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Diabetes nephropathy (DN) is the leading cause of end-stage renal disease (ESRD) worldwide, and podocyte injury is the central contributor to the progression of DN. Despite the emerging evidence that has established the importance of podocyte endoplasmic reticulum (ER) stress in the pathogenesis of DN, abnormal protein O-GlcNAcylation is also augmented. Currently, the mechanism associating these two hyperglycemia-induced disorders remains poorly understood. This study intended to elucidate whether ER stress drives hyper-protein O-GlcNAcylation to cause podocyte injury in DN. We used both type 1 and type 2 DN models to confirm the occurrence of ER stress and excessive protein O-GlcNAcylation, and then podocyte purification was also conducted for further investigation. Nephroseq V5 data were mined and in vitro studies were applied to reveal the involvement of ER stress and hyper-O-GlcNAcylation in podocyte injury. Our results indicated that ER stress was induced in both type 1 and type 2 DN, and the human RNA-seq data from Nephroseq V5 showed that O-GlcNAcylation-related genes were significantly upregulated in the DN patients. We further demonstrated that ER stress occurred prior to hyper-O-GlcNAc modification and that pharmacologically inhibited protein O-GlcNAcylation can help decrease the podocyte apoptosis induced by hyperglycemia. Together, these discoveries will aid in uncovering the activation of the ER stress–O-GlcNAcylation axis in podocyte injury under DN, which will help open up new therapeutic approaches for preventing DN progression.

The vision-based fruit recognition and localization system is the basis for the automatic operation of agricultural harvesting robots. Existing detection models are often constrained by high complexity and slow inference speed, which do not meet the real-time requirements of harvesting robots. Here, a method for apple object detection and localization is proposed to address the above problems. First, an improved YOLOX network is designed to detect the target region, with a multi-branch topology in the training phase and a single-branch structure in the inference phase. The spatial pyramid pooling layer (SPP) with serial structure is used to expand the receptive field of the backbone network and ensure a fixed output. Second, the RGB-D camera is used to obtain the aligned depth image and to calculate the depth value of the desired point. Finally, the three-dimensional coordinates of apple-picking points are obtained by combining two-dimensional coordinates in the RGB image and depth value. Experimental results show that the proposed method has high accuracy and real-time performance: F1 is 93%, mean average precision (mAP) is 94.09%, detection speed can reach 167.43 F/s, and the positioning errors in X, Y, and Z directions are less than 7 mm, 7 mm, and 5 mm, respectively.

The effects of inoculating plant growth promoting rhizobacteria (PGPR) and soil water deficits on crop growth and physiology remain largely unknown. Here, the responses of leaf gas exchange, growth, and water use efficiency (WUE) of tomato plants to Bacillus pumilus (B.p.) inoculation under four irrigation strategies (I1-I4) were investigated in a greenhouse. Results showed that soil water deficits, especially at I4 (20%, v/v), significantly decreased leaf stomatal conductance (gs), transpiration rate (Tr), and photosynthetic rate (An), and the decrease of gs and Tr were more pronounced than An. Reduced irrigation regimes significantly lowered dry matter and plant water use both in the non-B.p. control and the B.p. plants, while reduced irrigation significantly increased plant WUE, and B.p. inoculation had little effect on this parameter. Synergistic effects of PGPR and deficit irrigation on leaf gas exchange, leaf abscisic acid content, and stomatal density were found in this study, and specifically, B.p. treated plants at I4 possessed the highest WUE at stomatal and leaf scales, suggesting that B.p. inoculation could optimize water use and partly alleviate the negative effects of soil water deficit. These findings provide useful information for effective irrigation management and the application of PGPR in agriculture in the future.

β2 integrins are transmembrane receptors that exist widely in human immune cells and participate in pathological processes such as chronic inflammation, thrombosis, and malignant tumor formation. They mainly mediate intercellular adhesion, coordinate the ingestion of extracellular matrix components, and regulate cytoskeleton formation, thereby regulating cell signaling. Osteoarthritis (OA) is a chronic joint disease that causes joint pain and increases disease burden; it has a high prevalence among populations worldwide. Previous studies have reported that β2 integrins are overexpressed in OA and may play an essential role in the occurrence of OA. The important roles of β2 integrins in the maturation and differentiation of osteoclasts, the regulation of bone homeostasis, and the polarization and migration of macrophages have also been reported. The present review aims to highlight the role of β2 integrins in OA pathogenesis and outline their potential for serving as therapeutic targets.

The objective of this study was to explore the effects of plant growth-promoting rhizobacteria (PGPR), strain Bacillus licheniformis, with softwood biochar amendment on potato growth and water use efficiency (WUE) under a deficit irrigation (DI) regime. A pot experiment was conducted in a greenhouse. The results showed that PGPR improved leaf gas exchange rates, including photosynthesis rate, stomatal conductance and transpiration rate at early seedling stage, while tended to depress these parameters gradually until final harvest. The effects of biochar on plant leaf physiology, plant growth and WUE were not evident. Plants were more affected by DI than PGPR inoculation and biochar amendment. DI significantly decreased leaf gas exchange rates after exposure to water treatment for around three weeks, and the negative effect was eliminated at final harvest. At final harvest, DI significantly decreased leaf area, specific leaf area, dry mass of leaf and stem, total dry mass, dry mass increment and plant water use. The synergistical effect of PGPR strain Bacillus licheniformis and DI on plant growth and WUE were not observed in our study. WUE was solely improved by DI, indicating that, compared to PGPR inoculation, DI was a more effective measure to enhance plant WUE.

Internal erosion can trigger severe engineering disasters, such as the failure of embankment dams and uneven settlement of buildings and sinkholes. This paper comprehensively reviewed the mechanisms of soil internal erosion studied by numerical simulation, which can facilitate uncovering the internal erosion mechanism by tracing the movement of particles. The initiation and development of internal erosion are jointly influenced by the geometric, mechanical, and hydraulic conditions, which determine the pore channels and force chains in soil. The geometric conditions are fundamental to erosion resistance, whereas the mechanical conditions can significantly change the soil erosion resistance, and the hydraulic conditions determine whether erosion occurs. The erosion process can be divided into particle detachment, transport, and clogging. The first is primarily affected by force chains, whereas the latter two are mostly affected by the pore channels. The stability of the soil is mainly determined by force chains and pore channels, whereas the hydraulic conditions act as external disturbances. The erosion process is accompanied by contact failure, force chain bending, kinetic energy burst of particles, and other processes due to multi-factor coupling.

The two most important aspects of material research using deep learning (DL) or machine learning (ML) are the characteristics of materials data and learning algorithms, where the proper characterization of materials data is essential for generating accurate models. At present, the characterization of materials based on the molecular composition includes some methods based on feature engineering, such as Magpie and One-hot. Although these characterization methods have achieved significant results in materials research, these methods based on feature engineering cannot guarantee the integrity of materials characterization. One possible approach is to learn the materials characterization via neural networks using the chemical knowledge and implicit composition rules shown in large-scale known materials. This article chooses an adversarial method to learn the composition of atoms using the Generative Adversarial Network (GAN), which makes sense for data symmetry. The total loss value of the discriminator on the test set is reduced from 4.1e13 to 0.3194, indicating that the designed GAN network can well capture the combination of atoms in real materials. We then use the trained discriminator weights for material characterization and predict bandgap, formation energy, critical temperature (Tc) of superconductors on the Open Quantum Materials Database (OQMD), Materials Project (MP), and SuperCond datasets. Experiments show that when using the same predictive model, our proposed method performs better than One-hot and Magpie. This article provides an effective method for characterizing materials based on molecular composition in addition to Magpie, One-hot, etc. In addition, the generator learned in this study generates hypothetical materials with the same distribution as known materials, and these hypotheses can be used as a source for new material discovery.

A simple and fast high-performance liquid chromatography (HPLC) fingerprint method combining reference standard extract for the identification of bilberry extract was developed and validated. Six batches of bilberry extract collected from different manufactures were used to establish the HPLC fingerprint. Other berry extracts—such as blueberry extracts, mulberry extracts, cranberry extracts, and black rice extracts—were also analyzed for their HPLC chromatograms. The fingerprints of five batches of bilberry extract showed high similarities, while one batch was distinguished from others. Additionally, the content of anthocyanin Cyanidin-3-O-glucoside (Cy-3-glc) in each berry extract was analyzed and compared. The results indicate that this HPLC fingerprint method, combining reference standard extracts, could be used for the authentication and quality control of bilberry extracts.

In this paper, a hybrid neural network (HNN) that combines a convolutional neural network (CNN) and long short-term memory neural network (LSTM) is proposed to extract the high-level characteristics of materials for critical temperature (Tc) prediction of superconductors. Firstly, by obtaining 73,452 inorganic compounds from the Materials Project (MP) database and building an atomic environment matrix, we obtained a vector representation (atomic vector) of 87 atoms by singular value decomposition (SVD) of the atomic environment matrix. Then, the obtained atom vector was used to implement the coded representation of the superconductors in the order of the atoms in the chemical formula of the superconductor. The experimental results of the HNN model trained with 12,413 superconductors were compared with three benchmark neural network algorithms and multiple machine learning algorithms using two commonly used material characterization methods. The experimental results show that the HNN method proposed in this paper can effectively extract the characteristic relationships between the atoms of superconductors, and it has high accuracy in predicting the Tc.

The synthesis and structural analysis of (Me3SiC5H4)TiCl2(OAr) [OAr = O-2,6-iPr2-4-RC6H2; R = H, SiEt3] revealed that it exhibits higher catalytic activities than (tBuC5H4)TiCl2(OAr), Cp*TiCl2(OAr), with efficient comonomer incorporation in ethylene/styrene copolymerization in the presence of a methylaluminoxane (MAO) cocatalyst. The catalytic activity in the copolymerization increased upon increasing the charged styrene concentration along with the increase in the styrene content in the copolymers, whereas the activities of other catalysts showed the opposite trend. (Me3SiC5H4)TiCl2(O-2,6-iPr2C6H3) displayed the most suitable catalyst performance in terms of its activity and styrene incorporation, affording amorphous copolymers with styrene contents higher than 50 mol% (up to 63.6 mol%) and with random styrene incorporation confirmed by 13C-NMR spectra.

The coastal regions of Fujian, characterized by a subtropical maritime monsoon climate, experience a high frequency of windy days throughout the year, which significantly impacts residents’ lives. Local traditional villages, through long-term practical exploration, have developed a unique “maze-like” spatial layout adapted to withstand harsh wind conditions. This study aims to quantitatively analyze the climatic adaptability advantages of this traditional layout, providing theoretical support for the protection of historical cultural heritage and guidance for modern village construction. The methodology includes field wind measurement for data acquisition, construction of current and regularized divergent models, and comparative numerical simulations under scenarios of strong winter winds and typhoons. The results indicate that wind speeds within traditional villages are generally lower. The layout’s nonlinear roads and clusters of buildings form multiple buffer zones that effectively reduce wind speeds. In contrast, areas in the divergent model experience excessively high wind speeds, impacting outdoor activity safety and comfort. The traditional “maze-like” layout encapsulates the climate adaptation wisdom of ancestors, enhancing wind environment regulation, thermal comfort, and disaster resilience. This layout concept merits promotion and innovative application in the new era to construct livable, green, and sustainable human environments.

This article reports on the recent mining and production status of ruby in Longido, Tanzania. Faceted-grade rubies and their matrix from Longido Area, Tanzania, were investigated by standard gemological testing, including FTIR, UV-VIS, Raman spectra, and LA-ICP-MS. Microscopic observations revealed dense needle-like and triangular inclusions, distinct growth lines, and color banding as typical inclusions. In agreement with the Raman results, the transmission FTIR spectrum confirmed the presence of aluminum hydroxide. The Raman spectra identified associated minerals and inclusions, including zoisite, parasites, feldspar within the matrix, rutile, and diaspore in the ruby host. The chemistry analysis revealed a high amount of Cr and relatively low iron as a good indicator of geographic origin.

The design of the enclosure layout is crucial in establishing a comfortable wind environment in Chinese classic landscape gardens. The Ruins Park of the Old Summer Palace exemplifies the mountain construction techniques used in classical Chinese flat gardens, with a diverse and illustrative spatial layout of the hills. In this study, we focused on the earthen hill space of the Old Palace in the Summer Palace Ruins Park. We compared and analyzed the effects of different enclosure layouts of earthen hill spaces on the summer monsoon wind environment. This was achieved via on-site measurements and simulations using computational fluid dynamics (CFD). The results show the following: (1) The direction index of the enclosure layout of the earthen hill space affects wind speed, comfort, and ventilation. Increasing the index reduces speed and comfort but improves ventilation. (2) Increasing the density index of the enclosure layout of the earthen hill space leads to a decrease in wind speed and wind comfort and improved ventilation. (3) Conversely, increasing the area index of the enclosure layout of the earthen hill space results in an increase in wind speed, which can result in better wind comfort but can also lead to poor ventilation. Overall, the results suggest that careful consideration should be given to the enclosure layout of landscape gardens to ensure optimal wind conditions within the space.

In this study, seventeen faceted gem-quality chrysoberyls exhibiting an attractive canary yellow color were investigated using a variety of gemological, spectral, and chemical methods. Microscopic observation revealed the presence of distinct growth lines and inclusions, including CO2 fluids, carbon, and crystals of mineral such as calcite, quartz, sillimanite, and mica, identified by the Raman spectrum. The FTIR spectra showed the characteristic peaks of 2405 and 2160 cm−1 and a 3223 cm−1 peak in all samples, which can be accompanied by the 3112 cm−1 shoulder, 3301, and 3412 and 3432 cm−1 peaks. The UV-Vis spectra showed an Fe-related peak at 440 nm, along with the 650–660 nm band and the absorption band in the blue zone of visible light. Chemical analyses via EDXRF showed a composition poor in V and Cr and rich in Fe. The spectral and chemical results could help explain the origin of the canary yellow color, which originates from the abundant amount of Fe with very little influence from Cr and V.

Effectively inhibiting the formation of heterocyclic amines (HAs) and advanced glycation end products (AGEs) is crucial to human health. In the present study, chemical model systems were used to evaluate the inhibitory effects of seven hydrocolloids on HA and AGE formation. The results showed that hydrocolloids effectively inhibited the formation of two major AGEs. However, their inhibitory action against HA formation showed unexpected results, wherein alginic acid, carrageenan and konjac glucomannan promoted the formation of 2-Amino-1-methyl-6-phenylimidazo [4,5-b]pyridine (PhIP), harmane, norharmane and 2-amino-3,8-dimethyl-imidazo [4,5-f]-quinoline (MeIQx). Only chitosan and pectin showed significant inhibitory effects on HAs, reducing HA levels by 34.5–56.3% and 30.1–56.6%, respectively. In grilled beef patties, the addition of 1.5% chitosan and pectin significantly decreased AGE and HA content by 53.8–67.0% and 46.9–68.1%, respectively. Moreover, it had a limited impact on quality and sensory properties. Further mechanism studies conducted in model systems revealed that chitosan and pectin decreased the formation of key intermediates of AGEs and HAs. These findings suggest that chitosan and pectin are powerful inhibitors against AGE and HA formation with minimal impact on food quality. Therefore, their application in meat preparation and processing could effectively decrease human dietary exposure to HAs and AGEs.

Reversible insulator–metal transition (IMT) and structure phase change in vanadium dioxide (VO2) remain vital and challenging with complex polymorphs. It is always essential to understand the polymorphs that coexist in desired VO2 materials and their IMT behaviors. Different electrical properties and lattice alignments in VO2 (M) and VO2 (B) phases have enabled the creation of versatile functional devices. Here, we present polymorphous VO2 thin films with coexistent VO2 (M) and VO2 (B) phases and phase-dependent IMT behaviors. The presence of VO2 (B) phases may induce lattice distortions in VO2 (M). The plane spacing of (011)M in the VO2 (M) phase becomes widened, and the V-V and V-O vibrations shift when more VO2 (B) phase exists in the VO2 (M) matrix. Significantly, the coexisting VO2 (B) phases promote the IMT temperature of the polymorphous VO2 thin films. We expect that such coexistent polymorphs and IMT variations would help us to understand the microstructures and IMT in the desired VO2 materials and contribute to advanced electronic transistors and optoelectronic devices.

Cables or slip-rings are often used to power loads on a rotating unit in the rotation modulated inertial navigation system (RMINS). However, these power supply methods have the disadvantages of cable winding and slip ring friction and wear, which reduces the reliability and life of the RMINS. Therefore, this paper applies magnetic coupling resonant wireless power transfer (MCRWPT) technology to the RMINS to avoid the shortcomings of the above power supply methods. Furthermore, according to the structure and working characteristics of the RMINS, a simple design method of the MCRWPT system without any feedback control is proposed. Based on the ANSYS simulation, the magnetic shielding structure is designed to reduce magnetic leakage, and the efficiency of the MCRWPT system is optimized by designing the excitation frequency. Experiments verify the effectiveness of the proposed method. The experimental results show that the designed MCRWPT system can achieve an efficiency of 74.6% with an output power of 10 W and has been successfully applied to the uniaxial rotation module inertial navigation system. Finally, the design method of the MCRWPT system is simple, and it has guiding significance for the design of the wireless power transfer system in the RMINS.

Calibration and compensation techniques are essential to improve the accuracy of the strap-down inertial navigation system. Especially for the new uniaxial rotation module inertial navigation system (URMINS), replacing faulty uniaxial rotation modules introduces installation errors between modules and reduces navigation accuracy. Therefore, it is necessary to calibrate these systems effectively and compensate for the installation error between modules. This paper proposes a new self-calibration and compensation method for installation errors without additional information and equipment. Using the attitude, velocity, and position differences between the two sets of navigation information output from URMINS as measurements, a Kalman filter is constructed and the installation error is estimated. After URMINS is compensated for the installation error, the average of the demodulated redundant information is taken to calculate the carrier’s navigation information. The simulation results show that the proposed method can effectively assess the installation error between modules with an estimation accuracy better than 5”. Experimental results for static navigation show that the accuracy of heading angle and positioning can be improved by 73.12% and 81.19% after the URMINS has compensated for the estimated installation errors. Simulation and experimental results further validate the effectiveness of the proposed self-calibration and compensation method.

The traditional temperature modeling method is based on the full heating of the accelerometer to achieve thermal balance, which is not suitable for the cold start-up phase of the micro-accelerometer. For decreasing the complex temperature drift of the cold start-up phase, a new temperature compensation method based on a high-order Fourier transform combined model is proposed. The system structure and repeatability test of the micro digital quartz flexible accelerometer are provided at first. Additionally, we analyzed where the complex temperature drift of the cold start-up phase comes from based on the system structure and repeatability test. Secondly, a high-order temperature compensation model combined with K-means clustering and the symbiotic organisms search (SOS) algorithm is established with repeatability test data as training data. To verify the proposed temperature compensation model, a test platform was built to transmit the measured values before and after compensation with the proposed Fourier-related model and the other time-related model, which is also a model aiming at temperature compensation in the cold start-up phase. The experimental results indicate that the proposed method achieves better compensation accuracy compared with the traditional temperature compensation methods and the time-related compensation model. Furthermore, the compensation for the cold start-up phase has no effect on the original accuracy over the whole temperature range. The stability of the accelerometer can be significantly improved to about 30 μg in the start-up phase of different temperatures after compensation.

The aging of mammals is accompanied by the progressive atrophy of tissues and organs and the accumulation of random damage to macromolecular DNA, protein, and lipids. Flavonoids have excellent antioxidant, anti-inflammatory, and neuroprotective effects. Recent studies have shown that flavonoids can delay aging and prolong a healthy lifespan by eliminating senescent cells, inhibiting senescence-related secretion phenotypes (SASPs), and maintaining metabolic homeostasis. However, only a few systematic studies have described flavonoids in clinical treatment for anti-aging, which needs to be explored further. This review first highlights the association between aging and macromolecular damage. Then, we discuss advances in the role of flavonoid molecules in prolonging the health span and lifespan of organisms. This study may provide crucial information for drug design and developmental and clinical applications based on flavonoids.

Dead time estimation is important in the design process of quartz flexure accelerometers. However, to the authors’ knowledge, the dead time existing in quartz flexure accelerometers is not well investigated in conventional identification studies. In this paper, the dead time, together with the open-loop transfer function of quartz flexure accelerometers, is identified from step excitation experiments using two steps. Firstly, a monotonicity number was proposed to estimate the dead time. Analysis showed that the monotonicity number was robust enough to measurement noise and sensitive to step excitation. Secondly, parameters of the open-loop transfer function were identified using the least mean squares algorithm. A simulation example was applied to demonstrate the validity of the proposed method. The verified method was used to test a quartz flexure accelerometer. The experimental result shows that the dead time was 500 μs.

In order to solve the problems of filtering divergence and low accuracy in Kalman filter (KF) applications in a high-speed unmanned aerial vehicle (UAV), this paper proposed a new method of integrated robust adaptive Kalman filter: strong adaptive Kalman filter (SAKF). The simulation of two high-dynamic conditions and a practical experiment were designed to verify the new multi-sensor data fusion algorithm. Then the performance of the Sage−Husa adaptive Kalman filter (SHAKF), strong tracking filter (STF), H∞ filter and SAKF were compared. The results of the simulation and practical experiments show that the SAKF can automatically select its filtering process under different conditions, according to an anomaly criterion. SAKF combines the advantages of SHAKF, H∞ filter and STF, and has the characteristics of high accuracy, robustness and good tracking skill. The research has proved that SAKF is more appropriate in high-speed UAV navigation than single filter algorithms.

In practice, a high-dynamic vibration sensor is often plagued by the problem of drift, which is caused by thermal effects. Conversely, low-drift sensors typically have a limited sample rate range. This paper presents a system combining different types of sensors to address general drift problems that occur in measurements for high-dynamic vibration signals. In this paper, the hardware structure and algorithms for fusing high-dynamic and low-drift sensors are described. The algorithms include a drift state estimation and a Kalman filter based on a linear prediction model. Key issues such as the dimension of the drift state vector, the order of the linear prediction model, are analyzed in the design of algorithm. The performance of the algorithm is illustrated by a simulation example and experiments. The simulation and experimental results show that the drift can be removed while the high-dynamic measuring ability is retained. A high-dynamic vibration measuring system with the frequency range starting from 0 Hz is achieved. Meanwhile, measurement noise was improved 9.3 dB through using the linear-prediction-based Kalman filter.