNA expression profiles isolated from liver tissues of 5 groups of Guangxi Ma chickens divided according to the age and egg laying rate. Numerous differential genes (DEGs) were identified after pairwise comparison among samples, and time series analysis categorization (age-related factors) revealed that down-regulated DEGs with aging were predominantly involved in lipid transportation and metabolic processes in the low egg laying rate groups. Notably, functional enrichment analysis confirmed that DGAT2 , LIPG , PNPLA2 , LPL , CEL , LIPC , DGKD , AGPAT2 , AGPAT1 and AGPAT3 were highlighted as hub genes in glycerolipid metabolism pathway, which may be an essential non-age related factors of egg laying rate by regulating the synthesis of triacylglycerol (TAG) in liver. Finally, we categorized DEGs in Guangxi Ma chickens with different egg laying rate caused by age-related factors and found that DEGs with different expression patterns performing different biological functions. The analysis of DEGs with lower egg laying rate caused by non-age related factors and showed that the transportation of TAG was suppressed. Furthermore, critical genes and pathways involved in the synthesis of TAG in livers were identified, which dynamically regulated the formation of yolk precursors. Our results expanded the knowledge of the molecular mechanisms of the yolk precursor synthesis in chicken livers. The results will be helpful to explore the factors that affect egg laying rate from the perspective of yolk synthesis and provide a theoretical basis for improving the egg production of Guangxi Ma chickens. [ABSTRACT FROM AUTHOR]

Integrated 2D spiral inductors possess low inductance per unit area, which limits their application range. However, the state of investigation into the lumped-element parameter extraction method for integrated 3D in-chip multi-turn solenoid inductors, which possess higher inductance per unit area, is inadequate. This type of inductor can thus not be incorporated into fast computer-aided design (CAD)-assisted circuit design. In this study, we propose a broadband two-port physics-based equivalent circuit model for 3D microelectromechanical system (MEMS) in-chip solenoid inductors that are embedded in silicon substrates. The circuit model was composed of lumped elements with specific physical meanings and incorporated complicated parasitics resulting from eddy currents, skin effects, and proximity effects. Based on this model, we presented a lumped-element parameter extraction method using the electronic design automation software package, Agilent Advanced Design System (ADS). This method proved to be consistent with the results of two-port testing at low to self-resonant frequencies and could thus be used in CAD-assisted circuit design. The lumped element value variations were analyzed based on the physical meaning of the elements with respect to variations in structures and the substrate resistivity of inductors. This provided a novel perspective in terms of the design of integrated in-chip solenoid inductors. [ABSTRACT FROM AUTHOR]

This paper investigates the relationship between the community of shared future, extra-role behavior, and innovation performance. This paper conducts an empirical study based on 334 valid sample data items of 53 technology-based small to medium enterprises (SMEs) in China. The data were subjected to structural equation analysis using SPSS 20.0 software. The results show that the community of shared future positively affects the extra-role behavior of employees and their innovation performance and has a positive impact on knowledge sharing behavior, voice behavior, and helping behavior. Knowledge sharing behavior, voice behavior, and helping behavior all play a mediating role between the community of shared future and employees' innovation performance. [ABSTRACT FROM AUTHOR]

Owing to its extremely low light absorption, black silicon has been widely investigated and reported in recent years, and simultaneously applied to various disciplines. Black silicon is, in general, fabricated on flat surfaces based on the silicon substrate. However, with three normal fabrication methods—plasma dry etching, metal-assisted wet etching, and femtosecond laser pulse etching—black silicon cannot perform easily due to its lowest absorption and thus some studies remained in the laboratory stage. This paper puts forward a novel secondary nanostructured black silicon, which uses the dry-wet hybrid fabrication method to achieve secondary nanostructures. In consideration of the influence of the structure's size, this paper fabricated different sizes of secondary nanostructured black silicon and compared their absorptions with each other. A total of 0.5% reflectance and 98% absorption efficiency of the pit sample were achieved with a diameter of 117.1 μm and a depth of 72.6 μm. In addition, the variation tendency of the absorption efficiency is not solely monotone increasing or monotone decreasing, but firstly increasing and then decreasing. By using a statistical image processing method, nanostructures with diameters between 20 and 30 nm are the majority and nanostructures with a diameter between 10 and 40 nm account for 81% of the diameters. [ABSTRACT FROM AUTHOR]

• The black pigment in 'Heishi' persimmon fruit skin was a kind of melanin. • This melanin deposits on the cell walls of the upper epidermis and subepidermal cells. • Transient overexpression of DkPPO promoted melanin synthesis in persimmon. In this study, the melanin in persimmon and its formation were investigated. Melanin was found to be deposited on the cell walls of the upper epidermis and subepidermal cells in persimmon skin and the isolated pigment appears to have lamellar structures. Diagnostic analysis of the isolated pigment showed results that were similar to those of melanin from other sources. Ultraviolet–visible spectroscopy revealed that the extracted skin pigment displayed a broadband, structureless absorption profile that increased progressively towards shorter wavelengths. The Fourier transform infrared spectroscopy assay revealed that melanin in persimmon skin exhibits many characteristic absorption peaks. The phenolic profile analysis suggested that the precursors of this pigment may include gallic acid, procyanidin B1, procyanidin B2, ferulic acid and epigallocatechin gallate. The PPO activity and DkPPO expression significantly increased during melanin formation, and transient overexpression of DkPPO promoted melanin synthesis. These results indicate that the isolated pigment was a type of melanin and that PPO plays a critical role in its formation. [ABSTRACT FROM AUTHOR]

Recent object re-identification (Re-ID) methods gain high efficiency via lightweight student models trained by knowledge distillation (KD). However, the huge architectural difference between lightweight students and heavy teachers causes students to have difficulties in receiving and understanding teachers' knowledge, thus losing certain accuracy. To this end, we propose a refiner-expander-refiner (RER) structure to enlarge a student's representational capacity and prune the student's complexity. The expander is a multi-branch convolutional layer to expand the student's representational capacity to understand a teacher's knowledge comprehensively, which does not require any feature-dimensional adapter to avoid knowledge distortions. The two refiners are 1×1 convolutional layers to prune the input and output channels of the expander. In addition, in order to alleviate the competition accuracy-related and pruning-related gradients, we design a common consensus gradient resetting (CCGR) method, which discards unimportant channels according to the intersection of each sample's unimportant channel judgment. Finally, the trained RER can be simplified into a slim convolutional layer via re-parameterization to speed up inference. As a result, we propose an expanding and refining hybrid compressing (ERHC) method. Extensive experiments show that our ERHC has superior inference speed and accuracy, e.g., on the VeRi-776 dataset, given the ResNet101 as a teacher, ERHC saves 75.33% model parameters (MP) and 74.29% floating-point of operations (FLOPs) without sacrificing accuracy.

As the basic units of the human body structure and function, cells have a considerable influence on maintaining the normal work of the human body. In medical diagnosis, cell examination is an important part of understanding the human function. Incorporating cell examination into medical diagnosis would greatly improve the efficiency of pathological research and patient treatment. In addition, cell segmentation and identification technology can be used to quantitatively analyze and study cellular components at the molecular level. It is conducive to the study of the pathogenesis of diseases and to the formulation of highly effective disease treatment programs. However, because cells are of diverse types, their numbers are huge, and they exist in the order of micrometers, detecting and identifying cells without using a deep learning-based computer program are extremely difficult. Therefore, the use of computers to study and analyze cells has a certain practical value. In this work, target detection theory using deep learning is applied to cell detection. A target recognition network model is built based on the faster region-based convolutional neural network (R-CNN) algorithm, and the anchor box is designed in accordance with the characteristics of the data set. Different design methods influence cell detection results. Using the object detection method based on our novel faster R-CNN framework to detect the cell image can help improve the speed and accuracy of cell detection. The method has considerable advantages in dealing with the identification of flowing cells.

In this paper, we propose an application of a compressive imaging system to the problem of wide-area video surveillance systems. A parallel coded aperture compressive imaging system is proposed to reduce the needed high resolution coded mask requirements and facilitate the storage of the projection matrix. Random Gaussian, Toeplitz and binary phase coded masks are utilized to obtain the compressive sensing images. The corresponding motion targets detection and tracking algorithms directly using the compressive sampling images are developed. A mixture of Gaussian distribution is applied in the compressive image space to model the background image and for foreground detection. For each motion target in the compressive sampling domain, a compressive feature dictionary spanned by target templates and noises templates is sparsely represented. An l(1) optimization algorithm is used to solve the sparse coefficient of templates. Experimental results demonstrate that low dimensional compressed imaging representation is sufficient to determine spatial motion targets. Compared with the random Gaussian and Toeplitz phase mask, motion detection algorithms using a random binary phase mask can yield better detection results. However using random Gaussian and Toeplitz phase mask can achieve high resolution reconstructed image. Our tracking algorithm can achieve a real time speed that is up to 10 times faster than that of the l(1) tracker without any optimization.