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Abstract Nonsuicidal self-injury (NSSI) is one of the major public health problems endangering adolescents. However, the neural mechanisms of NSSI is still unclear. The purpose of this study was to explore regional brain activity and corresponding brain circuits in drug-naïve adolescents with NSSI using amplitude of low-frequency fluctuations (ALFF) combined with functional connectivity (FC) analysis. Thirty-two drug-naïve adolescents with NSSI (NSSI group) and 29 healthy controls matched for sex, age, and level of education (HC group) were enrolled in this study. ALFF and seed-based FC analyses were used to examine the alterations in regional brain activity and corresponding brain circuits. The correlation between ALFF or FC values of aberrant brain regions and clinical characteristics were detected by Pearson correlation analysis. The NSSI group showed increased ALFF in the left inferior and middle occipital gyri, lingual gyrus, and fusiform gyrus; additionally, decreased ALFF in the right medial cingulate gyrus, left anterior cingulate gyrus, and left medial superior frontal gyrus compared to those in the HC group. With the left inferior occipital gyrus as seed, the NSSI group showed increased FC between the left inferior occipital gyrus and the bilateral superior parietal gyrus, right inferior parietal angular gyrus, right inferior frontal gyrus of the insular region, and left precuneus relative to that the HC group. With the left anterior cingulate gyrus as seed, the NSSI group showed increased FC between the left anterior cingulate gyrus and right dorsolateral superior frontal gyrus. With the left lingual gyrus as seed, the NSSI group showed increased FC between the left lingual gyrus and right middle frontal gyrus, and decreased FC between the left lingual gyrus and the left superior temporal gyrus, right supplementary motor area, and left rolandic operculum. With the left fusiform gyrus as seed, the NSSI group showed increased FC between the left fusiform gyrus and left middle and inferior temporal gyrus, and decreased FC between the left fusiform gyrus and the bilateral postcentral gyrus, right precentral gyrus, right lingual gyrus, and left inferior parietal angular gyrus. Moreover, the FC value between the left fusiform gyrus and left inferior temporal gyrus was positively correlated with suicidal ideations score. This study highlights alterations in regional brain activity and corresponding brain circuits in brain regions related to visual and emotional regulation functions in drug-naïve adolescents with NSSI. These findings may facilitate better understand the underlying neural mechanisms of NSSI in adolescents.

To reduce CO2 emissions from coal-fired power plants, the development of low-carbon or carbon-free fuel combustion technologies has become urgent. As a new zero-carbon fuel, ammonia (NH3) can be used to address the storage and transportation issues of hydrogen energy. Since it is not feasible to completely replace coal with ammonia in the short term, the development of ammonia–coal co-combustion technology at the current stage is a fast and feasible approach to reduce CO2 emissions from coal-fired power plants. This study focuses on modifying the boiler and installing two layers of eight pure-ammonia burners in a 300-MW coal-fired power plant to achieve ammonia–coal co-combustion at proportions ranging from 20% to 10% (by heat ratio) at loads of 180- to 300-MW, respectively. The results show that, during ammonia–coal co-combustion in a 300-MW coal-fired power plant, there was a more significant change in NOx emissions at the furnace outlet compared with that under pure-coal combustion as the boiler oxygen levels varied. Moreover, ammonia burners located in the middle part of the main combustion zone exhibited a better high-temperature reduction performance than those located in the upper part of the main combustion zone. Under all ammonia co-combustion conditions, the NH3 concentration at the furnace outlet remained below 1 parts per million (ppm). Compared with that under pure-coal conditions, the thermal efficiency of the boiler slightly decreased (by 0.12%–0.38%) under different loads when ammonia co-combustion reached 15 t·h−1. Ammonia co-combustion in coal-fired power plants is a potentially feasible technology route for carbon reduction.

As the most advanced vitrification technology，cold crucible has a wide application prospect. As the first countries to study the cold crucible vitrification technology，Russia and France have kept there own technical characteristics in the process of research and development，at the same time，there have also carried out continuous technological innovation and cooperation，and all achieved industrialization. This paper reviews the research and development process of cold crucible in Russia and France，and puts forward development suggestions on China’s cold crucible technology from three aspects: basic research，operational experience and application fields.

Abstract Background Spinal muscular atrophy (SMA) is a rare autosomal recessive hereditary neuromuscular disease caused by survival motor neuron 1 (SMN1) gene deletion or mutation. Homozygous deletions of exon 7 in SMN1 result in 95% of SMA cases, while the remaining 5% are caused by other pathogenic variants of SMN1. Methods We analyzed two SMA-suspected cases that were collected, with no SMN1 gene deletion and point mutation in whole-exome sequencing. Exon 1 deletion of the SMN gene was detected using Multiplex ligation-dependent probe amplification (MLPA) P021. We used long-range polymerase chain reaction (PCR) to isolate the SMN1 template, optimized-MLPA P021 for copy number variation (CNV) analysis within SMN1 only, and validated the findings via third-generation sequencing. Results Two unrelated families shared a genotype with one copy of exon 7 and a novel variant, g.70919941_70927324del, in isolated exon 1 of the SMN1 gene. Case F1-II.1 demonstrated no exon 1 but retained other exons, whereas F2-II.1 had an exon 1 deletion in a single SMN1 gene. The read coverage in the third-generation sequencing results of both F1-II.1 and F2-II.1 revealed a deletion of approximately 7.3 kb in the 5’ region of SMN1. The first nucleotide in the sequence data aligned to the 7385 bp of NG_008691.1. Conclusion Remarkably, two proband families demonstrated identical SMN1 exon 1 breakpoint sites, hinting at a potential novel mutation hotspot in Chinese SMA, expanding the variation spectrum of the SMN1 gene and corroborating the specificity of isolated exon 1 deletion in SMA pathogenesis. The optimized-MLPA P021 determined a novel variant (g.70919941_70927324del) in isolated exon 1 of the SMN1 gene based on long-range PCR, enabling efficient and affordable detection of SMN gene variations in patients with SMA, providing new insight into SMA diagnosis to SMN1 deficiency and an optimized workflow for single exon CNV testing of the SMN gene.

Improving the sustainability and processability of shape memory composites is key to expanding their applications. This work introduces a novel bio-based shape memory composite resin with renewable cellulose nanocrystals, suitable for stereolithography (SLA) printing. We prepared epoxy soybean oil-based composites by incorporating Itaconic acid monomethyl ester (IAME) modified cellulose nanocrystals (CNCs-IAME) into IAME modified epoxy soybean oil (IESO). The CNCs-IAME/IESO composite resin, with a viscosity of 1.01–1.22 Pa•s, is ideal for SLA printing. Adding 0.75 wt% CNCs-IAME particles enhances mechanical properties, yielding a tensile strength of 19.54 MPa and elongation at a break of 34.03%. Demonstrated applications include flexible supports and temperature-responsive sensors. This innovative composite offers excellent sustainability and SLA-printability, showing great potential for new bio-based heat-activated shape memory materials.

Under the global climate challenges, accurate assessment of forest variables is becoming increasingly important for effective forest management and monitoring. While long-wavelength satellite radar data (P-, L-band) has been widely used for this purpose, the potential of airborne Ku-band microwave radar remains underexplored. In this paper, an airborne Ku-band frequency modulated continuous wave (FMCW) profiling radar data was used to predict forest variables including plot-level basal-area weighted mean canopy height (Hg), mean diameter at breast height (DBHg), stem volume (V) and above ground biomass (AGB) using the random forest method. In addition, the maximum canopy heights were computed from the radar-derived results. The estimated results were compared with 55 manually-measured and accurately matched field plots consisting of thousands of trees. The comparison results show that the estimation accuracy is at a good level, with the relative Root Mean Square Errors (RMSE%) and the coefficient of determination (R2) of the four variables were Hg (10.04 %, 0.75), DBHg (17.25 %, 0.63), V (21.11 %, 0.67) and AGB (19.75 %, 0.63), respectively. The estimation of plot-level maximum heights resulted in a relative RMSE of 7.95 % and R2 of 0.89. Through comparing with previous similar studies, the accuracies of estimating the four variables from airborne Ku-band data are comparable to those of high-precision satellite microwave radar data. The study results indicate that the canopy gaps and adequate penetration of airborne Ku-band signals into the canopy enable the characterization of the canopy layer and the ground floor, allowing for accurate estimation of forest variables in boreal forests.

Abstract Stable solid electrolytes are essential to high-safety and high-energy-density lithium batteries, especially for applications with high-voltage cathodes. In such conditions, solid electrolytes may experience severe oxidation, decomposition, and deactivation during charging at high voltages, leading to inadequate cycling performance and even cell failure. Here, we address the high-voltage limitation of halide solid electrolytes by introducing local lattice distortion to confine the distribution of Cl−, which effectively curbs kinetics of their oxidation. The confinement is realized by substituting In with multiple elements in Li3InCl6 to give a high-entropy Li2.75Y0.16Er0.16Yb0.16In0.25Zr0.25Cl6. Meanwhile, the lattice distortion promotes longer Li-Cl bonds, facilitating favorable activation of Li+. Our results show that this high-entropy halide electrolyte boosts the cycle stability of all-solid-state battery by 250% improvement over 500 cycles. In particular, the cell provides a higher discharge capacity of 185 mAh g−1 by increasing the charge cut-off voltage to 4.6 V at a small current rate of 0.2 C, which is more challenging to electrolytes|cathode stability. These findings deepen our understanding of high-entropy materials, advancing their use in energy-related applications.

Femtosecond-laser-fabricated black silicon has been widely used in the fields of solar cells, photodetectors, semiconductor devices, optical coatings, and quantum computing. However, the responsive spectral range limits its application in the near- to mid-infrared wavelengths. To further increase the optical responsivity in longer wavelengths, in this work, silicon (Si) was co-hyperdoped with nitrogen (N) and selenium (Se) through the deposition of Se films on Si followed by femtosecond (fs)-laser irradiation in an atmosphere of NF3. The optical and crystalline properties of the Si:N/Se were found to be influenced by the precursor Se film and laser fluence. The resulting photodetector, a product of this innovative approach, exhibited an impressive responsivity of 24.8 A/W at 840 nm and 19.8 A/W at 1060 nm, surpassing photodetectors made from Si:N, Si:S, and Si:S/Se (the latter two fabricated in SF6). These findings underscore the co-hyperdoping method’s potential in significantly improving optoelectronic device performance.

In the fields of agriculture and forestry, the Normalized Difference Vegetation Index (NDVI) is a critical indicator for assessing the physiological state of plants. Traditional imaging sensors can only collect two-dimensional vegetation distribution data, while dual-wavelength LiDAR technology offers the capability to capture vertical distribution information, which is essential for forest structure recovery and precision agriculture management. However, existing LiDAR systems face challenges in detecting echoes at two wavelengths, typically relying on multiple detectors or array sensors, leading to high costs, bulky systems, and slow detection rates. This study introduces a time-stretched method to separate two laser wavelengths in the time dimension, enabling a more cost-effective and efficient dual-spectral (600 nm and 800 nm) LiDAR system. Utilizing a supercontinuum laser and a single-pixel detector, the system incorporates specifically designed time-stretched transmission optics, enhancing the efficiency of NDVI data collection. We validated the ranging performance of the system, achieving an accuracy of approximately 3 mm by collecting data with a high sampling rate oscilloscope. Furthermore, by detecting branches, soil, and leaves in various health conditions, we evaluated the system’s performance. The dual-wavelength LiDAR can detect variations in NDVI due to differences in chlorophyll concentration and water content. Additionally, we used the radar equation to analyze the actual scene, clarifying the impact of the incidence angle on reflectance and NDVI. Scanning the Red Sumach, we obtained its NDVI distribution, demonstrating its physical characteristics. In conclusion, the proposed dual-wavelength LiDAR based on the time-stretched method has proven effective in agricultural and forestry applications, offering a new technological approach for future precision agriculture and forest management.

Abstract Herein, we fabricated a flexible semidry electrode with excellent mechanical performance, satisfactory self‐adhesiveness, and low‐contact impedance using physical/chemical crosslinked polyvinyl alcohol/polyacrylamide dual‐network hydrogels (PVA/PAM DNHs) as an efficient saline reservoir. The resultant PVA/PAM DNHs showed admirable adhesive and compliance to the hairy scalp, facilitating the establishment of a robust electrode/skin interface for biopotential signal transmission. Moreover, the PVA/PAM DNHs steadily released trace saline onto the scalp to achieve the minimized potential drift (1.47 ± 0.39 mV/min) and low electrode–scalp impedance (18.2 ± 8.9 kΩ @ 10 Hz). More importantly, the application feasibility of real‐world brain−computer interfaces (BCIs) was preliminarily validated by 10 participants using two classic BCI paradigms. The mean temporal cross‐correlation coefficients between the semidry and wet electrodes in the eyes open/closed and the N200 speller paradigms are 0.919 ± 0.054 and 0.912 ± 0.050, respectively. Both electrodes demonstrate anticipated neuroelectrophysiological responses with similar patterns. This semidry electrode could also effectively capture robust P‐QRS‐T peaks during electrocardiogram recording. Considering their outstanding advantages of fast setup, user‐friendliness, and robust signals, the proposed PVA/PAM DNH‐based electrode is a promising alternative to wet electrodes in biopotential signal acquisition.

Abstract Background Hepatocellular carcinoma (HCC), the most common primary liver cancer, prevails mainly in males and has long been attributed to androgens and higher circumstantial levels of interleukin-6 (IL-6) produced by resident hepatic macrophages. Methods Constitutively hepatocyte-specific histone deacetylase 3 (HDAC3)-deficient (HDAC3 LCKO ) mice and constitutively hepatocyte-specific HDAC3 knockout and systemic IL-6 simultaneously ablated (HDAC3 LCKO & IL-6 −/− ) mice were used in our study to explore the causes of sex differences in HCC. Additionally, we performed human HCC tissues with an IHC score. Correlation analysis and linear regression plots were constructed to reveal the association between HDAC3 and its candidate genes. To further elucidate that HDAC3 controls the expression of Foxa1/2, we knocked down HDAC3 in HUH7 liver cancer cells. Results We observed a contrary sex disparity, with an earlier onset and higher incidence of HCC in female mice when HDAC3 was selectively ablated in the liver. Loss of HDAC3 led to constant liver injury and the spontaneous development of HCC. Unlike the significant elevation of IL-6 in male mice at a very early age, female mice exhibit stable IL-6 levels, and IL-6 ablation did not eliminate the sex disparity in hepatocarcinogenesis in HDAC3-deficient mice. Oestrogen often protects the liver when combined with oestrogen receptor alpha (ERα); however, ovariectomy in HDAC3-ablated female mice significantly delayed tumourigenesis. The oestrogen-ERα axis can also play a role in tumour promotion in the absence of Foxa1 and Foxa2 in the receptor complex. Loss of HDAC3 profoundly reduced the expression of both Foxa1 and Foxa2 and impaired the binding between Foxa1/2 and ERα. Furthermore, a more frequent HDAC3 decrease accompanied by the simultaneous Foxa1/2 decline was found in female HCC compared to that in male HCC. Conclusion In summary, we reported that loss of HDAC3 reduces Foxa1/2 and thus promotes HCC development in females in an oestrogen-dependent manner.

Abstract. Background:. Glutamine synthetase (GS) and arginase 1 (Arg1) are widely used pathological markers that discriminate hepatocellular carcinoma (HCC) from intrahepatic cholangiocarcinoma; however, their clinical significance in HCC remains unclear. Methods:. We retrospectively analyzed 431 HCC patients: 251 received hepatectomy alone, and the other 180 received sorafenib as adjuvant treatment after hepatectomy. Expression of GS and Arg1 in tumor specimens was evaluated using immunostaining. mRNA sequencing and immunostaining to detect progenitor markers (cytokeratin 19 [CK19] and epithelial cell adhesion molecule [EpCAM]) and mutant TP53 were also conducted. Results:. Up to 72.4% (312/431) of HCC tumors were GS positive (GS+). Of the patients receiving hepatectomy alone, GS negative (GS−) patients had significantly better overall survival (OS) and recurrence-free survival (RFS) than GS+ patients; negative expression of Arg1, which is exclusively expressed in GS− hepatocytes in the healthy liver, had a negative effect on prognosis. Of the patients with a high risk of recurrence who received additional sorafenib treatment, GS− patients tended to have better RFS than GS+ patients, regardless of the expression status of Arg1. GS+ HCC tumors exhibit many features of the established proliferation molecular stratification subtype, including poor differentiation, high alpha-fetoprotein levels, increased progenitor tumor cells, TP53 mutation, and upregulation of multiple tumor-related signaling pathways. Conclusions:. GS− HCC patients have a better prognosis and are more likely to benefit from sorafenib treatment after hepatectomy. Immunostaining of GS may provide a simple and applicable approach for HCC molecular stratification to predict prognosis and guide targeted therapy.

The sub-lakes of Poyang Lake have significant ecological value. To date, the diazotrophs in sub-lakes are unknown. Moreover, no study has simultaneously focused on diazotrophic communities in the water and sediment in natural freshwater ecosystems. In this study, we investigated the diazotrophic alpha diversity, structure, abundance, molecular ecological network, and community assembly mechanism in the water and sediment of sub-lakes using Illumina MiSeq sequencing and a quantitative polymerase chain reaction assay. The results showed that the sediment had a greater diversity of diazotrophs than the water. Proteobacteria and Spirochaetes were the dominant diazotrophic phyla in the water, whereas Proteobacteria was the dominant diazotrophic phylum in the sediment. There were significant differences in the composition of diazotrophic communities between the water and sediment. The sediment had a more complex co-occurrence network of diazotrophs than the water. Deterministic processes dominate the community assembly of diazotrophs in both the water and sediment of the sub-lakes, and the relative role of deterministic processes was stronger for sediment than water. Our study is the first to reveal the differences in the diazotrophic communities between the water and sediment in natural freshwater ecosystems and provides the fundamental scientific datasets for understanding the nitrogen fixation process in sub-lakes.

Microfluidic mixers, a pivotal application of microfluidic technology, are primarily utilized for the rapid amalgamation of diverse samples within microscale devices. Given the intricacy of their design processes and the substantial expertise required from designers, the intelligent automation of microfluidic mixer design has garnered significant attention. This paper discusses an approach that integrates artificial neural networks (ANNs) with reinforcement learning techniques to automate the dimensional parameter design of microfluidic mixers. In this study, we selected two typical microfluidic mixer structures for testing and trained two neural network models, both highly precise and cost-efficient, as alternatives to traditional, time-consuming finite-element simulations using up to 10,000 sets of COMSOL simulation data. By defining effective state evaluation functions for the reinforcement learning agents, we utilized the trained agents to successfully validate the automated design of dimensional parameters for these mixer structures. The tests demonstrated that the first mixer model could be automatically optimized in just 0.129 s, and the second in 0.169 s, significantly reducing the time compared to manual design. The simulation results validated the potential of reinforcement learning techniques in the automated design of microfluidic mixers, offering a new solution in this field.

Water level fluctuations (WLFs) are typical characteristic of floodplain lakes and dominant forces regulating the structure and function of lacustrine ecosystems. The sediment diazotrophs play important roles in contributing bioavailable nitrogen to the aquatic environment. However, the relationship between the diazotrophic community and WLFs in floodplain lakes is unknown. In this paper, we carried out a comprehensive investigation on the alpha diversity, abundance, composition and co-occurrence network of the sediment diazotrophs during different water level phases in Poyang Lake. There were no regular variation patterns in the alpha diversity and abundance of the sediment diazotrophs with the water level phase transitions. The relative abundance of some diazotrophic phyla (including Alphaproteobacteria, Deltaproteobacteri, Euryarchaeota, and Firmicutes) and genera (including Geobacter, Deferrisoma, Desulfuromonas, Rivicola, Paraburkholderia, Methylophilus, Methanothrix, Methanobacterium, and Clostridium) was found to change with the water level phase transitions. The results of ANOSIM, PerMANOVA, and DCA at the OTU level showed that the diazotrophic community structure in the low water level phase was significantly different from that in the two high water level phases, while there was no significant difference between the two high water level phases. These results indicated that the diazotrophic community was affected by the declining water level in terms of the composition, while the rising water level contributed to the recoveries of the diazotrophic community. The diazotrophs co-occurrence network was disrupted by the declining water level, but it was strengthened by the rising water level. Moreover, redundancy analysis showed that the variation of the diazotrophic community composition was mostly related to sediment total nitrogen (TN) and total phosphorous (TP). Interestingly, the levels of sediment TN and TP were also found to vary with the water level phase transitions. Therefore, it might be speculated that the WLFs may influence the sediment TN and TP, and in turn influence the diazotrophic community composition. These data can contribute to broadening our understanding of the ecological impacts of WLFs and the nitrogen fixation process in floodplain lakes.

Abstract Exosomal miRNAs are known to play important roles in ovarian cancer and chemotherapeutic resistance. However, a systematic evaluation of characteristics of exosomal miRNAs involved in cisplatin resistance in ovarian cancer remains totally unclear. Exosomes (Exo-A2780, Exo-A2780/DDP) were extracted from cisplatin-sensitive cells (A2780) and cisplatin-resistant cells (A2780/DDP). Differential exosomal miRNA expression profiles were found by high-throughput sequencing (HTS). Target genes of the exo-miRNAs were predicted by using two online databases to increase the prediction accuracy. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were utilized to find biological relationships with chemoresistance. RT‒qPCR of three exosomal miRNAs was performed, and a protein‒protein interaction (PPI) network was established to identify the hub genes. The GDSC database was used to prove the association between hsa-miR-675-3p expression and the IC50 value. An integrated miRNA–mRNA network was constructed to predict miRNA–mRNA associations. The connection between hsa-miR-675-3p and ovarian cancer was discovered by immune microenvironment analyses. The upregulated exosomal miRNAs could regulate gene targets through signalling pathways such as the Ras, PI3K/Akt, Wnt, and ErbB pathways. GO and KEGG analyses indicated that the target genes were involved in protein binding, transcription regulator activity and DNA binding. The RT‒qPCR results were consistent with the HTS data, and the results of PPI network analysis suggested that FMR1 and CD86 were the hub genes. GDSC database analysis and construction of the integrated miRNA–mRNA network suggested that hsa-miR-675-3p was associated with drug resistance. Immune microenvironment analyses showed that hsa-miR-675-3p was crucial in ovarian cancer. The study suggested that exosomal hsa-miR-675-3p is a potential target for treating ovarian cancer and overcoming cisplatin resistance.

Dielectric elastomer is a kind of electronic electroactive polymer, which plays an important role in the application of soft robots and flexible electronics. In this study, an all-organic polyaniline/copper phthalocyanine/silicone rubber (PANI/CuPc/PDMS) dielectric composite with superior comprehensive properties was prepared by manipulating the arrangement of filler in a polymer matrix assisted by electric fields. Both CuPc particles and PANI particles can form network structures in the PDMS matrix by self-assembly under electric fields, which can enhance the dielectric properties of the composites at low filler content. The dielectric constant of the assembled PANI/CuPc/PDMS composites can reach up to 140 at 100 Hz when the content of CuPc and PANI particles is 4 wt% and 2.5 wt%, respectively. Moreover, the elastic modulus of the composites remains below 2 MPa, which is important for electro-deforming. The strain of assembled PANI/CuPc/PDMS three-phase composites at low electric field strength (2 kV/mm) can increase up to five times the composites with randomly dispersed particles, which makes this composite have potential application in the field of soft robots and flexible electronics.

Hyperspectral LiDAR (HSL) has been utilized as an efficacious technique in object classification and recognition based on its unique capability to obtain ranges and spectra synchronously. Different kinds of HSL prototypes with varied structures have been promoted and measured its performance. However, almost all of these HSL prototypes employ complex and large spectroscopic devices, such as an Acousto-Optic Tunable Filter and Liquid-Crystal Tunable Filter, which makes this HSL system bulky and expensive, and then hinders its extensive application in many fields. In this paper, a smart and smaller spectroscopic component, an intergraded optical filter (IOF), is promoted to miniaturize these HSL systems. The system calibration, range precision, and spectral profile experiments were carried out to test the HSL prototype. Although the IOF employed here only covered a wavelength range of 699–758 nm with a six-channel passband and showed a transmittance of less than 50%, the HSL prototype showed excellent performance in ranging and spectral profile collecting. The spectral profiles collected are well in accordance with those acquired based on the AOTF. The spectral profiles of the fruits, vegetables, plants, and ore samples collected by the HSL based on an IOF can effectively reveal the status of the plants, the component materials, and ore species. Finally, we also showed the integrated design of the HSL based on a three-dimensional IOF and combined with a detector. The performance and designs of this HSL system based on an IOF show great potential for miniaturizing in some specific applications.

1-Deoxynojirimycin (DNJ) is a type of alkaloid that mainly exists in mulberry fruit and leaves. DNJ inhibits α-glucosidase, reduces the absorption of sugar, and suppresses after-meal hyperglycemia. It was reported that DNJ functions in attenuating cellular oxidative stress. However, the mechanisms remain largely unknown. In this study, we firstly confirmed that 5 µmol/L DNJ treatment mitigated the oxidative DNA damage and cell senescence in human umbilical vein endothelial cells (HUVEC) cultured in medium containing 50 mmol/L glucose. Next, we found that DNJ treatment stimulates the expression of anti-oxidative response regulator, Nuclear factor (erythroid-derived 2)-like 2 (NRF2) by around 50% in cells cultured with high glucose. In addition, 8-oxoguanine DNA glycosylase (OGG1) was upregulated by over 15% after DNJ treatment to mitigate high-glucose-induced oxidative DNA damage, and it was identified as a downstream target of NRF2. Further, DNJ treatment promoted the phosphorylation and activation of AKT (ser473) by around 50% in cells cultured with high glucose, and AKT inhibitor treatment abrogated DNJ-induced upregulation of NRF2 and OGG1. Taken together, our results indicate that DNJ is an effective natural antioxidant in mitigating high-glucose-induced oxidative stress in HUVEC via activating the AKT-NRF2-OGG1 anti-oxidative response.

Indoor positioning plays a crucial role in various domains. It is employed in various applications, such as navigation, asset tracking, and location-based services (LBS), in Global Navigation Satellite System (GNSS) denied or degraded areas. The visual-based positioning technique is a promising solution for high-accuracy indoor positioning. However, most visual positioning research uses the side-view perspective, which is susceptible to interferences and may cause concerns about privacy and public security. Therefore, this paper innovatively proposes an up-view visual-based indoor positioning algorithm. It uses the up-view images to realize indoor positioning. Firstly, we utilize a well-trained YOLO V7 model to realize landmark detection and gross extraction. Then, we use edge detection operators to realize the precision landmark extraction, obtaining the landmark pixel size. The target position is calculated based on the landmark detection and extraction results and the pre-labeled landmark sequence via the Similar Triangle Principle. Additionally, we also propose an inertial navigation system (INS)-based landmark matching method to match the landmark within an up-view image with a landmark in the pre-labeled landmark sequence. This is necessary for kinematic indoor positioning. Finally, we conduct static and kinematic experiments to verify the feasibility and performance of the up-view-based indoor positioning method. The results demonstrate that the up-view visual-based positioning is prospective and worthy of research.

Dredging, adsorbent inactivation, and phytoremediation are commonly used to control internal nitrogen and phosphorus sediment loads in eutrophic still-water ecosystems, such as lakes and ponds. However, the effectiveness of these remediation techniques has not been verified for rivers, lakes, and reservoirs with large disturbances. In this study, a calcium-loaded clay granular adsorbent (CRB) was prepared as an alternative to commercial adsorbents, and an experiment was conducted on the ecological restoration effects of both dredging and adsorbent single treatments as well as combined treatments on eutrophic flowing water. The enhancement effect of phytoremediation on the above restoration techniques was investigated. The results indicated that CRB inactivation treatment reduced the phosphorus and turbidity of the water by 63% and 80%, respectively and increased the total nitrogen and permanganate index (CODMn) by 25% and 101% before phytoremediation, respectively compared to the control group. There were no significant differences in the nutrient indexes of the sediment and water between the dredging treatment and the control group, but dredging enhanced the effect of the CRB treatment. Compared with the CRB treatment, the total nitrogen and CODMn of water in the dredging and combined CRB treatments decreased by 13% and 15%, respectively. Phytoremediation significantly improved the effectiveness of the dredging and adsorbent treatments, both individually and in combination. Additionally, there were notable differences in the growth rates of the submerged plants and the contents of different phosphorus speciation among the plant species. Selecting suitable plant species is recommended when implementing phytoremediation methods. This study highlights that the combination of multiple restoration techniques is effective for eutrophic flowing water. The results provide a guide for the ecological restoration of flowing water.

There is no gold standard for the diagnosis of coagulation dysfunction in sepsis, and the use of the current scoring systems is still controversial. The purpose of this study was to assess the performance of sepsis-induced coagulopathy (SIC), the Japanese Association for Acute Medicine Disseminated Intravascular Coagulation (JAAM DIC), and the International Society on Thrombosis and Haemostasis overt DIC (ISTH overt-DIC). The relationship between each scoring system and 28-day all-cause mortality was examined. Among 452 patients (mean age, 65 [48,76] years), 306 [66.7%] were men, the median SOFA score was 6 [4,9], and the median APACHE II score was 15 [11,22]. A total of 132 patients (29.2%) died within 28 days. Both the diagnosis of SIC (AUROC, 0.779 [95% CI, 0.728–0.830], P

Abstract Background Autophagy is a highly conserved cellular proteolytic process that can interact with innate immune signaling pathways to affect the growth of tumor cells. However, the regulatory mechanism of autophagy in the tumor microenvironment, drug sensitivity, and immunotherapy is still unclear. Methods Based on the prognostic autophagy-related genes, we used the unsupervised clustering method to divide 866 ovarian cancer samples into two regulatory patterns. According to the phenotypic regulation pattern formed by the differential gene between the two regulation patterns, a risk model was constructed to quantify patients with ovarian cancer. Then, we systematically analyzed the relationship between the risk model and immune cell infiltration, immunotherapeutic response, and drug sensitivity. Results Based on autophagy-related genes, we found two autophagy regulation patterns, and confirmed that there were differences in prognosis and immune cell infiltration between them. Subsequently, we constructed a risk model, which was divided into a high-risk group and a low-risk group. We found that the high-risk group had a worse prognosis, and the main infiltrating immune cells were adaptive immune cells, such as Th2 cells, Tgd cells, eosinophils cells, and lymph vessels cells. The low-risk group had a better prognosis, and the most infiltrated immune cells were innate immune cells, such as aDC cells, NK CD56dim cells, and NK CD56bright cells. Furthermore, we found that the risk model could predict chemosensitivity and immunotherapy response, suggesting that the risk model may help to formulate personalized treatment plans for patients. Conclusions Our study comprehensively analyzed the prognostic potential of autophagy-related risk models in ovarian cancer and determined their clinical guiding role in targeted therapy and immunotherapy.

Hyperspectral LiDAR (HSL) has been utilised as an efficacious technique in objects classification and recognition based on its synchronously obtaining spectral and spatial information. However, the spectral information obtained by most of the developed HSL was in the visible and near-infrared range (VNIR, 400–1000 nm). Whereas spectral information in a longer wavelength range showed more useful for classification and detection, such as detecting vegetation water content. This paper proposed and tested an eight-channel HSL prototype covering visible to near-infrared and even short-wavelength infrared (VIS-NIR-SWIR, 450–1460 nm) based on a Super-continuum (SC) laser. System calibration, range precision and spectral profiles experiments were carried out to test the HSL prototype. The spectral profiles collected by the HSL are consistent with those acquired by the commercial spectrometer (SVC© HR-1024). And these spectral profiles of plants, textiles, camouflage objects, and ore samples collected by the HSL, especially those in the SWIR range, can effectively reveal the health status of the plants, and classify the manufacturing materials and ore species. The unique characteristics of spectral profiles covering VIS-NIR-SWIR promote the HSL shows the potential applications on objects classification related to vegetation, mining and surveillance.

Battery energy storage systems (BESS) are regarded as a multi-functional power system participator, participating in the energy arbitrage strategy (EAS), the frequency regulation strategy (FRS) and so on. However, the existing BESS mainly make profit from the EAS instead of the FRS in many countries such as China. Because there is no appropriate control strategy for BESS, when the developing ancillary services market cannot price the contribution of BESS in FRS. Meanwhile, BESS do have redundant power and capacity, if only the EAS is applied. Therefore, it is significant that BESS are involved in the FRS, that the EAS has the priority in BESS utilization. In this paper, a frequency regulation strategy for the user-side BESS is proposed, on the constraints of the planned energy arbitrage. Specifically, the chance-constrained programming is applied to solve the randomness of frequency regulation requirement, ensuring the BESS profit from the EAS. Also, the exiting BESS are fully used with extra profit from FRS. At last, the promising results prove the advantages of the proposed FRS.

The application of deep learning methods to remote sensing data has produced good results in recent studies. A promising application area is automatic land cover classification (semantic segmentation) from very high-resolution satellite imagery. However, the deep learning methods require large, labelled training datasets that are suitable for the study area. Map data can be used as training data, but it is often insufficiently detailed for very high-resolution satellite imagery. National airborne laser scanner (lidar) datasets provide additional details and are available in many countries. Successful land cover classifications from lidar datasets have been reached, e.g., by object-based image analysis. In the present study, we investigated the feasibility of using airborne laser scanner data and object-based image analysis to automatically generate labelled training data for a deep neural network -based land cover classification of a VHR satellite image. Input data for the object-based classification included digital surface models, intensity and pulse information derived from the lidar data. The resulting land cover classification was then utilized as training data for deep learning. A state-of-the-art deep learning architecture, UnetFormer, was trained and applied to the land cover classification of a WorldView-3 stereo dataset. For the semantic segmentation, three different input data composites were produced using the red, green, blue, NIR and digital surface model bands derived from the satellite data. The quality of the generated training data and the semantic segmentation results was estimated using an independent test set of ground truth points. The results show that final satellite image classification accuracy (94–96%) close to the training data accuracy (97%) was obtained. It was also demonstrated that the resulting maps could be used for land cover change detection.

Currently, the issue of eutrophication and cyanobacterial blooms persists in water bodies worldwide, prompting the exploration of various treatment methods. This study conducted a comparative analysis of eutrophic water bodies using ferric chloride-modified zeolite (FMZ) and calcium hydroxide-modified zeolite (CMZ) combined with Elodea nuttallii ( E. nuttallii ) for removal and purification effects. The results revealed that the addition of E. nuttallii had a sustained inhibitory effect on phosphorus release, maintaining stability with lower Turbidity(Tur) and stabilized pH within the range of 8.5–9. FMZ demonstrated rapid reduction in dissolved phosphorus concentration, achieving a removal rate of 96% within 3 days. The combined plant group of CMZ and FMZ exhibited synergistic effects with E. nuttallii , achieving an impressive total phosphorus (TP) removal rate of 80.13% and a total nitrogen (TN) removal rate of 48.77%. Additionally, chlorophyll a (Chl a ) concentration decreased from 100.74 ± 24.72 μ g l ^−1 to 49.96 ± 2.08 μ g l ^−1 . The phytoplankton community composition indicated that diatoms thrived in low temperatures and high NH _4 conditions. Under the same low Total Nitrogen to Total Phosphorus (TN:TP) ratio, high TP concentrations were associated with cyanobacteria dominance, while green algae dominated in other scenarios. This comprehensive approach demonstrates the potential efficacy of CMZ and FMZ combined with E. nuttallii in addressing eutrophic water bodies and mitigating cyanobacterial blooms.

The physical blending method was used in order to prepare nitrile-butadiene rubber/polyamide elastomer/single-walled carbon nanotube (NBR/PAE/SWCNT) composites with better thermal-oxidative aging resistance. The interactions between SWCNTs and NBR/PAE were characterized using the Moving Die Rheometer 2000 (MDR 2000), rheological behavior tests, the equilibrium swelling method, and mechanical property tests. The 100% constant tensile stress and hardness of NBR/PAE/SWCNT composites increased from 2.59 MPa to 4.14 MPa and from 62 Shore A to 69 Shore A, respectively, and the elongation decreased from 421% to 355% with increasing SWCNT content. NBR/PAE/SWCNT composites had improved thermal-oxidative aging resistance due to better interactions between SWCNTs and NBR/PAE. During the aging process, the tensile strength and elongation at break decreased with the increase in aging time compared to the unaged samples, and the constant tensile stress gradually increased. There was a more significant difference in the degradation of mechanical properties when aged in a variety of oils. The 100% constant tensile stress of NBR/PAE/SWCNT composites aged in IRM 903 gradually increased with aging time while it gradually decreased in biodiesel. The swelling index gradually increased with increasing SWCNT content. Interestingly, the swelling index of the composites in cyclohexanone decreased with the increase in SWCNT content. The reasons leading to different swelling behaviors when immersed in different kinds of liquids were investigated using the Hansen solubility parameter (HSP) method, which provides an excellent guide for the application of some oil-resistant products.

With versatile biological functions, microRNAs (miRNAs) participate in the regulation of post-transcriptional gene expression in plants. Tulipa thianschanica Regel is a key wild tulip resource of the Liliaceae; however, it reproduces poorly under natural conditions, and the spreading and expansion of its population rely on the release of its seeds. In this study, T. thianschanica seeds were subjected to stratification at 4 °C for three different durations: 1 d (physiological dormancy), 20 d (dormancy release), and 40 d (non-dormancy). Nine samples were selected, and miRNA databases were established and annotated. This research revealed information on 34 miRNA families, including 14 newly discovered families and 20 families that were previously known. TpmiRNA167 and TpmiRNA395 were observed to be upregulated. Conversely, TpmiRNA166, which targets the key enzymes involved in antioxidant reactions, was downregulated. Notably, PC-5p-84014 and TpmiRNA159 were found to target TpPYL and TpDELLA, respectively, which influenced the abscisic acid/gibberellin (ABA/GA) ratio. Additionally, TpmiRNA160 and TpmiRNA164 were found to participate in the indole-3-acetic acid signal transduction pathway and interact with ABA, thereby contributing to the release of dormancy. In conclusion, this study provides a comprehensive understanding of the mechanism used to release dormancy in T. thianschanica seeds at the molecular level.

Abstract Transmembrane of coiled-coil domains 1 (TMCO1) plays an important role in maintaining homeostasis of calcium (Ca2+) stores in the endoplasmic reticulum (ER). TMCO1-defect syndrome shares multiple features with human cerebro-facio-thoracic (CFT) dysplasia, including abnormal corpus callosum (CC). Here, we report that TMCO1 is required for the normal development of CC through sustaining Ca2+ homeostasis. Tmco1 −/− mice exhibit severe agenesis of CC with stalled white matter fiber bundles failing to pass across the midline. Mechanistically, the excessive Ca2+ signals caused by TMCO1 deficiency result in upregulation of FGFs and over-activation of ERK, leading to an excess of glial cell migration and overpopulated midline glia cells in the indusium griseum which secretes Slit2 to repulse extension of the neural fiber bundles before crossing the midline. Supportingly, using the clinical MEK inhibitors to attenuate the over-activated FGF/ERK signaling can significantly improve the CC formation in Tmco1 −/− brains. Our findings not only unravel the underlying mechanism of abnormal CC in TMCO1 defect syndrome, but also offer an attractive prevention strategy to relieve the related agenesis of CC in patients.

Abstract Plant growth-promoting rhizobacteria (PGPR) or Biocontrol strains inevitably encounter heavy metal excess stress during the product’s processing and application. Bacillus amyloliquefaciens Bam1 was a potential biocontrol strain with strong heavy metal resistant ability. To understand its heavy metal resistance mechanism, the complete genome of Bam1 had been sequenced, and the comparative genomic analysis of Bam1 and FZB42, an industrialized PGPR and biocontrol strain with relatively lower heavy metal tolerance, was conducted. The comparative genomic analysis of Bam1 and the other nine B. amyloliquefaciens strains as well as one Bacillus velezensis (genetically and physiologically very close to B. amyloliquefaciens) was also performed. Our results showed that the complete genome size of Bam1 was 3.95 Mb, 4219 coding sequences were predicted, and it possessed the highest number of unique genes among the eleven analyzed strains. Nine genes related to heavy metal resistance were detected within the twelve DNA islands of Bam1, while only two of them were detected within the seventeen DNA islands of FZB42. When compared with B. amyloliquefaciens type strain DSM7, Bam1 lacked contig L, whereas FZB42 lacked contig D and I, as well as just possessed contig B with a very small size. Our results could also deduce that Bam1 promoted its essential heavy metal resistance mainly by decreasing the import and increasing the export of heavy metals with the corresponding homeostasis systems, which are regulated by different metalloregulators. While Bam1 promoted its non-essential heavy metal resistance mainly by the activation of some specific or non-specific exporters responding to different heavy metals. The variation of the genes related to heavy metal resistance and the other differences of the genomes, including the different number and arrangement of contigs, as well as the number of the heavy metal resistant genes in Prophages and Genomic islands, led to the significant different resistance of Bam1 and FZB42 to heavy metals. Graphical Abstract

Abstract Background In modern animal husbandry, breeders pay increasing attention to improving sow nutrition during pregnancy and lactation to favor the health of neonates. Sow milk is a main food source for piglets during their first three weeks of life, which is not only a rich repository of essential nutrients and a broad range of bioactive compounds, but also an indispensable source of commensal bacteria. Maternal milk microorganisms are important sources of commensal bacteria for the neonatal gut. Bacteria from maternal milk may confer a health benefit on the host. Methods Sow milk bacteria were isolated using culturomics followed by identification using 16S rRNA gene sequencing. To screen isolates for potential probiotic activity, the functional evaluation was conducted to assess their antagonistic activity against pathogens in vitro and evaluate their resistance against oxidative stress in damaged Drosophila induced by paraquat. In a piglet feeding trial, a total of 54 newborn suckling piglets were chosen from nine sows and randomly assigned to three treatments with different concentrations of a candidate strain. Multiple approaches were carried out to verify its antioxidant function including western blotting, enzyme activity analysis, metabolomics and 16S rRNA gene amplicon sequencing. Results The 1240 isolates were screened out from the sow milk microbiota and grouped into 271 bacterial taxa based on a nonredundant set of 16S rRNA gene sequencing. Among 80 Pediococcus isolates, a new Pediococcus pentosaceus strain (SMM914) showed the best performance in inhibition ability against swine pathogens and in a Drosophila model challenged by paraquat. Pretreatment of piglets with SMM914 induced the Nrf2-Keap1 antioxidant signaling pathway and greatly affected the pathways of amino acid metabolism and lipid metabolism in plasma. In the colon, the relative abundance of Lactobacillus was significantly increased in the high dose SMM914 group compared with the control group. Conclusion P. pentosaceus SMM914 is a promising probiotic conferring antioxidant capacity by activating the Nrf2-Keap1 antioxidant signaling pathway in piglets. Our study provided useful resources for better understanding the relationships between the maternal microbiota and offspring. Video Abstract

Underwater noise pollution from the world’s longest cross-sea bridge—the Hong Kong-Zhuhai-Macao Bridge (HZMB)—which stretches across the Chinese White Dolphin National Nature Reserve (of the People’s Republic of China, PRC) in the Pearl River Estuary may affect the distribution of local humpback dolphins. In this study, static passive acoustic monitoring was applied to monitor biosonar activity of humpback dolphins and underwater noise adjacent to the tunnel section of the HZMB for more than one year. During the monitoring period, dolphin biosonar signals were detected on 88.5% of days. A significant temporal pattern occurred in dolphin biosonar activity and in anthropogenic noise. Biosonar activity was significantly higher at night than during the day, whereas underwater noise occurred more in the day than at night. Significantly more echolocation signals were detected in winter-spring than in summer-autumn, and highest acoustic activity occurred significantly more during high tide than at other tidal periods. In addition, the negative correlation between elevated underwater noise and dolphin sonar activity in winter suggests that dolphins may avoid noisy waters for short periods, perhaps due to auditory stress, but fish prey movement cannot be ruled out. These findings facilitate understanding activity patterns of humpback dolphins in the Pearl River Estuary and may contribute to conservation efforts.

Vortex beams accompanied with orbital angular momentum have attracted significant attention in research fields due to their formidable capabilities in various crucial applications. However, conventional devices for generating vortex beams still suffer from bulky sizes, high cost, and confined performances. Metalens, as an advanced platform to arbitrarily control the optical waves, has promising prospects to address the predicament for conventional devices. Although great progress has been demonstrated in the applications of vortex beams, they are still confronted with fixed functionality after fabrication that severely hinders their application range. In this work, the phase-change material of Ge2Sb2Te5 (GST) is employed to design the meta-atoms to realize tunable optical responses. Moreover, the focused vortex beam can be accomplished by superimposing a helical phase and hyperbolic phase, and the chromatic aberrations in near-infrared (NIR) range can be corrected by introducing an additional phase compensation. And the design strategy is validated by two different metalenses (BAMTF-1 and BAMTF-2). The numerical results indicate that the chromatic aberrations for two metalens can be corrected in 1.33–1.60 μm covering the telecom range. Moreover, the average focusing efficiency of BAMTF-1 is 51.4%, and that of BAMTF-2 is 39.9%, indicating the favorable performances of designed BAMTF. More importantly, their average focal lengths have a relative tuning range of 38.82% and 33.17% by altering the crystallization ratio of GST, respectively. This work may provide a significant scheme for on-chip and tunable devices for NIR imaging and communication systems.

A smartphone equipped with a Global Navigation Satellite System (GNSS) module can generate positional information for location-based services. However, GNSS signals are susceptible to fragility, multipath (MP), and Non-Line-Of-Sight (NLOS) interference, which can lead to a degradation in the accuracy of GNSS positioning on smartphones. Due to limitations in the smartphone’s antenna, GNSS signal strength is typically lower. Moreover, in urban areas, where smartphones rely on GNSS, MP and NLOS signals are the primary factors impeding accurate positioning. In this paper, with the goal of enhancing both the accuracy and robustness of smartphone GNSS positioning, we propose two methods. Firstly, an optimized particle filter method employing a Krill Herd Algorithm (KHA) is suggested for the integration of GNSS and Pedestrian Dead Reckoning (PDR). Secondly, a probabilistic approach is presented to identify faulty GNSS measurements using step distance information obtained from the PDR. Experimental tests were conducted using smartphones to evaluate the performance of the proposed method. The results demonstrate that both the KHA and fault detection methods effectively enhance the performance of integrated PDR and GNSS.

The Sustainable Development Goals Science Satellite-1 (SDGSAT-1) Glimmer Imager for Urbanization (GIU) data is very sensitive to low radiation and capable of detecting weak light sources from vessels at night while significantly improving the spatial resolution compared to similar products. Most existing methods fail to use the relevant characteristics of vessels effectively, and it is difficult to deal with the complex shape of vessels in high-resolution Nighttime Light (NTL) data, resulting in unsatisfactory detection results. Considering the overall sparse distribution of vessels and the light source diffusion phenomenon, a novel vessel detection method is proposed in this paper, utilizing the high spatial resolution of the SDGSAT-1. More specifically, noise separation is completed based on a local contrast-weighted RPCA. Then, artificial light sources are detected based on a density clustering algorithm, and an inter-cluster merging method is utilized to realize vessel detection further. We selected three research areas, namely, the Bohai Sea, the East China Sea, and the Gulf of Mexico, to establish a vessel dataset and applied the algorithm to the dataset. The results show that the total detection accuracy and the recall rate of the detection algorithm in our dataset are 96.84% and 96.67%, which is significantly better performance than other methods used for comparison in the experiment. The algorithm overcomes the dataset’s complex target shapes and noise conditions and achieves good results, which proves the applicability of the algorithm.

The investigation of stochastic optimal power flow (SOPF) is to seek the optimal solution of static stability constrained optimal power flow considering the uncertainty of parameters in power systems. To solve the problem, this paper proposes an approach based on the stochastic collocation method (SCM) and Gram-Charlier expansion to obtain the optimal solution of SOPF. Firstly, the SOPF model to simultaneously consider uncertainties and static stability is formulated. Then, probabilistic chance constraints are reformulated as a set of deterministic constraints using polynomial approximation, which explicitly describe the relationship between the probability of chance constraints and control variables. By applying the primal-dual interior point method to the reformulated SOPF model, the optimal solution can be efficiently obtained. The proposed SCM-based approach has been thoroughly tested on a modified 3-machine 9-bus system and IEEE 118-bus system, which verifies the effectiveness and accuracy of the proposed method.

Wood–leaf separation aiming at classifying LiDAR points into wood and leaf components is one of the most important genres for improving leaf area index estimation and forestry survey accuracy. The wood return signals could artificially increase the apparent foliage content, which needs to be screened out for deriving vital tree attributes accurately. Previous research works tended to use intensity, waveform, and geometric information extracted from a single wavelength LiDAR for wood–leaf separation. This article employs a revised hyperspectral LiDAR (HSL) to obtain spatial and ultrawide spectral data simultaneously. We also propose a simple three steps method to separate wood and leaf components based on HSL spatial and spectral measurements under the laboratory circumstances. First, the preprocessing is conducted to acquire 3-D spatial information and the multiband laser pulse reflectance for further separation. Second, preliminary separation (band division, key feature parameter calculation, and judgment) is implemented based on reflectance. Third, we employ K-Nearest Neighbor (KNN) method to enhance separation results based on preliminary separation results and spatial features and then update the results by recorrection. Then, 3-D reconstruction is accomplished by fusing wood–leaf separation results. The experimental results demonstrate that the proposed method can separate wood and leaf components with high accuracy and indicate tree attributes straightforwardly.

Modular multilevel converter-based high-voltage direct current (MMC-HVDC) transmission is becoming a trend in offshore wind-farm integration. However, the large DC-side energy dissipation equipment, which is utilized to dissipate surplus wind power under grid fault conditions, will largely increase the cost of MMC-HVDC systems. To reduce the cost, a novel low voltage ride-through (LVRT) strategy is proposed in this paper. When a grid fault occurs and the DC voltage exceeds the limit, the sending end converter is controlled to reduce the AC voltage of the wind farm. The LVRT of the wind generators will be activated, and the output active power of the wind farm is reduced. With this coordination, the DC-side energy dissipation equipment only needs to dissipate surplus power in the early stage of the grid fault before the output active power of the wind farm drops. Therefore, the heat generated by braking resistors can be significantly reduced. On this basis, the braking resistors can be distributed into the submodules of the receiving end converter (REC) station. The LVRT problem can be solved without building an individual energy dissipation station. Using the proposed coordination strategy, the construction cost of the MMC-HVDC system with offshore wind farm integration can be significantly reduced.

Pseudo threshold pressure gradient (PTPG) is one of the main factors affecting the oil recovery of heterogeneous low-permeability and tight reservoirs. When the pressure gradient between the supply boundary and the bottom hole is less than PTPG, the crude oil in the formation cannot flow. In order to accurately measure the relationship between PTPG and permeability, a novel experimental device has been designed and a series of core flooding experiments using brine and oil have been carried out. The new experimental device eliminates the influence of rubber sleeve in core holder and core end-effect on the results, and greatly improves the accuracy of pressure measurement. The experimental results show the PTPG has a power function relationship with permeability, and has no obvious relationship with the viscosity of the fluid. Based on the equation for PTPG and permeability of crude oil and brine fitted by the experimental data, a new heterogeneous reservoir mathematical model considering PTPG were established. The influence of the coefficient of permeability variation, average permeability, and the production rate on oil recovery factor have been studied by this model. The results clearly show that the coefficient of permeability variation has the greatest influence on oil recovery factor, which represents inhomogeneity in low-permeability and tight reservoirs. Also, when the coefficient of permeability variation is less than a certain value (about 0.2 when average permeability is 1mD, in our model), there is only a slight decline in oil recovery factor, and when coefficient of permeability variation is larger than this value, the oil recovery factor decreases rapidly. The finding is consistent with oil field production and helpful to determine whether to take EOR(enhanced oil recovery) measures for a low-permeability heterogeneous reservoirs.

Abstract Numb, a stem cell fate determinant, acts as a tumor suppressor and is closely related to a wide variety of malignancies. Intrahepatic cholangiocarcinoma (iCCA) originates from hepatic progenitors (HPCs); however, the role of Numb in HPC malignant transformation and iCCA development is still unclear. A retrospective cohort study indicated that Numb was frequently decreased in tumor tissues and suggests poor prognosis in iCCA patients. Consistently, in a chemically induced iCCA mouse model, Numb was downregulated in tumor cells compared to normal cholangiocytes. In diet-induced chronic liver injury mouse models, Numb ablation significantly promoted histological impairment, HPC expansion, and tumorigenesis. Similarly, Numb silencing in cultured iCCA cells enhanced cell spheroid growth, invasion, metastasis, and the expression of stem cell markers. Mechanistically, Numb was found to bind to the Notch intracellular domain (NICD), and Numb ablation promoted Notch signaling; this effect was reversed when Notch signaling was blocked by γ-secretase inhibitor treatment. Our results suggested that loss of Numb plays an important role in promoting HPC expansion, HPC malignant transformation, and, ultimately, iCCA development in chronically injured livers. Therapies targeting suppressed Numb are promising for the treatment of iCCA.

For a long time, wind speed profile measurement has been the primary task of weather forecasting. Therefore, the detection of atmospheric wind speed is extremely important for studying the changes in atmospheric motion. In order to solve the problems of insufficient data collection, low resolution, and low accuracy in atmospheric wind field detection, this paper introduces the relevant theories of wind speed detection, completes the optical design of the system according to the research objectives, and determines the selection of optical devices. At the same time, a Doppler wind lidar system based on a quadrichannel Mach–Zehnder interferometer is designed and built to carry out ground-based observation experiments, collect echo signal data, and inverse the atmospheric radial wind speed. Furthermore, the wind measurement error is analyzed. Firstly, the paper introduces the basic principle of the wind measurement system, i.e., using the Doppler effect of light, and then analyzes the frequency discrimination device of the system in detail, and obtains the theoretical calculation method of atmospheric wind speed inversion. At the same time, the relevant datasets of wind measurement system are analyzed, including backscattering ratio, aerosol, and molecular extinction coefficient, and the emission mechanism of the large pulse laser is also studied in detail, which provides a theoretical basis for the model construction of Doppler lidar and the research on the enhancement of pulsed laser emission energy. Secondly, according to the research index of wind measurement, a Doppler wind measurement lidar system based on a quadrichannel Mach–Zehnder interferometer is designed, including the design of ab external light path transceiver system, internal light path interferometer, software and hardware, and algorithm. The calibration of the quadrichannel Mach–Zehnder interferometer is completed, with its maximum interference contrast reaching 0.869. Through the self-developed optical transceiver system and data acquisition system, the echo signal of lidar is received and detected. Lastly, the data of echo signals collected by the interferometer are analyzed, the radial atmospheric wind speed profile is inversed, and the signal-to-noise ratio and wind speed measurement error of the system are evaluated. The experimental results show that the maximum signal-to-noise ratio (SNR) of the system can reach 1433 when the emission pulse energy of the large pulse laser is adjusted to 255 mJ, and the farthest wind speed detection distance is about 8 km. The high-precision wind speed detection range can reach 2 km, the actual wind measurement errors in this range are all within 1.593 m/s, and the minimum error is only 0.418 m/s. In addition, the backscattering coefficient and extinction coefficient of atmospheric molecules and aerosols in the range of 8 km and the atmospheric temperature in the range of 10 km are also measured. The measurement accuracy of the aerosol extinction coefficient is ±0.001 m−1, and the measurement error of atmospheric temperature within 10 km is within 2 K, achieving the expected goals.

In recent years, offshore wind farms have boomed all over the world. It is essential to manage the energy dispatch of the offshore wind power systems to reduce transmission losses. This article proposes an optimization method for the optimal power flow of offshore wind power systems based on the convex–concave procedure. First, the nonlinear variables in the power flow constraints of the offshore wind power system are relaxed with newly defined variables. Second, the non-convex constraints are reconstructed according to the variables’ characteristics so that the optimization method satisfies all constraints at the same time. Meanwhile, by applying the Taylor series expansion, the relaxation variables’ gaps are changed dynamically, and the convex relaxation is tightened to ensure the effectiveness of the proposed method. Finally, the feasibility of the relaxation and the optimized solution is verified by the simulation to realize the power optimization in the real offshore wind system.

Non-alcoholic fatty liver disease (NAFLD), ranging from simple steatosis to non-alcoholic steatohepatitis (NASH), hepatic fibrosis and even hepatocellular carcinoma, is a liver disease worldwide without approved therapeutic drugs. Baicalein (BAL), a flavonoid compound extracted from the Traditional Chinese Medicine (TCM) Scutellariae Radix (Scutellaria baicalensis Georgi.), has been used in TCM clinical practice for thousands of years to treat liver diseases due to its “hepatoprotective effect”. However, the underlying liver-protecting mechanisms remain largely unknown. Here, we found that oral administration of BAL significantly decreased excess serum levels of triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), aspartate aminotransferase (AST) as well as hepatic TG in fructose-fed rats. Attenuation of the increased vacuolization and Oil Red O staining area was evident on hepatic histological examination in BAL-treated rats. Mechanistically, results of RNA-sequencing, western-blot, real-time quantitative PCR (RT-qPCR) and hepatic metabolomics analyses indicated that BAL decreased fructose-induced excessive nuclear expressions of mature sterol regulatory element-binding protein 1c (mSREBP1c) and carbohydrate response element-binding protein (ChREBP), which led to the decline of lipogenic molecules [including fatty acid synthase (FASN), stearoyl-CoA desaturase 1 (SCD1), elongation of very long chain fatty acids 6 (ELOVL6), acetyl-CoA carboxylase (ACC)], accompanying with the alternation of hepatic fatty acids composition. Meanwhile, BAL enhanced fatty acid oxidation by activating AMPK/PGC1α signaling axis and PPARα signal pathway, which elicited high expression of carnitine palmitoyl transferase 1α (CPT1α) and Acyl-CoA oxidase 1 (ACO1) in livers of fructose-fed rats, respectively. BAL ameliorated fructose-induced hepatic steatosis, which is associated with regulating fatty acid synthesis, elongation and oxidation.

Abstract The signals of Global Navigation Satellite System (GNSS) are so vulnerable that can be easily jammed by intentional or unintentional interferences. One of the effective ways to protect GNSS signals from jamming is to use the Space‐Time Array Processing (STAP) technology. However, undesired carrier phase bias would be induced to the signals because of the STAP, which significantly influences the precision of positioning. Many algorithms have been proposed to deal with this carrier phase bias, but most of them need the directional information of signals or the pre‐test of antennas. In this paper, a carrier phase correction algorithm without the need of prior information is proposed. Alarmed by the jerk of carrier frequency, the algorithm can detect the change of jamming and calculate the induced carrier phase bias. Then it can correct this bias from the signal and alleviate its influence. The simulation results show that the algorithm can limit the bias from more than 60° to less than 10°, which verifies that the proposed algorithm is effective in the low dynamic receiver.

Many studies have focused on the smartphone-based global navigation satellite system (GNSS) for its portability. However, complex urban environments, such as urban canyons and tunnels, can easily interfere with GNSS signal qualities. Current smartphone-based positioning technologies using the GNSS signal still pose great challenges. Since the last satellite of the BeiDou navigation system (BDS) was successfully launched on 23 June 2020, it is possible to use a low-cost Android device to realize the localization based on the BDS signals worldwide. This research focuses on smartphone-based outdoor pedestrian navigation utilizing the GPS/BDS multi-constellation system. To improve the localization accuracy, we proposed the Weighted Factor Graph Optimization localization model (W-FGO). In this paper, firstly, we evaluate the signal qualities of the BDS via the data collected by the static experiment. Then, we structure the cost function based on the pseudo-range and the time series data for the traditional Factor Graph Optimization (FGO). Finally, we design the weight model based on the signal quality of each satellite and the time fading factor to further improve the localization accuracy of the conventional FGO method. An Android smartphone is utilized to collect the GNSS data for the evaluation and the localization. The experiment results demonstrate the superior performance of the proposed method.

According to the demand for high-performance fibers for high-latitude ocean exploration and development, this paper selects representative products of high-performance liquid crystal fibers: thermotropic liquid crystal polymer fibers (TLCP) and poly p-phenylene terephthalamide (PPTA) fibers. Through a series of freeze–thaw (F–T) experiments for simulating a real, cold marine environment, we then measure the retention of mechanical properties of these two kinds of fibers. Before that, due to the difference in their chemical structures, we tested their Yang–Laplace contact angle (YLCA) and water absorption; the results suggested that PPTA fibers would absorb more moisture. Surprisingly, then, compared with thermotropic liquid crystal polymer (TLCP) fibers, the retention of the mechanical properties of poly p-phenylene terephthalamide (PPTA) fibers decreased by around 25% after the F–T experiments. The Fourier-transformed infrared (FT-IR) analysis, the attenuated total reflection (ATR) accessory analysis and the degree of crystal orientation measured by two-dimensional wide-angle X-ray diffraction (2D-WAXD) confirm that no changes in the chemical and the orientation structure of the crystal region of the fibers occurred after they underwent the F–T cycles. However, as observed by scanning electron microscopy (SEM), there are microcracks of various extents on the surface of the PPTA fibers, but they do not appear on the surface of TLCP fibers. It is obvious that these microcracks will lead to the loss of mechanical properties; we infer that the moisture absorbed by the PPTA fibers freezes below the freezing point, and the volume expansion of the ice causes the collapse of the microfibrillar structure. The two sorts of fibers subjected to the F–T experiments are immersed in a sodium chloride solution, and the amount of water infiltrated into the PPTA microfibrillar structure is evaluated according to the content of sodium ions in the fiber surface and subsurface layers through X-ray spectroscopy (EDS) elemental analysis. From the above analysis, we found that TLCP fibers can more effectively meet the operating standards of the severe and cold marine environment.

Recent studies have shown that introducing fluorinated groups into polyimide (PI) molecules can effectively reduce the dielectric constant (Dk) and dielectric loss (Df) of PIs. In this paper, 2,2′-bis[4-(4-aminophenoxy) phenyl]-1,1′,1′,1′,3,3′,3′-hexafluoropropane (HFBAPP), 2,2′-bis(trifluoromethyl)-4,4′-diaminobenzene (TFMB), diaminobenzene ether (ODA), 1,2,4,5-Benzenetetracarboxylic anhydride (PMDA), 3,3′,4,4′-diphenyltetracarboxylic anhydride (s-BPDA) and 3,3′,4,4′-diphenylketontetracarboxylic anhydride (BTDA) were selected for mixed polymerization to find the relationship between the structure of PIs and dielectric properties. Firstly, different structures of fluorinated PIs were determined, and were put into simulation calculation to learn how structure factors such as fluorine content, the position of fluorine atom and the molecular structure of diamine monomer affect the dielectric properties. Secondly, experiments were carried out to characterize the properties of PI films. The observed change trends of performance were found to be consistent with the simulation results, and the possible basis of the interpretation of other performance was made from the molecular structure. Finally, the formulas with the best comprehensive performance were obtained respectively. Among them, the best dielectric properties were 14.3%TFMB/85.7%ODA//PMDA with dielectric constant of 2.12 and dielectric loss of 0.00698.

Intelligent management of trees is essential for precise production management in orchards. Extracting components’ information from individual fruit trees is critical for analyzing and understanding their general growth. This study proposes a method to classify persimmon tree components based on hyperspectral LiDAR data. We extracted nine spectral feature parameters from the colorful point cloud data and performed preliminary classification using random forest, support vector machine, and backpropagation neural network methods. However, the misclassification of edge points with spectral information reduced the accuracy of the classification. To address this, we introduced a reprogramming strategy by fusing spatial constraints with spectral information, which increased the overall classification accuracy by 6.55%. We completed a 3D reconstruction of classification results in spatial coordinates. The proposed method is sensitive to edge points and shows excellent performance for classifying persimmon tree components.

Background & Aims: N6-methyladenosine (m6A), the most prevalent and dynamic posttranscriptional methylation modification of mammalian mRNA, is involved in various biological processes, but its role in liver regeneration has not been characterized. Methods: We first conducted transcriptome-wide m6A mRNA sequencing and characterized the expression pattern of m6A in regenerating mouse liver. Next, we generated hepatocyte-specific Mettl3- or Mettl14-deficient mice and investigated their role in liver regeneration. A series of biochemical experiments in vitro and in vivo was further performed to investigate potential mechanisms. Results: We identified an overwhelming proportion of m6A-modified genes with initially up-regulated and subsequently down-regulated m6A levels as liver regeneration progressed. Loss of Mettl14 but not of Mettl3 resulted in markedly disrupted liver regeneration, and Mettl14-ablated hepatocytes were arrested in the G1 phase of the cell cycle. Most strikingly, the Mettl14-ablated regenerating liver exhibited extensive parenchymal necrosis. mRNA transcripts, such as Hsp90b1, Erp29, Stt3a, P4hb, and Lman1, encoding proteins involved in polypeptide processing and the endoplasmic reticulum (ER) stress response, were m6A-hypomethylated, and their mRNA and protein levels were subsequently decreased, resulting in unresolved ER stress, hepatocyte death, and inhibited proliferation. Conclusions: We demonstrate the essential role of Mettl14 in facilitating liver regeneration by modulating polypeptide-processing proteins in the ER in an m6A-dependent manner.