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In hydrated soft biological tissues experiencing edema, which is typically associated with various disorders, excessive fluid accumulates and is encapsulated by impermeable membranes. In certain cases of edema, an indentation induced by pressure persists even after the load is removed. The depth and duration of this indentation are used to assess the treatment response. This study presents a mixture theory-based approach to analyzing the edematous condition. The finite element analysis formulation was grounded in mixture theory, with the solid displacement, pore water pressure, and fluid relative velocity as the unknown variables. To ensure tangential fluid flow at the surface of tissues with complex shapes, we transformed the coordinates of the fluid velocity vector at each time step and node, allowing for the incorporation of the transmembrane component of fluid flow as a Dirichlet boundary condition. Using this proposed method, we successfully replicated the distinct behavior of pitting edema, which is characterized by a prolonged recovery time from indentation. Consequently, the proposed method offers valuable insights into the finite element analysis of the edematous condition in biological tissues.

The two-phase seepage fluid (i.e., air and water) behaviors in undisturbed granite residual soil (U-GRS) have not been comprehensively studied due to a lack of accurate and representative models of its internal pore structure. By leveraging X-ray computed tomography (CT) along with the lattice Boltzmann method (LBM) enhanced by the Shan–Chen model, this study simulates the impact of internal pore characteristics of U-GRS on the water–gas two-phase seepage flow behaviors. Our findings reveal that the fluid demonstrates a preference for larger and straighter channels for seepage, and as seepage progresses, the volume fraction of the water/gas phases exhibits an initial increase/decrease trend, eventually stabilizing. The results show the dependence of two-phase seepage velocity on porosity, while the local seepage velocity is influenced by the distribution and complexity of the pore structure. This emphasizes the need to consider pore distribution and connectivity when studying two-phase flow in undisturbed soil. It is observed that the residual gas phase persists within the pore space, primarily localized at the pore margins and dead spaces. Furthermore, the study identifies that hydrophobic walls repel adjacent fluids, thereby accelerating fluid movement, whereas hydrophilic walls attract fluids, inducing a viscous effect that decelerates fluid flow. Consequently, the two-phase flow rate is found to increase with then-enhanced hydrophobicity. The apex of the water-phase volume fraction is observed under hydrophobic wall conditions, reaching up to 96.40%, with the residual gas-phase constituting 3.60%. The hydrophilic wall retains more residual gas-phase volume fraction than the neutral wall, followed by the hydrophobic wall. Conclusively, the investigations using X-ray CT and LBM demonstrate that the pore structure characteristics and the wettability of the pore walls significantly influence the two-phase seepage process.

Upper limb movement is vital in daily life. A biomechanical simulation of the forearm with consideration of the physiological characteristics of the muscles is instrumental in gaining deeper insights into the upper limb motion mechanisms. In this study, we established a finite element model of the forearm, including the radius, biceps brachii, and tendons. We simulated the motion of the forearm resulting from the contraction of the biceps brachii by using a Hill-type transversely isotropic hyperelastic muscle model. We adjusted the contraction velocity of the biceps brachii muscle in the simulation and found that a slower muscle contraction velocity facilitated forearm flexion. Then, we changed the percentage of fast-twitch fibers, the maximum muscle strength, and the neural excitation values of the biceps brachii muscle to investigate the forearm flexion of elderly individuals. Our results indicated that reduced fast-twitch fiber percentage, maximum muscle strength, and neural excitation contributed to the decline in forearm motion capability in elderly individuals. Additionally, there is a threshold for neural excitation, below which, motion capability sharply declines. Our model aids in understanding the role of the biceps brachii in forearm flexion and identifying the causes of upper limb movement disorders, which is able to provide guidance for enhancing upper limb performance.

Tassel is an important part of the maize plant. The automatic detection and counting of tassels using unmanned aerial vehicle (UAV) imagery can promote the development of intelligent maize planting. However, the actual maize field situation is complex, and the speed and accuracy of the existing algorithms are difficult to meet the needs of real-time detection. To solve this problem, this study constructed a large high-quality maize tassel dataset, which contains information from more than 40,000 tassel images at the tasseling stage. Using YOLOv7 as the original model, a Tassel-YOLO model for the task of maize tassel detection is proposed. Our model adds a global attention mechanism, adopts GSConv convolution and a VoVGSCSP module in the neck part, and improves the loss function to a SIoU loss function. For the tassel detection task, the mAP@0.5 of Tassel-YOLO reaches 96.14%, with an average prediction time of 13.5 ms. Compared with YOLOv7, the model parameters and computation cost are reduced by 4.11 M and 11.4 G, respectively. The counting accuracy has been improved to 97.55%. Experimental results show that the overall performance of Tassel-YOLO is better than other mainstream object detection algorithms. Therefore, Tassel-YOLO represents an effective exploration of the YOLO network architecture, as it satisfactorily meets the requirements of real-time detection and presents a novel solution for maize tassel detection based on UAV aerial images.

To protect birds, it is crucial to identify their species and determine their population across different regions. However, currently, bird monitoring methods mainly rely on manual techniques, such as point counts conducted by researchers and ornithologists in the field. This method can sometimes be inefficient, prone to errors, and have limitations, which may not always be conducive to bird conservation efforts. In this paper, we propose an efficient method for wetland bird monitoring based on object detection and multi-object tracking networks. First, we construct a manually annotated dataset for bird species detection, annotating the entire body and head of each bird separately, comprising 3737 bird images. We also built a new dataset containing 11,139 complete, individual bird images for the multi-object tracking task. Second, we perform comparative experiments using a state-of-the-art batch of object detection networks, and the results demonstrated that the YOLOv7 network, trained with a dataset labeling the entire body of the bird, was the most effective method. To enhance YOLOv7 performance, we added three GAM modules on the head side of the YOLOv7 to minimize information diffusion and amplify global interaction representations and utilized Alpha-IoU loss to achieve more accurate bounding box regression. The experimental results revealed that the improved method offers greater accuracy, with mAP@0.5 improving to 0.951 and mAP@0.5:0.95 improving to 0.815. Then, we send the detection information to DeepSORT for bird tracking and classification counting. Finally, we use the area counting method to count according to the species of birds to obtain information about flock distribution. The method described in this paper effectively addresses the monitoring challenges in bird conservation.

This paper provides a systematic analysis of existing resource platforms, evaluating their advantages and drawbacks with respect to data privacy protection. To address the privacy and security risks associated with resource platform data, we propose a novel privacy protection algorithm based on chunking disorder. Our algorithm exchanges data within a specific range of chunk size for the position and combines the chunked data with the MD5 value in a differential way, thus ensuring data privacy. To ensure the security of the algorithm, we also discuss the importance of preventing client and server decompilation during its implementation. The findings of our experiments are as follows. Our proposed privacy-preserving algorithm is extremely secure and easy to implement. Our algorithm has a significant avalanche effect, maintaining values of 0.61–0.85, with information entropy being maintained at 4.5–4.9. This indicates that our algorithm is highly efficient without compromising data security. Furthermore, our algorithm has strong encryption and decryption time stability. The key length can be up to 594 bits, rendering it challenging to decrypt. Compared with the traditional DES algorithm, our algorithm has better security under the same conditions and approaches the levels of security offered by the AES and RC4 algorithms.

In order to solve the problems of excessive elastic deformation and excessive inertia force existed in the drive mechanism of traditional die-cutting machine, a lightweight drive rod with full symmetrical structure is proposed as the main force bearing component of the drive mechanism based on the kinematics analysis. The elastic deformation and inertia force of the lightweight drive rod are verified by static simulation analysis, and show that the weight of the drive rod is significantly reduced under the same deformation conditions, the traditional one. Further compared with, taking the minimum elastic deformation and lightweight as the optimization objectives, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to optimize the structural parameters of the drive rod. The results show that under the working conditions of 350 T die-cutting force and 125 r/min rotating speed, the elastic deformation of lightweight drive rod after structural optimization is smaller (the maximum deformation is 0.00988 mm) and the weight is lighter (27% less). The research data presented in this paper can be used as the theoretical basis for future research on die-cutting mechanism. The lightweight drive rod proposed in this study can be used in die-cutting devices with high die-cutting speed and high die-cutting accuracy.

Resins have enormous potential in the removal of naphthenic acids (NAs) from transformer oil due to their rich porosity and high mechanical and diversified functionality, whereas their poor adsorption capacity limits application. In this work, the polystyrene–diethylamine resin (PS−DEA−x) was prepared by grafting diethylamine (DEA) onto chloromethylated polystyrene (PS−Cl) resin to efficiently adsorb cyclopentane carboxylic acid from transformer oil for the first time. The characterization analysis results indicated that amine contents were significantly enhanced with the increase in DEA. Particularly, resin with a molar ratio of 1:5 depending on chloromethyl to DEA (PS−DEA−5) exhibited the highest amine contents and efficient adsorption of cyclopentane carboxylic acid (static adsorption capacity up to 110.0 mg/g), which was about 5 times higher than that of the pristine PS−Cl. The thermodynamic and kinetic studies showed that the adsorption behaviors could be well fitted to the Langmuir isotherm equation and pseudo−second−order rate equation. Moreover, it was found that 1 g of the PS−DEA−5 can decontaminate about 760 mL transformer oil to meet reuse standards by a continuous stream, indicating its potential application in industry.

With the rapid development of intelligent mobile terminals and communication technologies, location-based services (LBSs) have become an essential part of users’ lives. LBS providers upload and share the collected users’ location data. The more commonly used methods for location privacy protection are differential privacy and its extensions. However, the semantic information about location, which is an integral part of the location data, often contains sensitive user information. Most existing research methods have failed to pay enough attention to protecting the semantic information in the location data. To remedy this problem, two different scenarios for location semantic privacy protection methods are proposed in this paper to address single-point and continuous location queries. Simulation experiments on real social location check-in datasets, and comparison of three different privacy protection mechanisms, show that our solution demonstrates good service quality and privacy protection considering location semantics.

Growth and differentiation factor 15 (GDF15) is a cytokine reported to cause anorexia and weight loss in animal models. Neutralization of GDF15 was efficacious in mitigating cachexia and improving survival in cachectic tumor models. Interestingly, elevated circulating GDF15 was reported in patients with pulmonary arterial hypertension and heart failure, but it is unclear whether GDF15 contributes to cachexia in these disease conditions. In this study, rats treated with monocrotaline (MCT) manifested a progressive decrease in body weight, food intake, and lean and fat mass concomitant with elevated circulating GDF15, as well as development of right-ventricular dysfunction. Cotreatment of GDF15 antibody mAb2 with MCT prevented MCT-induced anorexia and weight loss, as well as preserved lean and fat mass. These results indicate that elevated GDF15 by MCT is causal to anorexia and weight loss. GDF15 mAb2 is efficacious in mitigating MCT-induced cachexia in vivo. Furthermore, the results suggest GDF15 inhibition is a potential therapeutic approach to alleviate cardiac cachexia in patients.

Patients with diffuse idiopathic skeletal hyperostosis (DISH) develop fractures of the vertebral bodies, even in minor trauma, because of the loss of flexibility, which causes difficulties in fusing vertebrae; therefore, the diagnosis of spine injuries may be delayed. We used the three-dimensional finite element method to add data on ossification to the healthy vertebral model in order to investigate how stress in intervertebral discs changes with bone shape and whether these changes present any risk factors. A healthy spine model and a DISH flat model (T8–sacrum) were generated from medical images. As an ossified hypertrophic model, T11–T12 was cross-linked with hypertrophic ossification, and hypertrophy was found to be 5 and 10 mm. An ossifying hypertrophic groove model (5 and 10 mm) was created at T11–T12 and T11–L1. A groove was created at the center of T12, and the radius of curvature of the groove was set to 1 and 2.5 mm. An extension force and flexion force were applied to the upper part of T8, assuming that external forces in the direction of flexion and extension were applied to the spine. Stresses were greater in the DISH flat model than in the healthy model. In the hypertrophic ossification model, the stress on the vertebral body was similar to greater ossification in extension and flexion. In the ossified hypertrophic groove model, the stress at the center of the groove increased. In DISH, vertebrae are more susceptible to stress. Furthermore, depending on the morphology of ossification, stresses on the vertebrae and intervertebral discs differed even with similar loads. An examination of ossification geometry may help surgeons decide the thoracolumbar spine’s stress elevated position in patients with DISH, thereby contributing to the understanding of the pathogenesis of pain.

The most common cause of lumbar spinal canal stenosis is age-related degenerative changes. The ligamentum flavum is said to become thicker and stiffer with age, based on several histological and cadaver studies. However, there are no studies determining the age-related changes of the mechanical properties of the ligamentum flavum in live patients. We examined the mechanical properties of the ligamentum flavum of live patients and evaluated the age-related changes. A total of 44 patients undergoing decompression surgery due to lumbar disease at our institute were included. The ligamentum flavum was harvested from the decompression site as a part of a necessary procedure for decompression. The tensile test was performed for the harvested ligamentum flavum within 24 h of harvest. Age-related changes in the stiffness of the ligamentum flavum were evaluated. Age was the only factor that showed a significant correlation with stiffness on multiple regression analysis. We demonstrated that the mechanical properties of the ligamentum flavum change with age.

In humans, the maternal endometrium participates in the physical and physiological interaction with the blastocyst to begin implantation. A bidirectional crosstalk is critical for normal implantation and then a successful pregnancy. While several studies have used animal models or cell lines to study this step, little knowledge was acquired to address the role of endometrial cells in humans. Here, we analyzed single-cell sequencing data from a previous study including 24 non-coculture endometrial stromal cells (EmSCs) and 57 EmSCs after coculture with embryos. We further explored the transcriptomic changes in EmSCs and their interactions with trophoblast cells after coculture. Differentially expressed gene (DEG) analysis showed 1783 upregulated genes and 569 downregulated genes in the cocultured embryos. Weight gene coexpression network and gene ontology analysis of these DEGs showed a higher expression of RAMP1, LTBP1, and LRP1 in EmSCs after coculture, indicating the enrichment of biological processes in blood vessel development and female pregnancy. These data imply that EmSCs start blood vessel development at the implantation stage. Compared with endometrium data in vivo at the implantation window, key pathways including epithelial cell development and oxygen response were involved at this stage. Further analysis using CellphoneDB shed light on the interactions between EmSCs and embryonic trophoblasts, suggesting the important role of integrins and fibroblast growth factor pathways during implantation. Taken together, our work reveals the synchronization signaling and pathways happening at the implantation stage involving the acquisition of receptivity in EmSCs and the interaction between EmSCs and trophoblast cells.

Systemic investigations are performed to comprehend the structural, optical, and electrical characteristics of four niobium (Nb) doped β-Ga2O3 crystals (β-Ga2O3:Nb) grown by the optical floating zone (OFZ) method. All of the β-Ga2O3:Nb crystals revealed monoclinic phases and good crystalline qualities. While the different Nb doped (i.e., 0.0001 mol%, 0.01 mol%, 0.1 mol% and 0.5 mol%) samples exhibited slightly changed bandgap energies Eg (≡ 4.72 eV, 4.73 eV, 4.81 eV, 4.68 eV)—the luminescence features indicated distinctive defect levels—affecting the electronic energy structure significantly. By increasing the Nb doping level from 0.0001 mol% to 0.1 mol%, the Fermi level (EF) moves closer to the bottom of the conduction band. For the sample with Nb doping 0.5 mol%—no further improvement is noticed in the electronic properties. Finally, the energy band diagrams of four samples are given.

Methane (CH4) emission and environmental controls of CH4-cycling microorganisms are unclear in inland floodplains. Here, we examined soil CH4 emissions and the community composition of CH4-cycling microorganisms under three vegetation types—mudflat (MF, no vegetation cover), Carex meadow (CM, mainly Carex brevicuspis), and reed land (RL, mainly Miscanthus sacchariflorus)—from water-adjacent areas to higher-elevation land in the Dongting Lake floodplain, China. The results showed that CH4 emission is the highest in CM, while significant absorption was observed in the RL site. The abundance ratio of methanogen/methanotroph was the highest in CM, intermediate in MF, and lowest in RL. The Methanosarcinaceae family represented the dominant methanogens in the three sampling sites (41.32–75.25%). The genus Methylocystis (60.85%, type II methanotrophs) was dominant in CM, while Methylobacter and Methylosarcina (type I methanotrophs) were the dominant genera in MF (51.00%) and RL (50.24%), respectively. Structural equation model analysis showed that methanogen and methanotroph abundance were affected by water table depth, soil water content, and pH indirectly through soil organic content, total nitrogen, microbial biomass carbon, and microbial biomass nitrogen. These results indicated that the Dongting Lake floodplain may change from a CH4 source to a CH4 sink with vegetation succession with an increase in elevation, and the methanogen/methanotroph ratio can be used as a proxy for CH4 emission in wetland soils. The continuous increase in reed area combined with the decrease in Carex meadow may mitigate CH4 emission and enhance the CH4 sink function during the non-flood season in the Dongting Lake floodplain.

Gravitational waves (GWs) encode important information about the mass of the source. For binary black holes (BBHs), the templates that are used to retrieve the masses normally are developed under the assumption of a vacuum environment. However, theories suggest that some BBHs form in gas-rich environments. Here, we study the effect of hydrodynamic drag on the chirp signal of a stellar-mass BBH and the impact on the measurement of the mass. Based on theoretical arguments, we show that the waveform of a BBH in gas resembles that of a more massive BBH residing in vacuum. The effect is important for those GW sources in the band of space-borne detectors but negligible for those in ground-based ones. Furthermore, we carry out a matched-filtering search of the best fitting parameters. We find that the best-fit chirp mass could be significantly greater than the real mass when the gas effect is ignored. Our results have important implications for the future joint observation of BBHs using both ground- and space-based detectors.

Phase and size of lanthanide-doped nanoparticles are the most important characteristics that dictate optical properties of these nanoparticles and affect their technological applications. Herein, we present a systematic study to examine the effect of alkaline earth doping on the formation of NaYF4 upconversion nanoparticles. We show that alkaline earth doping has a dual function of tuning particle size of hexagonal phase NaYF4 nanoparticles and stabilizing cubic phase NaYF4 nanoparticles depending on composition and concentration of the dopant ions. The study described here represents a facile and general strategy to tuning the properties of NaYF4 upconversion nanoparticles.

In this study, the coupled use of a double dielectric barrier discharge (DDBD) and CoOOH catalyst was investigated for the degradation of methylene blue (MB). The results indicated that the addition of CoOOH significantly promoted MB degradation performance compared to the DDBD system alone. In addition, both the removal rate and energy efficiency increased with an increase in CoOOH dosage and discharge voltage. After 30 min of discharge treatment in the coupled system (with CoOOH of 150 mg), the removal rate reached 97.10% when the discharge voltage was 12 kV, which was 1.92 times that in the single DDBD system. And when the discharge time was 10 min, the energy efficiency could reach 0.10 g (k·Wh)−1, which was 3.19 times better than the one in the single DDBD system. Furthermore, the addition of CoOOH could also significantly enhance the TOC and COD removal rates of MB. In the DDBD-coupled-with-CoOOH system, TOC and COD were 1.97 times and 1.99 times those of the single DDBD system after 20 min of discharge treatment with a discharge voltage of 12 kV and 100 mg of CoOOH. The main active substances detected in the coupled system indicated the conversion of the active species H2O2 and O3 into a more oxidizing ·OH was enhanced through the addition of a CoOOH catalyst, resulting in the more effective decomposition of MB and intermediate molecules.

The transformative wave of generative AI is reshaping the creative thinking processes of learners, posing a significant challenge to education and industry in cultivating technological literacy and creativity. This study delves into the exploration of how learners can effectively tackle new challenges by deconstructing fragments from a macro perspective and generating innovative methods or concepts. In the Scratch visual programming environment, learners in the self-regulated learning mode observed entire functioning projects, facilitating easy disassembly and learning, namely by using Code Decomposed by Learner (CDBL). A total of 104 fifth-grade students were divided into two learning scaffoldings: (1) domain-general, learning from the top down (CDBL-TD), and (2) domain-specific, learning from the bottom up (CDBL-BU). Students in the CDBL-TD group exhibited a high degree of completion, strong exploration abilities, and the willingness to experiment with unlearned functions. Although there was no significant difference in originality between the two groups, students in the CDBL-TD group showcased greater uniqueness in designing characters or items within the game. This study introduces a novel programming learning scaffolding, offering instructors a tool to guide students’ creativity and enhance their programming capabilities.

As information explosion and algorithms are proliferated in the digital age, computational thinking becomes more critical. Nevertheless, most activities that promote computational thinking are always presented in a programming or block language, which tends to horrify students. This study aimed to develop a series of non-programmed, computational-thinking training activities to demonstrate if they improve students’ computational thinking skills without writing code. In the meantime, it is checked whether students’ learning styles influence their outcomes. After an investigation consisting of a 16 h gamified learning session, we observed that students’ computational thinking skills improved overall. Furthermore, the initial learning style of the students influenced the effect of different dimensions of computational thinking in the learning procedures.

Computational thinking (CT) has become one of the critical goals of teaching CS programming courses. Computational skills consist of skills taken in a computational form in learning programming and dealing with daily life. More research adopted games to teach CT skills. This paper investigated two games, Little Alchemy 2 and Dr. Sudoku, to promote CS students’ CT skills and applied international Bebras tests to measure their CT skills. The results showed that CT skills in problem decomposition and pattern recognition could be improved via digital games. Thus, this study contributes to computing education using available digital games to promote CS college students’ CT abilities.

Due to the COVID-19 pandemic, courses for all ages in many countries moved online. The ability to use information technology fluently for learning has become a vital issue. Whether students can develop computational thinking (CT) literacy in online or offline learning environments is investigated. Two web games, Rummikub and Robozzle, are applied to teach computational thinking through Google Meet, Google Classroom, and offline live teaching. The results indicate that offline training activities are more appropriate for middle school students.

The study of black hole shadows by considering the surrounding kinds of matter has attracted interest in recent years. In this paper, we use the ray-tracing method to study shadows and photon spheres of renormalization group improved (RGI) black holes, taking into account the different thin spherical accretion models. We find that an increase in the parameters Ω and γ, which are excited by renormalization group theory, can decrease the event horizon and the radius of the photon sphere while increasing the effective potential. For static and infalling accretions, these results indicate that black hole shadows are related to the geometry of spacetime, and are nearly unaffected by spherical accretions. However, due to the Doppler effect, the shadow in the infalling case is darker than the static one, and the intensities of the photon sphere decay more slowly from the photon sphere to infinity. In addition, the peak intensities out of the shadow increase with the parameters Ω and γ. Finally, it can be seen that the effect of Ω on the shadow is more distinct by comparing it with that of γ at the same parameter level.

This study proposed a noninvasive blood glucose estimation system based on dual-wavelength photoplethysmography (PPG) and bioelectrical impedance measuring technology that can avoid the discomfort created by conventional invasive blood glucose measurement methods while accurately estimating blood glucose. The measured PPG signals are converted into mean, variance, skewness, kurtosis, standard deviation, and information entropy. The data obtained by bioelectrical impedance measuring consist of the real part, imaginary part, phase, and amplitude size of 11 types of frequencies, which are converted into features through principal component analyses. After combining the input of seven physiological features, the blood glucose value is finally obtained as the input of the back-propagation neural network (BPNN). To confirm the robustness of the system operation, this study collected data from 40 volunteers and established a database. From the experimental results, the system has a mean squared error of 40.736, a root mean squared error of 6.3824, a mean absolute error of 5.0896, a mean absolute relative difference of 4.4321%, and a coefficient of determination (R Squared, R2) of 0.997, all of which fall within the clinically accurate region A in the Clarke error grid analyses.

A computational fluid dynamics (CFD)-based simulation using a finite volume code for a full-appendage DARPA (Defense Advanced Research Projects Agency) SUBOFF model was investigated with a sliding mesh model in a multi-zone fluid domain. Unsteady Reynolds Averaged Navier–Stokes (URANS) equations were coupled with a Menter’s shear stress transport (SST) k-ω turbulence closure based on the Boussinesq approximation. In order to simulate unsteady motions and capture unsteady interactions, the sliding mesh model was employed to simulate flows in the fluid domain that contains multiple moving zones. The pressure-based solver, semi-implicit method for the pressure linked equations-consistent (SIMPLEC) algorithm was employed for incompressible flows based on the predictor-corrector approach in a segregated manner. After the grid independence test, the numerical simulation was validated by comparison with the published experimental data and other numerical results. In this study, the capability of the CFD simulation with the sliding mesh model was well demonstrated to conduct the straight-line towing tests by analyzing hydrodynamic characteristics, viz. resistance, vorticity, frictional coefficients, and pressure coefficients.

Digital advertising on social media officially surpassed traditional advertising and became the largest marketing media in many countries. However, how to maximize the value of the overall marketing budget is one of the most concerning issues of all enterprises. The content of the Facebook photo post needs to be analyzed effectively so that the social media companies and managers can concentrate on handling their fan pages. This research aimed to use text mining techniques to find the audience accurately. Therefore, we built a topic model recommendation system (TMRS) to analyze Facebook posts by sorting the target posts according to the recommended scores. The TMRS includes six stages, such as data preprocessing, Chinese word segmentation, word refinement, TF-IDF word vector conversion, creating model via Latent Semantic Indexing (LSI), or Latent Dirichlet Allocation (LDA), and calculating the recommendation score. In addition to automatically selecting posts to create advertisements, this model is more effective in using marketing budgets and getting more engagements. Based on the recommendation results, it is verified that the TMRS can increase the engagement rate compared to the traditional engagement rate recommended method (ERRM). Ultimately, advertisers can have the chance to create ads for the post with potentially high engagements under a limited budget.

SET7, serving as the only histone methyltransferase that monomethylates ‘Lys-4’ of histone H3, has been proved to function as a key regulator in diverse biological processes, such as cell proliferation, transcriptional network regulation in embryonic stem cell, cell cycle control, protein stability, heart morphogenesis and development. What′s more, SET7 is involved inthe pathogenesis of alopecia aerate, breast cancer, tumor and cancer progression, atherosclerosis in human carotid plaques, chronic renal diseases, diabetes, obesity, ovarian cancer, prostate cancer, hepatocellular carcinoma, and pulmonary fibrosis. Therefore, there is urgent need to develop novel SET7 inhibitors. In this paper, based on DC-S239 which has been previously reported in our group, we employed scaffold hopping- and 2D fingerprint-based similarity searches and identified DC-S285 as the new hit compound targeting SET7 (IC50 = 9.3 μM). Both radioactive tracing and NMR experiments validated the interactions between DC-S285 and SET7 followed by the second-round similarity search leading to the identification ofDC-S303 with the IC50 value of 1.1 μM. In cellular level, DC-S285 retarded tumor cell proliferation and showed selectivity against MCF7 (IC50 = 21.4 μM), Jurkat (IC50 = 2.2 μM), THP1 (IC50 = 3.5 μM), U937 (IC50 = 3.9 μM) cell lines. Docking calculations suggested that DC-S303 share similar binding mode with the parent compoundDC-S239. What′s more, it presented good selectivity against other epigenetic targets, including SETD1B, SETD8, G9a, SMYD2 and EZH2. DC-S303 can serve as a drug-like scaffold which may need further optimization for drug development, and can be used as chemical probe to help the community to better understand the SET7 biology.

Phidianidines A and B are two novel marine indole alkaloids bearing an uncommon 1,2,4-oxadiazole ring and exhibiting various biological activities. Our previous research showed that the synthesized phidianidine analogs had the potential to inhibit the activity of protein tyrosine phosphatase 1B (PTP1B), a validated target for Type II diabetes, which indicates that these analogs are worth further structural modification. Therefore, in this paper, a series of phidianidine derivatives were designed and rapidly synthesized with a function-oriented synthesis (FOS) strategy. Their inhibitory effects on PTP1B and T-cell protein tyrosine phosphatase (TCPTP) were evaluated, and several compounds displayed significant inhibitory potency and specific selectivity over PTP1B. The structure–activity relationship (SAR) and molecular docking analyses are also described.

This study designed a radio-frequency identification (RFID)-based Internet of Things (IoT) platform to create the core of a smart nest box. At the sensing level, we have deployed RFID-based sensors and egg detection sensors. A low-frequency RFID reader is installed in the bottom of the nest box and a foot ring RFID tag is worn on the leg of individual hens. The RFID-based sensors detect when a hen enters or exits the nest box. The egg-detection sensors are implemented with a resistance strain gauge pressure sensor, which weights the egg in the egg-collection tube. Thus, the smart nest box makes it possible to analyze the laying performance and behavior of individual hens. An evaluative experiment was performed using an enriched cage, a smart nest box, web camera, and monitoring console. The hens were allowed 14 days to become accustomed to the experimental environment before monitoring began. The proposed IoT platform makes it possible to analyze the egg yield of individual hens in real time, thereby enabling the replacement of hens with egg yield below a pre-defined level in order to meet the overall target egg yield rate. The results of this experiment demonstrate the efficacy of the proposed RFID-based smart nest box in monitoring the egg yield and laying behavior of individual hens.