Safety and efficacy of bilateral superselective adrenal arterial embolization for treatment of idiopathic hyperaldosteronism: a prospective single-center study.

OBJECTIVE: This study aimed to assess the efficacy and safety of bilateral superselective adrenal arterial embolization (SAAE) in patients with bilateral idiopathic hyperaldosteronism (IHA), a subtype of PA. METHODS: Ninety-eight patients with bilateral IHA underwent bilateral SAAE between August 2022 and August 2023. Sixty-eight patients were followed up for up to 12 months. The study outcomes were evaluated using the criteria provided by the Primary Aldosteronism Surgical Outcome (PASO) guidelines. RESULTS: The mean reductions in systolic and diastolic blood pressure were 27.4 ± 21.3 mmHg and 23.1 ± 17.4 mmHg, respectively (p < 0.001). The rates of clinical success and biochemical success after adrenal artery ablation were 63.2% (43/68) and 39.7% (27/68), respectively. Overall, there were significant reductions in daily defined doses (DDD), aldosterone/renin ratio (ARR), and plasma aldosterone levels (p < 0.001). Plasma renin levels increased by a mean value of 10.4 ± 39.0 pg/mL (p = 0.049), and potassium levels increased by 0.40 ± 0.63 mmol/L (p < 0.001). No significant adverse events were reported during SAAE or the follow-up period of up to one year. Additionally, no abnormalities were detected by adrenal 68Ga-Pentixafor PET/CT scans before or after SAAE. CONCLUSION: Bilateral SAAE appears to lead to sustained improvements in blood pressure and biochemical parameters in patients with bilateral PA, with minimal adverse effects. This suggests that bilateral SAAE could serve as an effective alternative approach for treating bilateral IHA, potentially curing this condition.

Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method.

The global concern regarding the adverse effects of heavy metal pollution in soil has grown significantly. Accurate prediction of heavy metal content in soil is crucial for environmental protection. This study proposes an inversion analysis method for heavy metals (As, Cd, Cr, Cu, Ni, Pb) in soil based on hyperspectral and machine learning algorithms for 21 soil reference materials from multiple provinces in China. On this basis, an integrated learning model called Stacked RF (the base model is XGBoost, LightGBM, CatBoost, and the meta-model is RF) was established to perform soil heavy metal inversion. Specifically, three popular algorithms were initially employed to preprocess the spectral data, then Random Forest (RF) was used to select the best feature bands to reduce the impact of noise, finally Stacking and four basic machine learning algorithms were used to establish comparisons and analysis of inversion model. Compared with traditional machine learning methods, the stacking model showcases enhanced stability and superior accuracy. Research results indicate that machine learning algorithms, especially ensemble learning models, have better inversion effects on heavy metals in soil. Overall, the MF-RF-Stacking model performed best in the inversion of the six heavy metals. The research results will provide a new perspective on the ensemble learning model method for soil heavy metal content inversion using data of hyperspectral characteristic bands collected from soil reference materials.

Hierarchical and Porous Structures of Carbon Nanotubes-Anchored MOF Derivatives Bridged by Carbon Nanocoils as Lightweight and Broadband Microwave Absorbers.

High-performance microwave absorption (MA) materials have attracted more and more attention because they can effectively prevent microwave radiation and interference from electronic devices. Herein, a new type of MA composite is constructed by introducing carbon nanotubes (CNTs)-anchored metal-organic framework derivatives (MOFDs) into a conductive carbon nanocoil (CNC) network, denoted as CNC/CNT-MOFD. The CNC/MOFD shows a wide effective absorption band of 6.7 GHz under a filling ratio of only 9% in wax-matrix. This is attributed to the hierarchical and porous structures of MOFD bridged by the uniformly dispersed conductive CNC network and the cross-polarization induced by the 3D spiral CNCs. Besides, the as-grown 1D CNTs improve space utilization, porosity, and polarization loss of the composites, resulting in the increase of imaginary permittivity, which further realizes impedance matching and energy attenuation. The Ni nanoparticles in layers of MOFD and at the tips of CNTs generate magnetic loss, promoting the low-frequency absorption ability. Resultantly, RCS values of the optimized composite in all tested theta (θ) ranges are less than -25 dB m2 at 9.5 GHz, effectively reducing the probability of the target detected by the radar.

Surface Enhancement Effects of Tiny SnO2 Nanoparticle Modification on α-Fe2O3 for Room-Temperature NH3 Sensing.

The development of a gas sensor capable of detecting ammonia with high selectivity and rapid response at room temperature has consistently posed a formidable challenge. To address this issue, the present study utilized a one-step solvothermal method to co-assemble α-Fe2O3 and SnO2 by evenly covering SnO2 nanoparticles on the surface of α-Fe2O3. By controlling the morphology and Fe/Sn mole ratio of the composite, the as-prepared sample exhibits high-performance detection of NH3. At room temperature conditions, a gas sensor composed of α-Fe2O3@3%SnO2 demonstrates a rapid response time of 14 s and a notable sensitivity of 83.9% when detecting 100 ppm ammonia. Experiments and density functional theory (DFT) calculations suggest that the adsorption capacity of α-Fe2O3 to ammonia is enhanced by the surface effect provided by SnO2. Meanwhile, the existence of SnO2 tailors the pore structure and effective surface area of α-Fe2O3, creating multiple channels for the diffusion and adsorption of ammonia molecules. Additionally, an N-N heterostructure is formed between α-Fe2O3 and SnO2, which enhances the potential energy barrier and improves the ammonia sensing performance. Demonstration experiments have proved that the sensor shows significant advantages over commercial sensors in the process of ammonia detection in agricultural facilities. This work provides new insights into the perspectives on ammonia detection at room temperature.

Study on detection method of microplastics in farmland soil based on hyperspectral imaging technology.

Microplastics (MPs) in farming soils can have a substantial impact on soil ecology and agricultural productivity, as well as affecting human health and the food chain cycle. As a result, it is vital to study MPs detection technologies that are rapid, efficient, and accurate in agriculture soils. This study investigated the classification and detection of MPs using hyperspectral imaging (HSI) technology and a machine learning methodology. To begin, the hyperspectral data was preprocessed using SG convolution smoothing and Z-score normalization. Second, the feature variables were extracted from the preprocessed spectral data using bootstrapping soft shrinkage, model adaptive space shrinkage, principal component analysis, isometric mapping (Isomap), genetic algorithm, successive projections algorithm (SPA), and uninformative variable elimination. Finally, three support vector machine (SVM), back propagation neural network (BPNN), and one-dimensional convolutional neural network (1D-CNN) models were developed to classify and detect three microplastic polymers: polyethylene, polypropylene, and polyvinyl chloride, as well as their combinations. According to the experimental results, the best approaches based on three models were Isomap-SVM, Isomap-BPNN, and SPA-1D-CNN. Among them, the accuracy, precision, recall and F1_score of Isomap-SVM were 0.9385, 0.9433, 0.9385 and 0.9388, respectively. The accuracy, precision, recall and F1_score of Isomap-BPNN were 0.9414, 0.9427, 0.9414 and 0.9414, respectively, while the accuracy, precision, recall and F1_score of SPA-1D-CNN were 0.9500, 0.9515, 0.9500 and 0.9500, respectively. When their classification accuracy was compared, SPA-1D-CNN had the best classification performance, with a classification accuracy of 0.9500. The findings of this study shown that the SPA-1D-CNN based on HSI technology can efficiently and accurately identify MPs in farmland soils, providing theoretical backing as well as technical means for real-time detection of MPs in farmland soils.

Dihydroartemisinin Attenuates Pulmonary Hypertension Through Inhibition of Pulmonary Vascular Remodeling in Rats.

Pulmonary arterial hypertension (PAH) is a malignant disease characterized by pulmonary arterial remodeling because of the abnormal proliferation and migration of pulmonary arterial smooth muscle cells. Dihydroartemisinin (DHA), an artemisinin derivative used to treat malaria, is able to inhibit fibrosis, neovascularization, and tumor proliferation. In this study, we hypothesized that DHA can be beneficial in treating PAH. To test this hypothesis, a rat model of pulmonary hypertension induced with monocrotaline (MCT) was used. Compared with MCT treatment alone, treatment with 50 or 100 mg/kg DHA significantly reduced the mean pulmonary arterial pressure (30.11 ± 2.48 mm Hg vs. 21.35 ± 3.04 mm Hg and 19.18 ± 1.98 mm Hg, respectively, both P < 0.01), right ventricular transverse diameter (4.36 ± 0.41 mm vs. 3.72 ± 0.24 mm and 3.67 ± 0.27 mm, respectively, both P < 0.01), pulmonary artery medial wall thickness (57.93 ± 11.14% vs. 34.45 ± 4.39% and 25.01 ± 6.66%, respectively, both P < 0.01), and increased tricuspid annular plane systolic excursion (1.34 ± 0.17 mm vs. 1.62 ± 0.3 mm and 1.62 ± 0.16 mm, respectively, both P < 0.05). We also found that DHA inhibited platelet-derived growth factor-BB-mediated pulmonary arterial smooth muscle cells proliferation and migration in a dose-dependent manner. Moreover, DHA downregulated ß-catenin levels while upregulating the levels of axis inhibition protein 2 (Axin2) and glycogen synthase kinase 3ß (GSK-3ß). Our findings suggest that DHA, which may be a potential candidate for PAH therapy, attenuates experimental pulmonary hypertension possibly by inhibiting pulmonary vascular remodeling.

High-temperature sensor based on suspended-core microstructured optical fiber.

We propose a high-temperature sensor based on a suspended-core microstructured optical fiber (SCMF). The sensor is constructed by fusion splicing a piece of SCMF between two sections of multimode fibers (MMFs) which act as light beam couplers. The multimode interference is formed by the air cladding modes and the silica core modes in the SCMF. Fast Fourier transform is adapted to filtering the raw transmission spectra of the MMF-SCMF-MMF structure. The wavelength shift of the dominant spatial frequency is monitored as the temperature varies from 50 °C to 800 °C. The sensitivities of 31.6 pm/°C and 51.6 pm/°C in the temperature range of 50 °C-450 °C and 450 °C-800 °C are respectively achieved. Taking advantage of the compact size, good stability and repeatability, easy fabrication, and low cost, this proposed high-temperature sensor has an applicable value.

Impact of discharge currents on the intensity of 46.9 nm capillary discharge soft X-ray laser.

In this article, capillary discharge Ne-like argon 46.9nm soft X-ray laser has been firstly manifested with 4.8mm inner diameter alumina capillary for higher discharge currents. We have designed and installed capillary discharge setup for 4.8mm inner diameter alumina capillary to achieve intense 46.9nm laser. One dimensional Langragian Magneto-hydrodynamics (MHD) code was used to simulate the plasma conditions at the lasing time. The MHD code was used to perform the parametric studies of Z-pinch argon plasma, such as electron temperature, electron density and Ne-like argon ion density. The intensities of capillary discharge 46.9nm laser emitted from 4.8mm inner diameter alumina capillary were measured at 30, 36 and 40kA main discharge currents. According to the results, when the main current amplitude was increased from 30kA to 36kA and 40kA, the intensity of laser produced at optimum pressure increased up to 1.5 and 2 times, respectively. Moreover, we also studied the influence of predischarge current by increasing the predischarge current from 25 to 250A and investigated 140A as the best predischarge current for lasing. Hence, increasing the amplitude of main current using a comparatively larger inner diameter capillary is an effective way to improve intensity of capillary discharge 46.9nm soft X-ray laser. The maximum energy of 46.9nm laser was observed approximately 1.5mJ under best discharge conditions. The discussion has been made on the enhancement of 46.9nm laser intensity for higher main discharge currents and best predischarge current with experimental and simulated results. This is the first observation of 46.9nm laser with 4.8mm inner diameter alumina capillary.

Transection of the cervical sympathetic trunk inhibits the progression of pulmonary arterial hypertension via ERK-1/2 Signalling.

BACKGROUND: Abnormal sympathetic hyperactivity has been shown to lead to pulmonary arterial hypertension (PAH) deterioration. The purpose of this study was to examine whether the transection of the cervical sympathetic trunk (TCST) can inhibit the progression of PAH in a monocrotaline (MCT)-induced PAH model and elucidate the underlying mechanisms. METHODS: Rats were randomly divided into four groups, including a control group, an MCT group, an MCT + sham group and an MCT + TCST group. After performing haemodynamic and echocardiographic measurements, the rats were sacrificed for the histological study, and the norepinephrine (NE) concentrations and protein expression level of tyrosine hydroxylase (TH) were evaluated. The protein expression levels of extracellular signal-regulated kinase (ERK)-1/2, proliferating cell nuclear antigen (PCNA), cyclin A2 and cyclin D1 in pulmonary artery vessels and pulmonary arterial smooth muscle cells (PASMCs) were determined. RESULTS: Compared with the MCT + sham group, TCST profoundly reduced the mean pulmonary arterial pressure (mPAP) (22.02 ± 4.03 mmHg vs. 31.71 ± 2.94 mmHg), right ventricular systolic pressure (RVSP) (35.21 ± 5.59 mmHg vs. 48.36 ± 5.44 mmHg), medial wall thickness (WT%) (22.48 ± 1.75% vs. 46.10 ± 3.16%), and right ventricular transverse diameter (RVTD) (3.78 ± 0.40 mm vs. 4.36 ± 0.29 mm) and increased the tricuspid annular plane systolic excursion (TAPSE) (2.00 ± 0.12 mm vs. 1.41 ± 0.24 mm) (all P < 0.05). The NE concentrations and protein expression levels of TH were increased in the PAH rats but significantly decreased after TCST. Furthermore, TCST reduced the increased protein expression of PCNA, cyclin A2 and cyclin D1 induced by MCT in vivo. We also found that NE promoted PASMC viability and activated the ERK-1/2 pathway. However, the abovementioned NE-induced changes could be suppressed by the specific ERK-1/2 inhibitor U0126. CONCLUSION: TCST can suppress pulmonary artery remodelling and right heart failure in MCT-induced PAH. The main mechanism may be that TCST decreases the NE concentrations in lung tissues, thereby preventing NE from promoting PASMC proliferation mediated by the ERK-1/2 signalling pathway.

Demonstration of an optical directed half-subtracter using integrated silicon photonic circuits.

An integrated silicon photonic circuit consisting of two silicon microring resonators (MRRs) is proposed and experimentally demonstrated for the purpose of half-subtraction operation. The thermo-optic modulation scheme is employed to modulate the MRRs due to its relatively simple fabrication process. The high and low levels of the electrical pulse signal are utilized to define logic 1 and 0 in the electrical domain, respectively, and the high and low levels of the optical power represent logic 1 and 0 in the optical domain, respectively. Two electrical pulse sequences regarded as the operands are applied to the corresponding micro-heaters fabricated on the top of the MRRs to achieve their dynamic modulations. The final operation results of bit-wise borrow and difference are obtained at their corresponding output ports in the form of light. At last, the subtraction operation of two bits with the operation speed of 10 kbps is demonstrated successfully.

Demonstration of gain saturation and double-pass amplification of a 69.8 nm laser pumped by capillary discharge.

With a 45-cm-long capillary, we obtained a saturated 69.8 nm laser with a gain coefficient of 0.4 cm-1 and a gain length product of 18. In order to increase the laser energy further, a double-pass amplification of the 69.8 nm laser was first realized with a SiC mirror without a coating. With a half cavity, the effective plasma column length and the effective gain length product can reach 84 cm and 33.7, respectively. The amplitude of a laser pulse for double-pass amplification is 9 times larger than that for single-pass amplification. In addition, the full width at half-maximum (FWHM) pulse width of a laser pulse and FWHM divergence for single-pass amplification are 1.4 ns and 0.5 mrad, respectively, which increase to 2.2 ns and 3.4 mrad for double-pass amplification.

Si and Cu ablation with a 46.9-nm laser focused by a toroidal mirror.

Si and Cu targets were ablated by a capillary-discharge 46.9-nm pumped laser beam, focused by a toroidal mirror at grazing incidence. The peak power density of the focal spot was ~2 × 107 W/cm2. Clear ablation patterns on the surfaces of Si and Cu targets were obtained, with shapes consistent with simulations. A YAG: Ce scintillator (cerium-doped YAG crystal) was used to image the variations of the laser spots. We discuss the shape and damage mechanics of the measured patterns. Melting of the target material was observed in the ablation region on Cu, but not on Si.

Electro-optic directed XOR logic circuits based on parallel-cascaded micro-ring resonators.

We report an electro-optic photonic integrated circuit which can perform the exclusive (XOR) logic operation based on two silicon parallel-cascaded microring resonators (MRRs) fabricated on the silicon-on-insulator (SOI) platform. PIN diodes embedded around MRRs are employed to achieve the carrier injection modulation. Two electrical pulse sequences regarded as two operands of operations are applied to PIN diodes to modulate two MRRs through the free carrier dispersion effect. The final operation result of two operands is output at the Output port in the form of light. The scattering matrix method is employed to establish numerical model of the device, and numerical simulator SG-framework is used to simulate the electrical characteristics of the PIN diodes. XOR operation with the speed of 100Mbps is demonstrated successfully.

Free light-shape focusing in extreme-ultraviolet radiation with self-evolutionary photon sieves.

Extreme-ultraviolet (EUV) radiation is a promising tool, not only for probing microscopic activities but also for processing nanoscale structures and performing high-resolution imaging. In this study, we demonstrate an innovative method to generate free light-shape focusing with self-evolutionary photon sieves under a single-shot coherent EUV laser; this includes vortex focus shaping, array focusing, and structured-light shaping. The results demonstrate that self-evolutionary photon sieves, consisting of a large number of specific pinholes fabricated on a piece of Si3N4 membrane, are capable of freely regulating an EUV light field, for which high-performance focusing elements are extremely lacking, let alone free light-shape focusing. Our proposed versatile photon sieves are a key breakthrough in focusing technology in the EUV region and pave the way for high-resolution soft X-ray microscopy, spectroscopy in materials science, shorter lithography, and attosecond metrology in next-generation synchrotron radiation and free-electron lasers.

Nondestructive Detection of Sunflower Seed Vigor and Moisture Content Based on Hyperspectral Imaging and Chemometrics.

Sunflower is an important crop, and the vitality and moisture content of sunflower seeds have an important influence on the sunflower's planting and yield. By employing hyperspectral technology, the spectral characteristics of sunflower seeds within the wavelength range of 384-1034 nm were carefully analyzed with the aim of achieving effective prediction of seed vitality and moisture content. Firstly, the original hyperspectral data were subjected to preprocessing techniques such as Savitzky-Golay smoothing, standard normal variable correction (SNV), and multiplicative scatter correction (MSC) to effectively reduce noise interference, ensuring the accuracy and reliability of the data. Subsequently, principal component analysis (PCA), extreme gradient boosting (XGBoost), and stacked autoencoders (SAE) were utilized to extract key feature bands, enhancing the interpretability and predictive performance of the data. During the modeling phase, random forests (RFs) and LightGBM algorithms were separately employed to construct classification models for seed vitality and prediction models for moisture content. The experimental results demonstrated that the SG-SAE-LightGBM model exhibited outstanding performance in the classification task of sunflower seed vitality, achieving an accuracy rate of 98.65%. Meanwhile, the SNV-XGBoost-LightGBM model showed remarkable achievement in moisture content prediction, with a coefficient of determination (R2) of 0.9715 and root mean square error (RMSE) of 0.8349. In conclusion, this study confirms that the fusion of hyperspectral technology and multivariate data analysis algorithms enables the accurate and rapid assessment of sunflower seed vitality and moisture content, providing robust tools and theoretical support for seed quality evaluation and agricultural production practices. Furthermore, this research not only expands the application of hyperspectral technology in unraveling the intrinsic vitality characteristics of sunflower seeds but also possesses significant theoretical and practical value.

Quest for the Nitrogen-Metabolic Versatility of Microorganisms in Soil and Marine Ecosystems.

Whether nitrogen (N)-metabolic versatility is a common trait of N-transforming microbes or if it only occurs in a few species is still unknown. We collected 83 soil samples from six soil types across China, retrieved 19 publicly available metagenomic marine sample data, and analyzed the functional traits of N-transforming microorganisms using metagenomic sequencing. More than 38% and 35% of N-transforming species in soil and marine ecosystems, respectively, encoded two or more N-pathways, although N-transforming species differed greatly between them. Furthermore, in both soil and marine ecosystems, more than 80% of nitrifying and N-fixing microorganisms at the species level were N-metabolic versatile. This study reveals that N-metabolic versatility is a common trait of N-transforming microbes, which could expand our understanding of the functional traits of drivers of nitrogen biogeochemistry.

Designing a Microstructure of NiCo-LDH@CNTs@Carbon Foam for Efficient Electromagnetic Wave Absorption and Excellent Environmental Tolerance.

The constantly evolving environment imposes increasingly stringent demands on the mechanical qualities of materials employed for absorbing electromagnetic waves (EMWs). Therefore, there is an urgent need for advanced materials capable of efficiently absorbing EMWs and withstanding harsh electromagnetic conditions. In this study, the electrodeposition method was effectively used to synthesize nickel-cobalt layered double hydroxides (NiCo-LDHs) in a controlled manner on a composite structure of carbon nanotubes and carbon foam, creating an exquisite construction. The manipulation of the electrodeposition time facilitated the regulation of the density of the layered structure within the composite material, thereby significantly enhancing its polarization relaxation performance. Increased defect sites and interface polarization enhance impedance matching and the attenuation constant, resulting in greatly improved absorption performance. The optimized sample demonstrated exceptional wave-absorbing performance in comparative experimental analysis, attaining a maximum reflection loss of -58.18 dB. It also has an effective absorption bandwidth of 5.36 GHz at a wavelength of 2.28 mm. The exceptional isolation effect of LDH, coupled with the outstanding insulation ability of the porous carbon skeleton, confers remarkable corrosion resistance and thermal insulation performance on the composite material. Hence, this discovery offers novel insights into designing environmentally tolerant absorbent materials.

Genome sequencing of Coryphaenoides yaquinae reveals convergent and lineage-specific molecular evolution in deep-sea adaptation.

Abyssal (3501-6500 m) and hadal (>6500 m) fauna evolve under harsh abiotic stresses, characterized by high hydrostatic pressure, darkness and food shortage, providing unique opportunities to investigate mechanisms underlying environmental adaptation. Genomes of several hadal species have recently been reported. However, the genetic adaptation of deep sea species across a broad spectrum of ocean depths has yet to be thoroughly investigated, due to the challenges imposed by collecting the deep sea species. To elucidate the correlation between genetic innovation and vertical distribution, we generated a chromosome-level genome assembly of the macrourids Coryphaenoides yaquinae, which is widely distributed in the abyssal/hadal zone ranging from 3655 to 7259 m in depth. Genomic comparisons among shallow, abyssal and hadal-living species identified idiosyncratic and convergent genetic alterations underlying the extraordinary adaptations of deep-sea species including light perception, circadian regulation, hydrostatic pressure and hunger tolerance. The deep-sea fishes (Coryphaenoides Sp. and Pseudoliparis swirei) venturing into various ocean depths independently have undergone convergent amino acid substitutions in multiple proteins such as rhodopsin 1, pancreatic and duodenal homeobox 1 and melanocortin 4 receptor which are known or verified in zebrafish to be related with vision adaptation and energy expenditure. Convergent evolution events were also identified in heat shock protein 90 beta family member 1 and valosin-containing protein genes known to be related to hydrostatic pressure adaptation specifically in fishes found around the hadal range. The uncovering of the molecular convergence among the deep-sea species shed new light on the common genetic innovations required for deep-sea adaptation by the fishes.

YOLOC-tiny: a generalized lightweight real-time detection model for multiripeness fruits of large non-green-ripe citrus in unstructured environments.

This study addresses the challenges of low detection precision and limited generalization across various ripeness levels and varieties for large non-green-ripe citrus fruits in complex scenarios. We present a high-precision and lightweight model, YOLOC-tiny, built upon YOLOv7, which utilizes EfficientNet-B0 as the feature extraction backbone network. To augment sensing capabilities and improve detection accuracy, we embed a spatial and channel composite attention mechanism, the convolutional block attention module (CBAM), into the head's efficient aggregation network. Additionally, we introduce an adaptive and complete intersection over union regression loss function, designed by integrating the phenotypic features of large non-green-ripe citrus, to mitigate the impact of data noise and efficiently calculate detection loss. Finally, a layer-based adaptive magnitude pruning strategy is employed to further eliminate redundant connections and parameters in the model. Targeting three types of citrus widely planted in Sichuan Province-navel orange, Ehime Jelly orange, and Harumi tangerine-YOLOC-tiny achieves an impressive mean average precision (mAP) of 83.0%, surpassing most other state-of-the-art (SOTA) detectors in the same class. Compared with YOLOv7 and YOLOv8x, its mAP improved by 1.7% and 1.9%, respectively, with a parameter count of only 4.2M. In picking robot deployment applications, YOLOC-tiny attains an accuracy of 92.8% at a rate of 59 frames per second. This study provides a theoretical foundation and technical reference for upgrading and optimizing low-computing-power ground-based robots, such as those used for fruit picking and orchard inspection.

Environmental pseudotargeted metabolomics: A high throughput and wide coverage method for metabolic profiling of 1000-year paddy soil chronosequences.

Pseudotargeted metabolomics is achieved by introducing an algorithm designed to choose ions for selected ion monitoring from identified metabolites. This method integrates the advantages of both untargeted and targeted metabolomics. In this study, environmental pseudotargeted metabolomics was established to analyze the soil metabolites, based on microwave assisted derivatization followed by gas chromatography-mass spectrometry analysis. The method development included the optimization of extraction factors and derivatization conditions, evaluation of silylation reagent types and matrix-dependent behaviors. Under the optimal conditions, the microwave oximation and silylation were completed in 5 min and 9 min. A total of 184 metabolites from 26 chemical classifications were identified in soil matrices. The method validation demonstrated excellent performance in terms of linearity (correlation coefficient > 0.99), repeatability (relative standard deviation (RSD) < 20 %), reproducibility (RSD < 25 %), stability (relative difference < 10 % within 18 h), and sensitivity (16-110 times higher signal-to-noise ratio). This developed method was applied to characterize the metabolite compositions and metabolic profiling in a 1000-year paddy soil chronosequence. The relative abundance of trehalose was highest in 6-(40.3 %), 60-(55.8 %), 300-(67.7 %)and 1000-(61.7 %)years paddy soil, respectively, but long-chain fatty acids were most abundant in marine sediment (57.4 %). Forty-two characteristic metabolites were considered as primarily responsible for discriminating and characterizing the paddy soil chronosequences development and seven major metabolic pathways were altered. In addition, GC-MS metabolite profile presented better discriminating power in paddy soil ecosystem changes than phospholipid fatty acids (PLFAs). Overall, environmental pseudotargeted metabolomics can provide a high throughout and wide coverage approach for performing metabolic profiling in the soil research.