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Abstract Excess weight and obesity are often associated with ectopic adipose tissue accumulation in skeletal muscles. Intermuscular adipose tissue (IMAT) impairs muscle quality and reduces insulin-stimulated skeletal muscle glucose uptake. Although energy restriction and high protein intake can decrease IMAT, the effects and mechanisms of protein intake from an energy-restricted diet on protein and fat masses in skeletal muscle have received little attention. After establishing a diet-induced overweight and obese Sprague-Dawley rat model (half male and half female), rats were divided into five groups: normal control (NC; normal weight, general maintenance diet), model control (MC; overweight and obesity, high-fat diet), energy-restricted low protein (LP; overweight and obesity, 60% energy intake of NC, general maintenance diet), energy-restricted normal protein (NP; overweight and obesity, 60% energy intake of NC, high-protein diet 1), and energy-restricted high protein (HP; overweight and obesity, 60% energy intake of NC, high-protein diet 2). After 8 weeks, plasma and skeletal muscle (quadriceps femoris and gastrocnemius) samples were collected. Plasma levels of glucose, triglycerides, and hormones were analyzed, while contents of protein, fat, and factors associated with their synthesis and degradation were evaluated in skeletal muscles. Plasma concentrations of hormones contrasted protein and fat contents in skeletal muscles. Fat weights and contents of quadriceps femoris and gastrocnemius muscles in the NP group were significantly lower compared with LP and HP groups (P

This study aimed to develop a predictive equation for basal metabolic rate (BMR) in normal-weight Chinese adults and provide a reference for establishing the national recommended dietary energy intake. A new equation for BMR was derived from a sample of 516 normal-weight Chinese adults (men = 253, women = 263), and this sample was collected from two previous studies. Furthermore, the accuracy of this new equation and eight other previous predictive equations was reviewed. The agreement and reliability were compared in terms of bias, accuracy, the intraclass correlation coefficient, and Bland–Altman plots between predictive equations. In addition, the newly developed equation was further verified using a small independent sample, which contained 41 healthy Chinese adults (men = 21, women = 20). The measured BMR (mBMR) of all participants, measured using indirect calorimetry, was 1346.2 ± 358.0 kcal/d. Thirty participants were excluded based on Cook’s distance criteria (Cook’s distance of ≥0.008). Previous equations developed by Henry, Schofield, Harris–Benedict (H-B), Yang, and Hong overestimated the BMR of healthy Chinese adults. The present equation displayed the smallest average bias (0.2 kcal/d) between the mBMR and predicted basal metabolic rate (pBMR). The limits of agreement of the present equation from Bland–Altman plots were −514.3 kcal/d and 513.9 kcal/d, which is the most narrow and balanced limit of agreement. Moreover, in the verification of the testing database, the pBMR of the new equation was not significantly different from the mBMR, and the accuracy was 75.6%. Compared with pre-existing equations, the present equation is more applicable to the prediction of BMR in healthy Chinese adults. However, further studies are required to verify the accuracy of this new equation.

By conducting organic geochemical analysis of the samples taken from the drilled wells in Baiyun Sag of Pearl River Mouth Basin, China, the development characteristics of hydrocarbon source rocks in the sag are clarified. Reconstruct the current geothermal field of the sag and restore the tectonic-thermal evolution process to predict the type, scale, and distribution of resources in Baiyun Sag through thermal pressure simulation experiments and numerical simulation. The Baiyun Sag is characterized by the development of Paleogene shallow lacustrine source rocks, which are deposited in a slightly oxidizing environment. The source rocks are mainly composed of terrestrial higher plants, with algae making a certain contribution, and are oil and gas source rocks. Current geothermal field of the sag was reconstructed, in which the range of geothermal gradients is (3.5–5.2) °C/100 m, showing an overall increasing trend from northwest to southeast, with significant differences in geothermal gradients across different sub-sags. Baiyun Sag has undergone two distinct periods of extensional process, the Eocene and Miocene, since the Cenozoic era. These two periods of heating and warming events have been identified, accelerating the maturation and evolution of source rocks. The main body of ancient basal heat flow value reached its highest at 13.82 Ma. The basin modelling results show that the maturity of source rocks is significantly higher in Baiyun main sub-sag than that in other sub-sags. The Eocene Wenchang Formation is currently in the stage of high maturity to over maturity, while the Eocene Enping Formation has reached the stage of maturity to high maturity. The rock thermal simulation experiment shows that the shallow lacustrine mudstone of the Wenchang Formation has a good potential of generating gas from kerogen cracking with high gas yield and long period of gas window. Shallow lacustrine mudstone of the Enping Formation has a good ability to generate light oil, and has ability to generate kerogen cracking gas in the late stage. The gas yield of shallow lacustrine mudstone of the Enping Formation is less than that of shallow lacustrine mudstone of the Wenchang Formation and the delta coal-bearing mudstone of the Enping Formation. The numerical simulation results indicate that the source rocks of Baiyun main sub-sag generate hydrocarbons earlier and have significantly higher hydrocarbon generation intensity than other sub-sags, with an average of about 1 200×104 t/km2. Oil and gas resources were mainly distributed in Baiyun main sub-sag and the main source rocks are distributed in the 3rd and 4th members of Wenchang Formation. Four favorable zones are selected for the division and evaluation of migration and aggregation units: No. Panyu 30 nose-shaped structural belt, No. Liuhua 29 nose-shaped uplift belt and Liwan 3 nose-shaped uplift belt, No. gentle slope belt of Baiyun east sag, and No. Baiyun 1 low-uplift.

Abstract This study explores the feasibility, safety, and efficacy of percutaneous transluminal angioplasty (PTA) for reinserting tunneled cuffed catheters (TCC) with a Dacron sheath in the right internal jugular vein (RIJV) in hemodialysis patients with a history of prior RIJV catheterization and subsequent stenosis or occlusion of the RIJV, right innominate vein, and superior vena cava. Clinical data from 21 hemodialysis patients with dysfunctional vascular access who underwent PTA for reinsertion of TCC in the RIJVs from July 2020 to June 2023 at the First and Second Affiliated Hospitals of Bengbu Medical College were retrospectively analyzed. Clinical efficacy during hospitalization, postoperative TCC blood flow, and related complications during follow-up were observed. The procedure was successful in all 21 patients, with postoperative TCC blood flow meeting daily hemodialysis requirements. Only one case experienced acute bleeding with contrast agent extravasation at the intersection of the left and right innominate veins during sharp recanalization. No severe complications, such as arrhythmias, vascular rupture, pneumothorax, mediastinal hematoma, or pericardial tamponade, occurred during the procedures. Upon discharge, all patients exhibited satisfactory TCC blood flow (247.14 ± 11.46 ml/min). Postoperatively, TCC blood flow ranged between 200 and 260 ml/min, meeting the demands of regular hemodialysis. For patients with a history of repeated TCC or non-tunneled catheter (NTC) placement in the RIJV, reinserting TCC in the RIJVs through PTA is a safe and reliable technique. It effectively utilizes vascular resources and prevents vascular resource depletion associated with changing the venous catheter placement location.

Abstract Imaging technology based on detecting individual photons has seen tremendous progress in recent years, with broad applications in autonomous driving, biomedical imaging, astronomical observation, and more. Comparing with conventional methods, however, it takes much longer time and relies on sparse and noisy photon-counting data to form an image. Here we introduce Physics-Informed Masked Autoencoder (PI-MAE) as a fast and efficient approach for data acquisition and image reconstruction through hardware implementation of the MAE (Masked Autoencoder). We examine its performance on a single-photon LiDAR system when trained on digitally masked MNIST data. Our results show that, with $$1.8\times 10^{-6}$$ 1.8 × 10 - 6 or less detected photons per pulse and down to 9 detected photons per pixel, it achieves high-quality image reconstruction on unseen object classes with 90% physical masking. Our results highlight PI-MAE as a viable hardware accelerator for significantly improving the performance of single-photon imaging systems in photon-starving applications.

Abstract Background Transposition of the great arteries (TGA) is the most common cyanotic congenital heart defect in neonates but with low prenatal detection rate. This study sought to review the prenatal diagnosis, associated abnormalities, and mid-term postnatal outcomes of fetuses with TGA and investigate the integrated prenatal and postnatal management for TGA neonates. Methods A total of 134 infants prenatally diagnosed with TGA in Guangdong Provincial People’s Hospital, China, from January 2009 to December 2022 were included in the study. The prenatal ultrasound data and neonatal records were reviewed to assess the accuracy of prenatal diagnosis. Univariate and multivariate logistic and Cox analyses were used to identify risk factors associated with prognosis in such individuals. Results The population originated from 40 cities in 10 provinces in China, with integrated antenatal and postnatal management rate reaching 94.0% (126/134) and a high accuracy rate (99.3%) of prenatal primary diagnosis. The median period of follow-up was 1.6 [interquartile range (IQR) 0.1–4.3] years. There were 3 (2.2%) postnatal deaths, 118 (88.1%) patients undergoing arterial switch operation (ASO), 3 (2.2%) undergoing Rastelli operations and 5 (3.7%) doing stage operations. Of 118 patients receiving ASO, the major morbidity occurred in 64 patients (54.2%), and right ventricular outflow tract obstruction (RVOTO) in 31 (26.3%). In the multivariate logistic analysis, gestational ages at birth (OR = 0.953, 95% CI 0.910–0.991; p = 0.025) and cardiopulmonary bypass (CPB) time (OR = 1.010, 95% CI 1.000–1.030; p = 0.038) were identified as independent risk factors associated with major morbidity. In the Cox multivariate analysis, aortic cross-clamping time (HR = 1.030, 95% CI 1.000–1.050; p = 0.017) was identified as independent risk factor associated with RVOTO. Conclusion Earlier gestational ages at birth and longer CPB time are significantly associated with increased morbidity. Integrated prenatal and postnatal management is recommended for patients with prenatal diagnosis of TGA.

Abstract Background Gastric cancer represents a highly lethal malignancy with an elevated mortality rate among cancer patients, coupled with a suboptimal postoperative survival prognosis. Nectin-4, an overexpressed oncological target for various cancers, has been exploited to create antibody-drug conjugates (ADCs) to treat solid tumors. However, there is limited research on Nectin-4 ADCs specifically for gastric cancer, and conventional immunoglobulin G (IgG)-based ADCs frequently encounter binding site barriers. Based on the excellent tumor penetration capabilities inherent in nanobodies (Nbs), we developed Nectin-4-targeting Nb drug conjugates (NDCs) for the treatment of gastric cancer. Results An immunized phage display library was established and employed for the selection of Nectin-4-specific Nbs using phage display technology. Subsequently, these Nbs were engineered into homodimers to enhance Nb affinity. To prolong in vivo half-life and reduce immunogenicity, we fused an Nb targeting human serum albumin (HSA), resulting in the development of trivalent humanized Nbs. Further, we site-specifically conjugated a monomethyl auristatin E (MMAE) at the C-terminus of the trivalent Nbs, creating Nectin-4 NDC (huNb26/Nb26-Nbh-MMAE) with a drug-to-antibody ratio (DAR) of 1. Nectin-4 NDC demonstrated excellent in vitro cell-binding activities and cytotoxic efficacy against cells with high Nectin-4 expression. Subsequent administration of Nectin-4 NDC to mice bearing NCI-N87 human gastric cancer xenografts demonstrated rapid tissue penetration and high tumor uptake through in vivo imaging. Moreover, Nectin-4 NDC exhibited noteworthy dose-dependent anti-tumor efficacy in in vivo studies. Conclusion We have engineered a Nectin-4 NDC with elevated affinity and effective tumor uptake, further establishing its potential as a therapeutic agent for gastric cancer. Graphical abstract

Lithium (Li) metal batteries though with high energy density are still facing issues like Li dendrite growth, dead Li formation, and thick solid electrolyte interphase (SEI) formation, hindering their long-term stability. Recently, Li-Ag alloys have been reported to potentially address these challenges possibly due to their superior conductivity, lithiophilicity, and mechanical stability. In the pursuit of high-energy-density batteries, Li-Ag alloys typically employ a high Li content phase (γ1). In this study, we applied density functional theory (DFT) calculations to compare the thermodynamic stability, Li adsorption, and Li diffusion of Ag-rich Li-Ag alloy within the γ1 phase (AR-γ1), Ag-poor Li-Ag alloy within the γ1 phase (AP-γ1), and pure Li. AR-γ1 showed better thermodynamic stability and improved Li adsorption and diffusion properties compared to AP-γ1 and pure Li. Electrochemical tests further confirmed the advantages of AR-γ1 in terms of electrode kinetics and cell stability compared to AP-γ1 and pure Li. Our study offers guidance for the selection of the most suitable Li-Ag alloys that can be utilized in high-energy-density lithium batteries.

Abstract High-power inductors are fundamental components in high-power DC–DC converters, with their performance being a crucial metric of converter efficiency. This paper presents an in-depth analysis of a novel calculation method for the air gap length in such inductors. Taking into account the effects of air gap diffusion and the winding magnetic field, an expression for the air gap diffusion radius is derived, focusing on a distributed air gap structure. Furthermore, models for calculating the air gap and winding reluctance are developed, grounded in electromagnetic field theory. An equivalent magnetic circuit model, formulated based on Kirchhoff's second law, facilitates the proposed method for air gap length calculation. This study also involves the development of 3D models for both discrete and decoupled integrated inductors. The comparison between simulation outcomes and calculated air gap lengths indicates a maximum error of less than 8%, with the minimum error being as low as − 0.79%. Compared with traditional methods, the calculation method proposed in this paper has significant advantages. Additionally, the discrepancy between calculated values and experimental measurements is found to be 1.11%. These results validate the accuracy and applicability of the theoretical analysis and calculation method, underscoring their significance in the design and optimization of high-power DC–DC converters.

Wind power poses a challenge to the stability of the power grid due to its unpredictability and intermittency. This study aims to analyze the forecasting law and uncertainties of short-term wind farm power forecasting (WFPF) at various time scales, in order to support the stability of energy generation. To achieve this, we propose a framework for short-term WFPF and uncertainty analysis, utilizing the whale optimization algorithm (WOA), convolutional neural network-bidirectional long short-term memory network (CNN-BiLSTM), cloud model (CM), and non-parametric kernel density estimation (NPKDE). The data is trained using a hybrid model of CNN-BiLSTM with multiple convolution and pooling methods, while the parameters are optimized using the WOA algorithm. The uncertainty of WFPF is described qualitatively by the expectation, entropy, and hyper-entropy of the cloud model, and quantified through the confidence interval based on non-parametric kernel density estimation. Test results show that the proposed WOA-CNN-BiLSTM model achieves RMSE forecasting errors of 3.79%, 4.52%, and 5.12% at 4 hours, 24 hours, and 72 hours, respectively. The maximum peak errors are less than 10.5758MW, 21.128MW, and 20.0292MW, and are better than other models. Additionally, the WOA optimization performance is superior, consistent with the results described by the cloud model. Furthermore, the RMSE forecasting value of WFPF increases with the time scale, while the growth rate of RMSE decreases with the increase of time scale. This study provides valuable insights into the uncertainties of short-term WFPF and offers a robust framework for improving the stability of energy generation.

Osteoarthritis and psoriasis arthritis are two degenerative forms of arthritis that share similar yet also different manifestations at the histological, cellular, and clinical levels. Rheumatologists have marked them as two entirely distinct arthropathies. Given recent discoveries in disease initiation and progression, potential mechanisms, cellular signaling pathways, and ongoing clinical therapeutics, there are now more opportunities for discovering osteoarthritis drugs. This review summarized the osteoarthritis and psoriasis arthritis signaling pathways, crosstalk between BMP, WNT, TGF-β, VEGF, TLR, and FGF signaling pathways, biomarkers, and anatomical pathologies. Through bench research, we demonstrated that regenerative medicine is a promising alternative for treating osteoarthritis by highlighting significant scientific discoveries on entheses, multiple signaling blockers, and novel molecules such as immunoglobulin new antigen receptors targeted for potential drug evaluation. Furthermore, we offered valuable therapeutic approaches with a multidisciplinary strategy to treat patients with osteoarthritis or psoriasis arthritis in the coming future in the clinic.

Abstract Background Pancreatic cancer is a highly aggressive malignancy with limited treatment options and a poor prognosis. Trophoblast cell surface antigen 2 (TROP2), a cell surface antigen overexpressed in the tumors of more than half of pancreatic cancer patients, has been identified as a potential target for antibody–drug conjugates (ADCs). Almost all reported TROP2-targeted ADCs are of the IgG type and have been poorly studied in pancreatic cancer. Here, we aimed to develop a novel nanobody-drug conjugate (NDC) targeting TROP2 for the treatment of pancreatic cancer. Results In this study, we developed a novel TROP2-targeted NDC, HuNbTROP2-HSA-MMAE, for the treatment of TROP2-positive pancreatic cancer. HuNbTROP2-HSA-MMAE is characterized by the use of nanobodies against TROP2 and human serum albumin (HSA) and has a drug-antibody ratio of 1. HuNbTROP2-HSA-MMAE exhibited specific binding to TROP2 and was internalized into tumor cells with high endocytosis efficiency within 5 h, followed by intracellular translocation to lysosomes and release of MMAE to induce cell apoptosis in TROP2-positive pancreatic cancer cells through the caspase-3/9 pathway. In a xenograft model of pancreatic cancer, doses of 0.2 mg/kg and 1 mg/kg HuNbTROP2-HSA-MMAE demonstrated significant antitumor effects, and a dose of 5 mg/kg even eradicated the tumor. Conclusion HuNbTROP2-HSA-MMAE has desirable affinity, internalization efficiency and antitumor activity. It holds significant promise as a potential therapeutic option for the treatment of TROP2-positive pancreatic cancer. Graphical Abstract

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables. Therefore, the aim of this review is to give detailed outlines about the theory and principle of light penetration depth based on several emerging optical detection technologies and to focus primarily on its applications in the field of quality evaluation of fruits and vegetables, its future applicability in fruits and vegetables and the challenges it may face in the future.

In bone-milling surgical procedures, the intense friction between the tool and bone material often results in high cutting temperatures, leading to the thermal necrosis of bone cells. This paper aims to investigate the effect of micro-texture on the tribological properties of YG8 cemented carbide in contact with bone. The main objective is to guide the design of tool surface microstructures to reduce frictional heat generation. To minimize experimental consumables and save time, numerical simulations are first conducted to determine the optimal machining depth for the texture. Subsequently, micro-textures with different shapes and pitches are prepared on the surface of YG8 cemented carbide. These textured samples are paired with bovine cortical bone pins featuring various bone unit arrangements, and friction and wear tests are conducted under physiological saline lubrication. The experimental results indicate that the appropriate shape and pitch of the micro-texture can minimize the coefficient of friction. The parallel arrangement of bone units exhibits a lower coefficient of friction compared to the vertical arrangement. This study holds significant implications for the design and fabrication of future micro-texture milling cutters.

As a new kind of carbonaceous adsorbent, biochar has a good function of controlling VOCs. A series of biochar (BCx) and potassium carbonate activated biochar (KBC-x-y) were pre-pared from corncob for benzene adsorption. Thermogravimetric analysis, nitrogen adsorption-desorption, scanning electron microscopy (SEM) and elemental analysis (EA) were used to char-acterize the pyrolytic properties, specific surface area, pore volume and pore size, surface mor-phology and atomic percentage of the biochar (mass) samples. The effects of carboniza-tion/activation temperature on benzene adsorption were investigated by adsorption experiments. The results show that the specific surface area of biochar modified by potassium carbonate is up to 576.76 m2/g, the pore volume is 0.325 m3/g, and the maximum adsorption capacity of benzene is up to 82.51 mg/g (2.9 times higher than that of unmodified biochar). The carbonization temperature and adsorption capacity show a trend of normal distribution. The adsorption capacity increases with the increase of carbonization temperature, but the high carbonization temperature above 800 ℃ will lead to the clogging of pores, decrease in number, decrease in specific surface area and decrease in adsorption capacity. The adsorption capacity of biochar shows the same trend with the activation temperature under low/high carbonization temperature. After high-temperature carbonization (800 ℃), the optimum activation temperature is 400 ℃ (KBC-800-400). If the activation temperature is too high, it will lead to the fracture of micropore wall and the sintering effect of volatiles, thus reducing the adsorption capacity. Lower activation temperature fails to make K2CO3 fully react on the carbon surface. After low-temperature carbonization (400 ℃), the optimal activation temperature is (800 ℃). The adsorption performance of low-temperature carbonized high-temperature activated biochar (KBC-400-800) is better than that of high-temperature carbonized low-temperature activated biochar (KBC-800-400). It is possibly because the higher activation temperature facilitates the involvement of potassium carbonate in the reaction of the activation process in the case of low temperature car-bonization.

Dendrite formation, contact loss, and continuous formation of the solid electrolyte interphase (SEI) preclude the practical use of the energy-dense lithium (Li) metal. Li–Ag alloys have the potential to address these issues due to their exceptional lithiophilicity, outstanding mechanical stability, and moderate chemical stability. This study evaluates all phases in the Li–Ag phase diagram based on lithiation capacity, Li insertion, mechanical property, and chemical stability. Our findings suggest that Li4Ag is the most promising phase, and the Gibbs free energy of nucleation (∆Gnucle) for Li–Ag alloys is 3 to 5 orders of magnitude smaller compared to pure Li, resulting in uniform nucleation and deposition behavior. We proposed practical applications within the Li4Ag phases or from the Li9Ag4 to the Li4Ag phases, which may provide a usable capacity of 409 to 696 mAh/g, respectively. Experiments indicate that Li4Ag exhibits not only the smallest impedance but also the highest capacity retention compared to Li9Ag4 and pure Li. The study provides valuable guidance for the selection and application of Li-containing alloys in future battery development.

Lubricating grease plays an important role in the rolling screw transmission of the actuation system and is particularly concerned with the performance stability of long-term storage in aerospace applications. In this article, a batch of ball screws that were lying flat in the warehouse for about eight years were selected to extract lubricating grease from the screw raceway after being stored in situ. The oxidation performance, friction performance and rheological properties of lubricating grease were tested and compared to those of fresh grease to analyze and summarize the performance changes in lubricating grease. The transmission efficiency, friction torque, and temperature rise of ball screws without removing the original grease and those filled with fresh grease after cleaning were tested and compared. The impact of grease degradation on the transmission performance of ball screws was analyzed to provide a reference for ball screw lubrication schemes and further accelerated storage experimental design.

Urban underground pipeline networks are a key component of urban infrastructure, and a large number of older urban areas lack information about their underground pipelines. In addition, survey methods for underground pipelines are often time-consuming and labor-intensive. While the manhole cover serves as the hub connecting the underground pipe network with the ground, the generation of underground pipe network can be realized by obtaining the location and category information of the manhole cover. Therefore, this paper proposed a manhole cover detection method based on UAV aerial photography to obtain ground images, using image super-resolution reconstruction and image positioning and classification. Firstly, the urban image was obtained by UAV aerial photography, and then the YOLOv8 object detection technology was used to accurately locate the manhole cover. Next, the SRGAN network was used to perform super-resolution processing on the manhole cover text to improve the clarity of the recognition image. Finally, the clear manhole cover text image was input into the VGG16_BN network to realize the manhole cover classification. The experimental results showed that the manhole cover classification accuracy of this paper’s method reached 97.62%, which verified its effectiveness in manhole cover detection. The method significantly reduces the time and labor cost and provides a new method for manhole cover information acquisition.

Lidar multiple scattering measurements provide the probability distribution of the distance laser light travels inside snow. Based on an analytic two-stream radiative transfer solution, the present study demonstrates why/how these lidar measurements can be used to derive snow depth and snow density. In particular, for a laser wavelength with little snow absorption, an analytical radiative transfer solution is leveraged to prove that the physical snow depth is half of the average distance photons travel inside snow and that the relationship linking lidar measurements and the extinction coefficient of the snow is valid. Theoretical formulas that link lidar measurements to the extinction coefficient and the effective grain size of snow are provided. Snow density can also be derived from the multi-wavelength lidar measurements of the snow extinction coefficient and snow effective grain size. Alternatively, lidars can provide the most direct snow density measurements and the effective discrimination between snow and trees by adding vibrational Raman scattering channels.

Optical Ising machines provide a promising approach to solve complex optimization problems and hence are of broad interest in physics society. This paper constructs a nonlinear optical Ising machine with spatial light modulators to find distinct phase transitions, which demonstrates a platform for solving optimization problem in more efficient way.

In this paper, a novel global time-varying path planning (GTVP) method is proposed. In the method, real-time paths can be generated based on tunable Bezier curves, which can realize obstacle avoidance of manipulators. First, finite feature points are extracted to represent the obstacle information according to the shape information and position information of the obstacle. Then, the feature points of the obstacle are converted into the feature points of the curve, according to the scale coefficient and the center point of amplification. Furthermore, a Bezier curve representing the motion path at this moment is generated to realize real-time adjustment of the path. In addition, the 5-degree Bezier curve planning method consider the start direction and the end direction is used in the path planning to avoid the situation of abrupt change with oscillation of the trajectory. Finally, the GTVP method is applied to multi-obstacle environment to realize global time-varying dynamic path planning. Through theoretical derivation and simulation, it can be proved that the path planned by the GTVP method can meet the performance requirements of global regulation, real-time change and multi-obstacle avoidance simultaneously.

The detection and feedback of displacement and velocity significantly impact the control accuracy of the linear feed system. In this study, we propose a flexible and self-powered displacement sensor based on the triboelectric effect, designed for seamless integration into linear feed systems. The displacement sensor comprises two parts, the mover and stator, operating in a sliding mode. This sensor can precisely detect the displacement of the linear feed system with a large detection range. Additionally, the sensor is capable of real-time velocity detection of linear feed systems, with an error rate below 0.5%. It also offers advantages, such as excellent flexibility, compact size, stability, easy fabrication, and seamless integration, with linear feed systems. These results highlight the potential of the self-powered displacement sensor for various applications in linear feed systems.

In order to study the mode switching and fault reconfiguration of the 10 kW dual redundancy electromechanical servo system driven by differential when one channel fault occurs， through simulation analysis， the system parameters of transient response and frequency characteristic under the active- active working mode are compared with those under the active-standby working mode. The sinusoidal switching process of the active-active switching and active-standby switching are analyzed. The sinusoidal variation curves of the active-active switching mode and the active-standby switching mode are carried out by the test rig. Simulation comparison shows that， comparison with the active-standby working mode， it is found that the active-active working mode possesses better parameters of transient response and frequency characteristic. Consistent with simulation， the test shows that the switching time and oscillation process of switching at the zero point are longer and non-smoother than those of switching at the maximum displacement point. For the 10 kW electromechanical servo system with only internal friction and inertia load， either switching mode can be switched reliably.

The break-in operation of the brake unit of a differential redundant actuation system is of considerable importance to improve its reliability and safety. However, the operation will generate a large impact on the driven load, which may cause damage to the load, and hence, it needs to be analyzed in detail. In this study, we first analyzed in detail the different working modes of a differential redundant actuation system and their dynamic characteristics during the break-in process. Subsequently, a dedicated offline test platform for the load simulation of the actuation system was designed to simulate rudders, i.e., the main type of load for such an actuation system. The test platform was used to perform experimental testing on the impact characteristics of the break-in process on the load under different working modes of the actuation system, and the relevant test data were obtained and evaluated accordingly. The experimental results show that, when the differential redundant actuation system is in a multiple-degrees-of-freedom state with a single input and multiple outputs, the break-in process of the brake unit has the smallest impact on the load; furthermore, when the backup channel of the differential redundant actuation system is in a locked state, the break-in process of the brake unit has the largest impact on the load.

We report the detection and interferometric localization of the repeating fast radio burst (FRB) source FRB 20220912A during commissioning observations with the Deep Synoptic Array (DSA-110). Two bursts were detected from FRB 20220912A, one each on 2022 October 18 and 2022 October 25. The best-fit position is (R.A. J2000, decl. J2000) = (23:09:04.9, +48:42:25.4), with a 90% confidence error ellipse with radii ±2″ and ±1″ in R.A. and decl., respectively. The two bursts are polarized, and we find a Faraday rotation measure that is consistent with the low value of +0.6 rad m ^−2 reported by CHIME/FRB. The DSA-110 localization overlaps with the galaxy PSO J347.2702+48.7066 at a redshift z = 0.0771, which we identify as the likely host. PSO J347.2702+48.7066 has a stellar mass of approximately 10 ^10 M _⊙ , modest internal dust extinction, and a star formation rate likely in excess of 0.1 M _⊙ yr ^−1 . The host-galaxy contribution to the dispersion measure is likely ≲50 pc cm ^−3 . The FRB 20220912A source is therefore likely viewed along a tenuous plasma column through the host galaxy.

IntroductionHeat-clearing and detoxifying Chinese medicines have been documented to have anti-Alzheimer’s disease (AD) activities according to the accumulated clinical experience and pharmacological research results in recent decades. In this study, Fibraurea recisa Pierre (FRP), the classic type of Heat-clearing and detoxifying Chinese medicine, was selected as the object of research.Methods12 components with anti-AD activities were identified in FRP by a variety of methods, including silica gel column chromatography, multiple databases, and literature searches. Then, network pharmacology and molecular docking were adopted to systematically study the potential anti-AD mechanism of these compounds. Consequently, it was found that these 12 compounds could act on 235 anti-AD targets, of which AKT and other targets were the core targets. Meanwhile, among these 235 targets, 71 targets were identified to be significantly correlated with the pathology of amyloid beta (Aβ) and Tau.Results and discussionIn view of the analysis results of the network of active ingredients and targets, it was observed that palmatine, berberine, and other alkaloids in FRP were the key active ingredients for the treatment of AD. Further, Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis revealed that the neuroactive ligand-receptor interaction pathway and PI3K-Akt signaling pathway were the most significant signaling pathways for FRP to play an anti-AD role. Findings in our study suggest that multiple primary active ingredients in FRP can play a multitarget anti-AD effect by regulating key physiological processes such as neurotransmitter transmission and anti-inflammation. Besides, key ingredients such as palmatine and berberine in FRP are expected to be excellent leading compounds of multitarget anti-AD drugs.

As electric vehicles (EVs) are eco-friendly and have the feature of flexible power storage, the electric vehicle development is strongly supported by many governments. The market share of EVs has been rising steadily in recent years to promote the long-term growth of the available EV battery resources to participate in vehicle to grid (V2G). When a large number of electric vehicles can connect to grids randomly for charging or discharging, this inevitably brings large load fluctuation in regions and new challenges to the operation scheduling and control of power systems. Therefore, this paper proposed a new multi-level optimal V2G scheduling approach, ensuring the smooth operation and control from the V2G control center to the EV users. This paper also introduced a new EV economic dispatch optimization model to minimize the operating costs of regional V2G systems. A case analysis of the IEEE 33-bus system with 100 EVs verified the feasibility of the proposed model and indicated that the proper size control of total EV battery capacities with ramp adjustment can reduce additional load fluctuations caused by large-scale vehicles to grid. Moreover, the multi-stage TOU pricing mode is another effective measures that can trigger a next round of EV charging and discharging service.

A nonlinear dynamics model of the planetary gears-rotor system is established with a developed internal mesh stiffness embedded with ring gear stiffness. The torsional effect of rotor and pivotal parameters from gears including gear backlash， time-varying mesh stiffness and comprehensive transmission error are incorporated. Responses characteristic are analyzed with bifurcation diagrams， the largest Lyapunov exponents （LLE）， Poincaré maps and phase diagrams. The torsional vibration displacement response between gear and rotor is studied， and the influence law of torsional stiffness ratio between rotor shaft and drive shaft is analyzed. It is found that the system exhibits nonlinear characteristic， enters into chaotic motion through quasi-periodic bifurcation and period-doubling bifurcation， threshold values for stiffness ratios to avoid bifurcation and chaos are obtained. The research provides a reference of undesirable torsional behaviors in dynamic designing and vibration controlling for planetary gears-rotor systems in helicopter main reducer transmission.

Inversion of electromagnetic (EM) signals reflected from or transmitted through a medium, or emitted by it due to internal sources can be used to investigate the optical and physical properties of a variety of scattering/absorbing/emitting materials. Such media encompass planetary atmospheres and surfaces (including water/snow/ice), and plant canopies. In many situations the signals emerging from such media can be described by a linear transport equation which in the case of EM radiation is the radiative transfer equation (RTE). Solutions of the RTE can be used as a forward model to solve the inverse problem to determine the medium state parameters giving rise to the emergent (reflected/transmitted/emitted) EM signals. A novel method is developed to determine layer-by-layer contributions to the emergent signals from such stratified, multilayered media based on the solution of the pertinent RTE. As a specific example of how this approach may be applied, the radiation reflected from a multilayered atmosphere is used to solve the problem relevant for EM probing by a space-based lidar system. The solutions agree with those obtained using the standard lidar approach for situations in which single scattering prevails, but this novel approach also yields reliable results for optically thick, multiple scattering aerosol and cloud layers that cannot be provided by the traditional lidar approach.

Metabolic diseases characterized by dyslipidemia are common health problems for elderly populations. Dietary fiber intake is inversely associated with the risk of dyslipidemia. This study investigated the effects of Portulaca oleracea polysaccharide (POP) on the intestinal microbiota and its metabolites in aging rats using 16S rRNA sequencing and metabolomics techniques. Our results showed that POPs reduced the ratio of Firmicutes/Bacteroidetes (F/B), relative abundance of Fusobacteria, and levels of triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), alanine aminotransferase (ALT), and gamma-glutamyl transferase (γ-GT) in the serum of aging rats. POP supplementation also reduced 5beta-cholestane-3alpha,7alpha,12alpha,25-tetrol, and vaccenic acid concentrations in lipids and lipoid-like molecules, while soyasapogenol E and monoacylglycerol (MG) (24:0/0:0/0:0) levels increased. This study demonstrated that POP’s beneficial effects on lipid levels in aging rats might be partially attributable to the modification of gut microbiota and related metabolites.

In order to study the mechanism and product compositions of oil cracking, crude oil samples from the Zhuhai Formation of the Baiyun Sag of Pearl River Mouth Basin were carried out for the high-temperature, high-pressure pyrolysis with different heating rates with the pressure close to the conditions of underground. The underground fluid was also considered to be included with a semi-open condition for the pyrolysis, the gas yields and gas composition characteristics were then analyzed. Results showed that crude oils start to crack at 365 ℃, and the cracking yield increases with the increase of temperature. At a heating rate of 20 ℃/h, the final yields (at 550 ℃) of pyrolysis gas, hydrocarbon gas and non-hydrocarbon gas were 580.13, 394.25, and 185.88 mg/g, while at a heating rate of 60 ℃/h, these values increased to 707.68, 485.77, 221.91 mg/g, respectively. The composition of hydrocarbon gases at different heating rates also varied, and these variations were assumed to be related to the difference of cracking mechanisms of crude oils at different temperatures of pyrolysis. According to the composition characteristics of pyrolytic gas products, most of the gases from crude oil cracking has a relative higher content of high molecular weight hydrocarbon gas, thus these compounds can be used as an auxiliary index to distinguish crude oil cracked gas from kerogen cracked gas.

Spatial-frequency domain imaging (SFDI) has been developed as an emerging modality for detecting early-stage bruises of fruits, such as apples, due to its unique advantage of a depth-resolved imaging feature. This paper presents theoretical and experimental analyses to determine the light penetration depth in apple tissues under spatially modulated illumination. Simulation and practical experiments were then carried out to explore the maximum light penetration depths in ‘Golden Delicious’ apples. Then, apple experiments for early-stage bruise detection using the estimated reduced scattering coefficient mapping were conducted to validate the results of light penetration depths. The results showed that the simulations produced comparable or a little larger light penetration depth in apple tissues (~2.2 mm) than the practical experiment (~1.8 mm or ~2.3 mm). Apple peel further decreased the light penetration depth due to the high absorption properties of pigment contents. Apple bruises located beneath the surface peel with the depth of about 0–1.2 mm could be effectively detected by the SFDI technique. This study, to our knowledge, made the first effort to investigate the light penetration depth in apple tissues by SFDI, which would provide useful information for enhanced detection of early-stage apple bruising by selecting the appropriate spatial frequency.

The paper deals with a minimum potential energy algorithm considering the maximum deflection angle of joint (MPE-MDA algorithm) for three key factors including the maximum deflection angle of the joint, the total length of the path, and the minimum distance from obstacles. The algorithm is applied for space obstacle avoidance of hyper-redundant manipulators. On the path-following planning of the hyper-redundant manipulator, the MPE-MDA algorithm equates one link to multiple virtual small links and then derives the relationship between the length of the small links and the deflection angle of the small links. The planned path based on this relationship meets that the deflection angle of the link does not exceed the limited angle. The MPE-MDA algorithm resolves the problem that the traditional algorithm cannot limit the maximum deflection angle of the joint. Besides, the paper checks different paths by changing the step length, the direction of path planning, and other factors, and then selects the optimal path according to the evaluation function. Furthermore, by comparing the simulation results of path-following planning employing the MPE-MDA algorithm and the artificial potential field (APF) method, respectively. It is found that when the manipulator moves along the optimal path planned by the MPE-MDA algorithm, it can not only keep the specified distance from the obstacle but also can satisfy the condition that the deflection angle of the joint never exceeds the limited range, which verifies the reliability and effectiveness of the algorithm.

The application of diffusion theory and Monte Carlo lidar radiative transfer simulations presented in Part I of this series of study suggests that snow depth can be derived from the first-, second- and third-order moments of the lidar backscattering pathlength distribution. These methods are now applied to the satellite ICESat-2 lidar measurements over the Arctic sea ice and land surfaces of Northern Hemisphere. Over the Arctic sea ice, the ICESat-2 retrieved snow depths agree well with co-located IceBridge snow radar measured values with a root-mean-square (RMS) difference of 7.8 cm or 29.2% of the mean snow depth. The terrestrial snow depths derived from ICESat-2 show drastic spatial variation of the snowpack along ICESat-2 ground tracks over the Northern Hemisphere, which are consistent with the University of Arizona (UA) and Canadian Meteorological Centre (CMC) gridded daily snow products. The RMS difference in snow depths between ICESat-2 and UA gridded daily snow products is 14 cm, or 28% of the mean UA snow depth. To better understand these results, we also discuss the possible sources of errors in ICESat-2 derived snow depths, including surface roughness within the laser footprint, atmospheric forward scattering, solar background noise, and detector dark current. Simulation results indicate that the snow depth errors would be less than 5 cm if the standard deviation of pulse spreading due to surface roughness is within 50 cm. Our results demonstrate that the ICESat-2 lidar measurements can be used to reliably derive snow depth, which is a critical geophysical parameter for cryosphere studies including sea ice thickness estimation and also provides important constraints in the modeling of terrestrial hydrological processes.

Snow is a crucial element in the Earth’s system, but snow depth and mass are very challenging to be measured globally. Here, we provide the theoretical foundation for deriving snow depth directly from space-borne lidar (ICESat-2) snow multiple scattering measurements for the first time. First, based on the Monte Carlo lidar radiative transfer simulations of ICESat-2 measurements of 532-nm laser light propagation in snow, we find that the lidar backscattering path length follows Gamma distribution. Next, we derive three simple analytical equations to compute snow depth from the average, second-, and third-order moments of the distribution. As a preliminary application, these relations are then used to retrieve snow depth over the Antarctic ice sheet and the Arctic sea ice using the ICESat-2 lidar multiple scattering measurements. The robustness of this snow depth technique is demonstrated by the agreement of snow depth computed from the three derived relations using both modeled data and ICESat-2 observations.

Mulch film is usually mixed in with cotton during machine-harvesting and processing, which reduces the cotton quality. This paper presents a novel sorting algorithm for the online detection of film on cotton using hyperspectral imaging with a spectral region of 1000 - 2500 nm. The sorting algorithm consists of a group of stacked autoencoders, two optimization modules and an extreme learning machine (ELM) classifier. The variable-weighted stacked autoencoders (VW-SAE) are constructed to extract the features from hyperspectral images, and an artificial neural network (ANN), which is one optimization module, is applied to optimize the parameters of the VW-SAE. Then, the extracted features are input in the ELM to classify four types of objects: background, film on background, cotton and film on cotton. The ELM is optimized by a new optimizer (grey wolf optimizer), which can adjust the hidden nodes and parameters of the ELM simultaneously. A group of experiments was carried out to evaluate the performance of the proposed sorting algorithm using cotton that was provided by a Xinjiang municipality cotton ginning company. The experimental results show that the VW-SAE can improve the classification accuracies by approximately 15%. The overall recognition rate of the proposed algorithm is over 95%, and its recognition time is comparable to some state-of-the-art methods.

Traditional methods for solving the inverse kinematics of a hyper-redundant manipulator (HRM) can only plan the path of the end-effector with a complicated solving process, where obstacle avoidance is also not considered. To solve the above problems, a novel method for solving inverse kinematics of HRM is proposed in this paper: the variable dimension scaling method (VDSM), which can solve complex inverse kinematics while avoiding obstacles. Through this method, the path of the end-effector is scaled under a certain proportion and is adjusted depending on the position of the obstacle, which has good universality. The number of link angles changed is as small as possible in the process of achieving the end-effector moving along the desired path. With the redundancy of HRM, obstacle avoidance can be implemented in any environment by the proposed method. Through simulation and experiments in different environments, the above advantages of VDSM are verified.

Damage occurs easily and is difficult to find inside fruits and vegetables during transportation or storage, which not only brings losses to fruit and vegetable distributors, but also reduces the satisfaction of consumers. Spatially resolved spectroscopy (SRS) is able to detect the quality attributes of fruits and vegetables at different depths, which is of great significance to the quality classification and defect detection of horticultural products. This paper is aimed at reviewing the applications of spatially resolved spectroscopy for measuring the quality attributes of fruits and vegetables in detail. The principle of light transfer in biological tissues, diffusion approximation theory and methodologies are introduced, and different configuration designs for spatially resolved spectroscopy are compared and analyzed. Besides, spatially resolved spectroscopy applications based on two aspects for assessing the quality of fruits and vegetables are summarized. Finally, the problems encountered in previous studies are discussed, and future development trends are presented. It can be concluded that spatially resolved spectroscopy demonstrates great application potential in the field of fruit and vegetable quality attribute evaluation. However, due to the limitation of equipment configurations and data processing speed, the application of spatially resolved spectroscopy in real-time online detection is still a challenge.

The diamondback moth, Plutella xylostella, is a cosmopolitan pest and the first species to develop field resistance to toxins from the gram-positive bacterium Bacillus thuringiensis (Bt). Although previous work has suggested that mutations of ATP-binding cassette transporter subfamily C2 (ABCC2) or C3 (ABCC3) genes can confer Cry1Ac resistance, here we reveal that P. xylostella requires combined mutations in both PxABCC2 and PxABCC3 to achieve high-level Cry1Ac resistance, rather than simply a mutation of either gene. We identified natural mutations of PxABCC2 and PxABCC3 that concurrently occurred in a Cry1Ac-resistant strain (Cry1S1000) of P. xylostella, with a mutation (RA2) causing the mis-splicing of PxABCC2 and another mutation (RA3) leading to the premature termination of PxABCC3. Genetic linkage analysis showed that RA2 and RA3 were tightly linked to Cry1Ac resistance. Introgression of RA2 and RA3 enabled a susceptible strain (G88) of P. xylostella to obtain high resistance to Cry1Ac, confirming that these genes confer resistance. To further support the role of PxABCC2 and PxABCC3 in Cry1Ac resistance, frameshift mutations were introduced into PxABCC2 and PxABCC3 singly and in combination in the G88 strain with CRISPR/Cas9 mediated mutagenesis. Bioassays of CRISPR-based mutant strains, plus genetic complementation tests, demonstrated that the deletion of PxABCC2 or PxABCC3 alone provided < 4-fold tolerance to Cry1Ac, while disruption of both genes together conferred >8,000-fold resistance to Cry1Ac, suggesting the redundant/complementary roles of PxABCC2 and PxABCC3. This work advances our understanding of Bt resistance in P. xylostella by demonstrating mutations within both PxABCC2 and PxABCC3 genes are required for high-level Cry1Ac resistance.

The main objective was to measure the optical coefficients of peaches after bruising at different maturity levels and detect bruises. A spatially resolved method was used to acquire absorption coefficient (μa) and the reduced scattering coefficient (µs’) spectra from 550 to 1000 nm, and a total of 12 groups (3 maturity levels * 4 detection times) were used to assess changes in µa and µs’ resulting from bruising. Maturation and bruising both caused a decrease in µs’ and an increase in µa, and the optical properties of immature peaches changed more after bruising than the optical properties of ripe peaches. Four hours after bruising, the optical properties of most samples were significantly different from those of intact peaches (p < 0.05), and the optical properties showed damage to tissue earlier than the appearance symptoms observed with the naked eye. The classification results of the Support Vector Machine model for bruised peaches showed that μa had the best classification accuracy compared to μs′ and their combinations (µa × µs’, µeff). Overall, based on μa, the average detection accuracies for peaches after bruising of 0 h, 4 h, and 24 h were increased.

Spatial-frequency domain imaging (SFDI) is a wide-field, noncontact, and label-free imaging modality that is currently being explored as a new means for estimating optical absorption and scattering properties of two-layered turbid materials. The accuracy of SFDI for optical property estimation, however, depends on light transfer model and inverse algorithm. This study was therefore aimed at providing theoretical analyses of the diffusion model and inverse algorithm through numerical simulation, so as to evaluate the potential for estimating optical absorption and reduced scattering coefficients of two-layered horticultural products. The effect of varying optical properties on reflectance prediction was first simulated, which indicated that there is good separation in diffuse reflectance over a large range of spatial frequencies for different reduced scattering values in the top layer, whereas there is less separation in diffuse reflectance for different values of absorption in the top layer, and even less separation for optical properties in the bottom layer. To implement the nonlinear least-square method for extracting the optical properties of two-layered samples from Monte Carlo-generated reflectance, five curve fitting strategies with different constrained parameters were conducted and compared. The results confirmed that estimation accuracy improved as fewer variables were to be estimated each time. A stepwise method was thus suggested for estimating optical properties of two-layered samples. Four factors influencing optical property estimation of the top layer, which is the basis for accurately implementing the stepwise method, were investigated by generating absolute error contour maps. Finally, the relationship between light penetration depth and spatial frequency was studied. The results showed that penetration depth decreased with the increased spatial frequency and also optical properties, suggesting that appropriate selection of spatial frequencies for a stepwise method to estimate optical properties from two-layered samples provides potential for estimation accuracy improvement. This work lays a foundation for improving optical property estimation of two-layered horticultural products using SFDI.

Tomato maturity is important to determine the fruit shelf life and eating quality. The objective of this research was to evaluate tomato maturity in different layers by using a newly developed spatially resolved spectroscopic system over the spectral region of 550–1650 nm. Thirty spatially resolved spectra were obtained for 600 tomatoes, 100 for each of the six maturity stages (i.e., green, breaker, turning, pink, light red, and red). Support vector machine discriminant analysis (SVMDA) models were first developed for each of individual spatially resolved (SR) spectra to compare the classification results of two sides. The mean spectra of two sides with the same source-detector distances were employed to determine the model performance of different layers. SR combination by averaging all the SR spectra was also subject to comparison with the classification model performance. The results showed large source-detector distances would be helpful for evaluating tomato maturity, and the mean_SR 15 obtained excellent classification results with the total classification accuracy of 98.3%. Moreover, the classification results were distinct for two sides of the probe, which demonstrated even if in the same source-detector distances, the classification results were influenced by the measurement location due to the heterogeneity for tomato. The mean of all SR spectra could only improve the classification results based on the first three mean_SR spectra, but could not obtain the accuracy as good as the following mean_SR spectra. This study demonstrated that spatially resolved spectroscopy has potential for assessing tomato maturity in different layers.

Blueberries, which are rich in nutrition, are susceptible to fungal infection during postharvest or storage. However, early detection of diseases in blueberry is challenging because of their opaque appearance and the inconspicuousness of spots in the early stage of disease. The goal of this study was to investigate the potential of hyperspectral imaging over the spectral range of 400–1000 nm to discriminate early disease in blueberries. Scanning electron microscope observation verified that fungal damage to the cellular structure takes place during the early stages. A total of 400 hyperspectral images, 200 samples each of healthy and early disease groups, were collected to obtain mean spectra of each blueberry samples. Spectral correlation analysis was performed to select an effective spectral range. Partial least square discrimination analysis (PLSDA) models were developed using two types of spectral range (i.e., full wavelength range of 400–1000 nm and effective spectral range of 685–1000 nm). The results showed that the effective spectral range made it possible to provide better classification results due to the elimination of the influence of irrelevant variables. Moreover, the effective spectral range combined with an autoscale preprocessing method was able to obtain optimal classification accuracies, with recognition rates of 100% and 99% for healthy and early disease blueberries. This study demonstrated that it is feasible to use hyperspectral imaging to measure early disease blueberries.

This paper reports the nondestructive detection of apple varieties using a multichannel hyperspectral imaging system consisting of an illumination fiber and 30 detection fibers arranged at source–detector distances of 1.5–36 mm over the spectral range of 550–1650 nm. Spatially resolved (SR) spectra were obtained for 1500 apples, 500 each of three varieties from the same orchard to avoid environmental and geographical influences. Partial least squares discriminant analysis (PLSDA) models were developed for single SR spectra and spectral combinations to compare their performance of variety detection. To evaluate the effect of spectral range on variety detection, three types of spectra (i.e., visible region: 550–780 nm, near-infrared region: 780–1650 nm, full region: 550–1650 nm) were analyzed and compared. The results showed that the single SR spectra presented a different accuracy for apple variety classification, and the optimal SR spectra varied with spectral types. Spectral combinations had better accuracies for variety detection with best overall classifications of 99.4% for both spectral ranges in the NIR and full regions; however, the spectral combination could not improve the results over the optimal single SR spectra in the visible region. Moreover, the recognition of golden delicious (GD) was better than those of the other two varieties, with the best classification accuracy of 100% for three types of spectra. Overall, the multichannel hyperspectral imaging system provides more spatial-spectral information for the apples, and the results demonstrate that the technique gave excellent classifications, which suggests that the multichannel hyperspectral imaging system has potential for apple variety detection.

Acid resistance is one of key properties assisting the survival of cariogenic bacteria in a dental caries environment, but only a few genes conferring acid resistance have been identified to data. Functional metagenomics provides a systematic method for investigating commensal DNA to identify genes that encode target functions. Here, the host strain Escherichia coli DH10B and a constructed bidirectional transcription vector pSKII+-lacZ contributed to the construction of a metagenomic library, and 46.6 Mb of metagenomic DNA was cloned from carious supragingival plaque of 8children along with screening for lethal functionality. The screen identified 2 positive clones that exhibited a similar aciduric phenotype to that of the positive controls. Bioinformatic analysis revealed that these two genes encoded an ATP/GTP-binding protein and a malate dehydrogenase. Moreover, we also performed functional screening of Streptococcus mutans, since it is one of the predominant cariogenic strains but was not identified in our initial screening. Five positive clones were retrieved. In conclusion, our improved functional metagenomics screening method helped in the identification of important acid resistance genes, thereby providing new insights into the mechanism underlying caries formation as well as in the prevention and treatment of early childhood caries (ECC).

The response surface methodology was used to optimize the hydrothermal processing conditions based on the rice quality parameters of the Rong Youhua Zhan rice variety (Indica). The effect of soaking temperature (29.77, 40, 55, 70, and 80.23°C), soaking time (67.55, 90, 120, 150, and 170.45 min), and steaming time (1.59, 5, 10, 15, and 18.41 min), each tested at five levels, on percentage of head rice yield (HRY), hardness, cooking time, lightness, and color were determined, with R2 values of 0.96, 0.94, 0.90, 0.88, and 0.94, respectively. HRY, hardness, cooking time, and color increased with process severity while lightness decreased, although HRY decreased after reaching a maximum. The predicted optimum soaking temperature, soaking time, and steaming time were 69.88°C, 150 min, and 6.73 min, respectively, and the predicted HRY, hardness, cooking time, lightness, and color under these conditions were 73.43%, 29.95 N, 32.14 min, 83.03 min, and 12.24 min, respectively, with a composite desirability of 0.9658. The parboiling industry could use the findings of the current study to obtain the desired quality of parboiled rice. This manuscript will be helpful for researchers working on commercializing parboiled rice processes in China as well as in other countries.

Our understanding of the genus Natrinema is presently limited due to the lack of available genetic tools. Auxotrophic markers have been widely used to construct genetic systems in bacteria and eukaryotes and in some archaeal species. Here, we isolated four auxotrophic mutants of Natrinema sp. J7-2, via 1-methyl-3-nitro-1-nitroso-guanidin mutagenesis, and designated them as J7-2-1, J7-2-22, J7-2-26, and J7-2-52, respectively. The mutant phenotypes were determined to be auxotrophic for leucine (J7-2-1), arginine (J7-2-22 and J7-2-52), and lysine (J7-2-26). The complete genome and the biosynthetic pathways of amino acids in J7-2 identified that the auxotrophic phenotype of three mutants was due to gene mutations in leuB (J7-2-1), dapD (J7-2-26), and argC (J7-2-52). These auxotrophic phenotypes were employed as selectable makers to establish a transformation method. The transformation efficiencies were determined to be approximately 103 transformants per µg DNA. And strains J7-2-1 and J7-2-26 were transformed into prototrophic strains with the wild type genomic DNA, amplified fragments of the corresponding genes, or the integrative plasmids carrying the corresponding genes. Additionally, exogenous genes, bgaH or amyH gene, were expressed successfully in J7-2-1. Thus, we have developed a genetic manipulation system for the Natrinema genus based on the isolated auxotrophic mutants of Natrinema sp. J7-2.

New, non-destructive sensing techniques for fast and more effective quality assessment of fruits and vegetables are needed to meet the ever-increasing consumer demand for better, more consistent and safer food products. Over the past 15 years, hyperspectral imaging has emerged as a new generation of sensing technology for non-destructive food quality and safety evaluation, because it integrates the major features of imaging and spectroscopy, thus enabling the acquisition of both spectral and spatial information from an object simultaneously. This paper first provides a brief overview of hyperspectral imaging configurations and common sensing modes used for food quality and safety evaluation. The paper is, however, focused on the three innovative hyperspectral imaging-based techniques or sensing platforms, i.e., spectral scattering, integrated reflectance and transmittance, and spatially-resolved spectroscopy, which have been developed in our laboratory for property and quality evaluation of fruits, vegetables and other food products. The basic principle and instrumentation of each technique are described, followed by the mathematical methods for processing and extracting critical information from the acquired data. Applications of these techniques for property and quality evaluation of fruits and vegetables are then presented. Finally, concluding remarks are given on future research needs to move forward these hyperspectral imaging techniques.

Natrinema sp. J7-2 is an extreme haloarchaeon capable of growing on synthetic media without amino acid supplements. Here we report the complete genome sequence of Natrinema sp. J7-2 which is composed of a 3,697,626-bp chromosome and a 95,989-bp plasmid pJ7-I. This is the first complete genome sequence of a member of the genus Natrinema. We demonstrate that Natrinema sp. J7-2 can use gluconate, glycerol, or acetate as the sole carbon source and that its genome encodes complete metabolic pathways for assimilating these substrates. The biosynthetic pathways for all 20 amino acids have been reconstructed, and we discuss a possible evolutionary relationship between the haloarchaeal arginine synthetic pathway and the bacterial lysine synthetic pathway. The genome harbors the genes for assimilation of ammonium and nitrite, but not nitrate, and has a denitrification pathway to reduce nitrite to N(2)O. Comparative genomic analysis suggests that most sequenced haloarchaea employ the TrkAH system, rather than the Kdp system, to actively uptake potassium. The genomic analysis also reveals that one of the three CRISPR loci in the Natrinema sp. J7-2 chromosome is located in an integrative genetic element and is probably propagated via horizontal gene transfer (HGT). Finally, our phylogenetic analysis of haloarchaeal genomes provides clues about evolutionary relationships of haloarchaea.

In the title molecule, C24H32N4O2, the piperazine ring adopts a chair conformation and the dihedral angle between the two benzene rings is 35.4 (1)°. In the crystal structure, intermolecular O—H...N hydrogen bonds link molecules into chains along [001].