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Abstract Acute kidney injury (AKI) is closely related to lysosomal dysfunction and ferroptosis in renal tubular epithelial cells (TECs), for which effective treatments are urgently needed. Although selenium nanoparticles (SeNPs) have emerged as promising candidates for AKI therapy, their underlying mechanisms have not been fully elucidated. Here, we investigated the effect of SeNPs on hypoxia/reoxygenation (H/R)-induced ferroptosis and lysosomal dysfunction in TECs in vitro and evaluated their efficacy in a murine model of ischemia/reperfusion (I/R)-AKI. We observed that H/R-induced ferroptosis was accompanied by lysosomal Fe2+ accumulation and dysfunction in TECs, which was ameliorated by SeNPs administration. Furthermore, SeNPs protected C57BL/6 mice against I/R-induced inflammation and ferroptosis. Mechanistically, we found that lysosomal Fe2+ accumulation and ferroptosis were associated with the excessive activation of NCOA4-mediated ferritinophagy, a process mitigated by SeNPs through the upregulation of X-box binding protein 1 (XBP1). Downregulation of XBP1 promoted ferritinophagy and partially counteracted the protective effects of SeNPs on ferroptosis inhibition in TECs. Overall, our findings revealed a novel role for SeNPs in modulating ferritinophagy, thereby improving lysosomal function and attenuating ferroptosis of TECs in I/R-AKI. These results provide evidence for the potential application of SeNPs as therapeutic agents for the prevention and treatment of AKI.

The continuous drive for miniaturization and enhanced functionality in micro-electronic devices demands highly integrated circuit (IC) packaging. This trend leads to a dense network of micro-electronic packaging interconnections, facilitated by the reduction in traditional solder interconnection sizes. However, these advancements bring about significant challenges, including thermal expansion differences between materials used in the package and the presence of non-planar substrates. Such issues can lead to thermomechanical stresses in interconnections and warpage, resulting in serious reliability issues. In response, nanostructured compliant interconnections have emerged as a promising solution. These interconnections effectively manage thermal expansion variations and substrate non-coplanarity, mitigating the risks associated with miniaturization and high integration demands in IC packaging. This review explores the latest trends and advancements in developing nanostructured compliant interconnections for modern micro-electronics. The focus is on integrating various interconnection materials, including nanoparticles (via sintering), nanoporous materials, nanowires (NWs) and carbon nanotubes (CNTs). This integration aims to improve the performance and mechanical reliability of interconnections under extreme thermal loading conditions. Advanced bonding techniques and their significant impacts on interconnection reliability are also discussed. Additionally, the study provides insights into future developments of nanostructured compliant interconnections, guiding researchers toward specific technical areas for future exploration.

ObjectiveThis study aims to develop and validate machine learning models to predict proliferative lupus nephritis (PLN) occurrence, offering a reliable diagnostic alternative when renal biopsy is not feasible or safe.MethodsThis study retrospectively analyzed clinical and laboratory data from patients diagnosed with SLE and renal involvement who underwent renal biopsy at West China Hospital of Sichuan University between 2011 and 2021. We randomly assigned 70% of the patients to a training cohort and the remaining 30% to a test cohort. Various machine learning models were constructed on the training cohort, including generalized linear models (e.g., logistic regression, least absolute shrinkage and selection operator, ridge regression, and elastic net), support vector machines (linear and radial basis kernel functions), and decision tree models (e.g., classical decision tree, conditional inference tree, and random forest). Diagnostic performance was evaluated using ROC curves, calibration curves, and DCA for both cohorts. Furthermore, different machine learning models were compared to identify key and shared features, aiming to screen for potential PLN diagnostic markers.ResultsInvolving 1312 LN patients, with 780 PLN/NPLN cases analyzed. They were randomly divided into a training group (547 cases) and a testing group (233 cases). we developed nine machine learning models in the training group. Seven models demonstrated excellent discriminatory abilities in the testing cohort, random forest model showed the highest discriminatory ability (AUC: 0.880, 95% confidence interval(CI): 0.835–0.926). Logistic regression had the best calibration, while random forest exhibited the greatest clinical net benefit. By comparing features across various models, we confirmed the efficacy of traditional indicators like anti-dsDNA antibodies, complement levels, serum creatinine, and urinary red and white blood cells in predicting and distinguishing PLN. Additionally, we uncovered the potential value of previously controversial or underutilized indicators such as serum chloride, neutrophil percentage, serum cystatin C, hematocrit, urinary pH, blood routine red blood cells, and immunoglobulin M in predicting PLN.ConclusionThis study provides a comprehensive perspective on incorporating a broader range of biomarkers for diagnosing and predicting PLN. Additionally, it offers an ideal non-invasive diagnostic tool for SLE patients unable to undergo renal biopsy.

The aim of this study is to accurately extract the dielectric parameters of building materials through nondestructive measurement methods. The ultrawideband (UWB) measurement system is used to capture echoes from marble targets in the frequency range of 2.5–15 GHz, and the reflection coefficient is derived using a time window separation technique. By combining the particle swarm optimization (PSO) algorithm, the dielectric parameters of the marble targets are successfully inverted. Research results show that the relative dielectric constant extracted under three different incident angle conditions ranges from 5.370 to 5.545, and the conductivity ranges from 0.00429 to 0.00515 S/m. The root mean square error (RMSE) between the theoretically calculated reflection coefficient and the measured reflection coefficient ranges from 0.013 to 0.025, while the RMSE ranges from 0.047 to 0.066 if the dielectric parameters recommended by ITU-R P.2040-3 are used, thus confirming the accuracy and reliability of the proposed method for dielectric parameters extraction.

The maritime environment is complex and changeable, and an accurate maritime wireless channel model is particularly difficult to establish. This study investigates the sensitivity of a three-dimensional (3D) maritime ray tracing (RT) model for the use of the geometrical optics in radio channel characterizations of maritime environments. The channel measurement experiments are mainly carried out at three frequency points of 1.5, 1.8, and 2.5 GHz, and the simulation results of the model are compared and corrected with the measured received power. Analysis shows that the modified model simulation results at 1.5, 1.8, and 2.5 GHz frequency points are in good agreement with the actual measurement, and the RMS is within 7 dB. Moreover, the reverse RT algorithm has the advantages of fast calculation speed and high efficiency. The effects of the different sea conditions, frequencies, and distances on the propagation of electromagnetic waves are analyzed on the basis of this model.

The emergence of ligand-protected, atomically precise gold nanoclusters (NCs) in recent years has attracted broad interest in catalysis due to their well-defined atomic structures and intriguing properties. Especially, the precise formulas of NCs provide an opportunity to study the size effects at the atomic level without complications by the polydispersity in conventional nanoparticles that obscures the relationship between the size/structure and properties. Herein, we summarize the catalytic size effects of atomically precise, thioate-protected gold NCs in the range of tens to hundreds of metal atoms. The catalytic reactions include electrochemical catalysis, photocatalysis, and thermocatalysis. With the precise sizes and structures, the fundamentals underlying the size effects are analyzed, such as the surface area, electronic properties, and active sites. In the catalytic reactions, one or more factors may exert catalytic effects simultaneously, hence leading to different catalytic-activity trends with the size change of NCs. The summary of literature work disentangles the underlying fundamental mechanisms and provides insights into the size effects. Future studies will lead to further understanding of the size effects and shed light on the catalytic active sites and ultimately promote catalyst design at the atomic level.

Atomically precise gold nanoclusters display useful photoluminescence properties, but limitations in synthetic methods and characterization techniques have hindered their detailed exploration. Here, a Au38(PET)26 nanocluster is found to exhibit fluorescence, phosphorescence, and thermally activated delayed fluorescence emissions, with a significant enhancement in photoluminescence intensity at cryogenic temperatures owing to the suppression of nonradiative pathways.

Introduction: The consolidation behavior of horizontal drainage foundation under complex aquifer conditions in karst areas is a hot topic in the field of geotechnical engineering.Methods: This paper presents a modified piecewise-linear model for plane-strain consolidation. In this model, the distributed drainage boundary was used to describe the drainage performance of soil layer boundaries, and the UH model considering the time effect was selected to reflect soil’s rheological property. Through comparison with existing research, the validity of the calculation model in this paper was verified. Then several examples were used to analyze the consolidation behavior of the foundation under the combined action of rheological effect and distributed drainage boundaries.Results and discussion: Numerical studies show that the phenomenon of the increase of excess pore pressure exists in the foundation of the distributed drainage boundary after considering the rheology in the early stage of consolidation. Moreover, the larger the secondary consolidation coefficient and the initial over-consolidation parameter, or the smaller the pave rate and the thickness-width ratio, the above phenomenon is more obvious. In terms of the dissipation of the pore water pressure, the larger the secondary consolidation coefficient and the initial over-consolidation parameter, the slower the pore pressure dissipation, and the smaller the pave rate or the thickness-width ratio can achieve the above effects. In terms of the impact on settlement, the above-mentioned parameters are consistent, that is, the larger the corresponding parameter, the larger the corresponding settlement value.

Ischemic stroke is closely associated with gut microbiota dysbiosis and intestinal barrier dysfunction. Prebiotic intervention could modulate the intestinal microbiota, thus considered a practical strategy for neurological disorders. Puerariae Lobatae Radix-resistant starch (PLR-RS) is a potential novel prebiotic; however, its role in ischemic stroke remains unknown. This study aimed to clarify the effects and underlying mechanisms of PLR-RS in ischemic stroke. Middle cerebral artery occlusion surgery was performed to establish a model of ischemic stroke in rats. After gavage for 14 days, PLR-RS attenuated ischemic stroke-induced brain impairment and gut barrier dysfunction. Moreover, PLR-RS rescued gut microbiota dysbiosis and enriched Akkermansia and Bifidobacterium. We transplanted the fecal microbiota from PLR-RS-treated rats into rats with ischemic stroke and found that the brain and colon damage were also ameliorated. Notably, we found that PLR-RS promoted the gut microbiota to produce a higher level of melatonin. Intriguingly, exogenous gavage of melatonin attenuated ischemic stroke injury. In particular, melatonin attenuated brain impairment via a positive co-occurrence pattern in the intestinal microecology. Specific beneficial bacteria served as leaders or keystone species to promoted gut homeostasis, such as Enterobacter, Bacteroidales_S24–7_group, Prevotella_9, Ruminococcaceae and Lachnospiraceae. Thus, this new underlying mechanism could explain that the therapeutic efficacy of PLR-RS on ischemic stroke at least partly attributed to gut microbiota-derived melatonin. In summary, improving intestinal microecology by prebiotic intervention and melatonin supplementation in the gut were found to be effective therapies for ischemic stroke.

Objective A post hoc subgroup analysis of prospectively collected data from a randomized controlled trial was conducted to identify risk factors related to poor outcomes in patients who underwent minimally invasive discectomy. Methods Patients were divided into satisfied and dissatisfied subgroups based on Oswestry Disability Index (ODI), visual analogue scale (VAS) back pain score (VAS-back) and leg pain score (VAS-leg) at short-term and midterm follow-up according to the patient acceptable symptom state threshold. Demographic characteristics, radiographic parameters, and clinical outcomes between the satisfied and dissatisfied subgroups were compared using univariate and multivariate analysis. Results A total of 222 patients (92.1%) completed 2-year follow-up, and the postoperative ODI, VAS-back, and VAS-leg were significantly improved after surgery as compared to preoperatively. Multivariate analysis indicated older age (p=0.026), lateral recess stenosis (p=0.046), and lower baseline ODI (p=0.027) were related to poor short-term functional improvement. Higher baseline VAS-back (p=0.048) was associated with poor short-term relief of back pain, while absence of decreased sensation (p=0.019) and far-lateral disc herniation (p=0.004) were associated with poorer short-term relief of leg pain. Lumbar facet joint osteoarthritis was identified as a risk factor for poor functional improvement (p=0.003) and relief of back pain (p=0.031). Disc protrusion (p=0.036) predicted poorer relief of back pain at midterm follow-up. Conclusion In this study, several factors were identified to be predictive of poor surgical outcomes following minimally invasive discectomy. (ClinicalTrials.gov number: NCT01997086).

Taking location-based service (LBS) as the research scenario and aiming at the limitation of visualizing LBS points of interest (POI) in conventional web maps, this article proposes a visualization method of LBS-POI based on tag cloud, which is called “LBS tag cloud”. In this method, the user location is taken as the layout center, and the name of the POI is converted into a text tag and then placed around the center. The tags’ size, color, and placement location are calculated based on other attributes of the POI. The calculation of placement location is at the core of the LBS tag cloud. Firstly, the tag’s initial placement position and layout priority are calculated based on polar coordinates, and the tags are placed in the initial placement position in the order of layout priority. Then, based on the force-directed model, a repulsive force is applied to the tag from the layout center to make it move to a position without overlapping with other tags. During the move, the quadtree partition of the text glyph is used to optimize the detection of overlaps between tags. Taking scenic spots as an example, the experimental results show that the LBS tag cloud can present the attributes and distribution of POIs completely and intuitively and can effectively represent the relationship between the POIs and user location, which is a new visualization form suitable for spatial cognition.

A major unmet need in the cystic fibrosis (CF) therapeutic landscape is the lack of effective treatments for nonsense CFTR mutations, which affect approximately 10% of CF patients. Correction of nonsense CFTR mutations via genomic editing represents a promising therapeutic approach. In this study, we tested whether prime editing, a novel CRISPR-based genomic editing method, can be a potential therapeutic modality to correct nonsense CFTR mutations. We generated iPSCs from a CF patient homozygous for the CFTR W1282X mutation. We demonstrated that prime editing corrected one mutant allele in iPSCs, which effectively restored CFTR function in iPSC-derived airway epithelial cells and organoids. We further demonstrated that prime editing may directly repair mutations in iPSC-derived airway epithelial cells when the prime editing machinery is efficiently delivered by helper-dependent adenovirus (HDAd). Together, our data demonstrated that prime editing may potentially be applied to correct CFTR mutations such as W1282X.

While Silicon is widely used for electronic devices, its band-gap limits its use for infrared detection. Here, Zheng et al present a method for overcoming this limitation, by integrating colloidal quantum dots, with the resulting structure exhibiting high sensitivity to infrared radiation.

Abstract Background Hypertrophy is a critical process for chondrocyte differentiation and maturation during endochondral ossification, which is responsible for the formation of long bone and postnatal longitudinal growth. Increasing evidence suggests that melatonin, an indole hormone, plays a pivotal role in chondrogenesis. However, little is known about the effects of melatonin on the terminal differentiation of chondrocytes. Methods Mesenchymal stem cell (MSC)-derived chondrocytes generated by a high-density micromass culture system were induced to undergo hypertrophic differentiation. Melatonin-mediated hypertrophic differentiation was examined by reverse transcription polymerase chain reaction analysis (RT-PCR) analysis, histological staining and immunohistochemistry. Activation of the Wnt signaling pathway was evaluated by PCR array, RT-PCR, western blotting and immunofluorescence. XAV-939, a Wnt signaling pathway antagonist, was further used to determine whether the effect of melatonin on chondrocyte hypertrophic differentiation was mediated occurred by activation of Wnt signaling pathway. Results Histological staining showed melatonin increased chondrocyte cell volume and the expression of type X collagen but decreased the expression of type II collagen compared with the control group. RT-PCR showed that melatonin significantly up-regulated the gene expressions of biomarkers of hypertrophic chondrocytes, including type X collagen, alkaline phosphatase, runt-related transcription factor 2, Indian hedgehog and parathyroid hormone-related protein receptor, and melatonin down-regulated the mRNA expression of hallmarks of chondrocytes, including parathyroid hormone-related protein. PCR array showed that the effect of melatonin on chondrocyte hypertrophic differentiation was accompanied by the up-regulation of multiple target genes of the canonical Wnt signaling pathway, and this effect was blocked by XAV-939. Conclusions The current findings demonstrate that melatonin enhances the hypertrophic differentiation of MSC-derived chondrocytes through the Wnt signaling pathway. Our findings add evidence to the role of melatonin in promoting bone development and highlight the positive effects of melatonin on terminal differentiation of chondrocytes.

Internal curing technology involves the integration of internal curing materials into concrete, typically under pre-water storage conditions. This method works by gradually releasing water to increase the internal humidity of the concrete, which enhances the hydration of cementitious materials, reduces self-shrinkage in high-strength concrete (HSC), and improves its overall performance. Commonly used internal curing materials include absorbent resin and lightweight aggregates. However, using these materials in excessive amounts can compromise the strength or durability of the concrete, making it essential to determine the optimal dosage for effective application. When applied to HSC, internal curing helps mitigate shrinkage and enhances frost resistance. As noted, accurately determining the appropriate dosage of internal curing materials is critical to maximizing these benefits. The performance evaluation of internally cured HSC is a multiple-attribute decision-making (MADM) problem, and to address the uncertainties involved in this process, triangular fuzzy neutrosophic sets (TFNSs) are particularly suitable. TFNSs offer a more precise way to represent uncertain information. Grey relational analysis (GRA), a widely used technique in grey system theory, assesses the similarity between sequence curves based on their geometric shapes. In this paper, we introduce a triangular fuzzy neutrosophic number GRA (TFNN-GRA) technique under TFNSs, where no prior weight information is available. Weight values under TFNSs are determined using information entropy. By combining GRA with TFNSs, we propose the TFNN-GRA method and outline the steps for solving MADM problems. Finally, a numerical example is presented to demonstrate the performance evaluation of internally cured HSC, along with comparative studies that highlight the advantages of the TFNN-GRA technique. [ABSTRACT FROM AUTHOR]

Insufficient handling of spontaneous combustion in coal piles arises from the influence of natural wind during the piling process, resulting in the displacement of the heat source. To investigate the impact of wind flow on heat source movement in simulated coal piles under varying wind velocities, an experimental stage was established. The research findings elucidate that both normal and tangential winds exert an influence on the heat source position, with normal winds exhibiting a greater effect than tangential winds. The relationship between heat source position speed and wind speed magnitude follows a common fitting function under both wind conditions. Specifically, the speed of the heat source at the edge position demonstrates a linear correlation with the magnitude of wind speed, while the speed of the heat source at the center position conforms to a quadratic function with the wind speed magnitude. The heat source moves at a distance of 0.8 cm to 5.3 cm on the Y = 0 tangent, corresponding to a moving speed of 0.03 cm/min to 0.18 cm/min. On theY = −20 tangent, the heat source moves at a distance of 2.1 cm to 8.1 cm, corresponding to a moving speed of 0.07 cm/min to 0.27 cm/min. Moreover, the study reveals that the influence on heat source movement at the center of the simulated coal pile diminishes as wind speed decreases under both wind conditions. These research findings provide a theoretical foundation for managing spontaneous combustion in coal piles and offer insights into precise management of heat source positions within coal piles. [ABSTRACT FROM AUTHOR]

The occurrence of coal spontaneous combustion has a significant impact on both the safety of personnel and mine recovery. In order to establish an early warning system for combustion, it is crucial to develop a mathematical model that characterizes indicator gases and coal temperature. In this study, we investigated the O2, CO, and CO2 characteristics of data collected from a goaf beam pipe in the Mengcun mine. Our findings demonstrate a linear decrease in O2 concentration with goaf depth and a strong negative correlation between CO and O2. We observed that CO/∆O2 and CO/CO2 increased to a maximum and then decreased as the goaf depth increased. Furthermore, we found that the peaks of these parameters at the same sampling point corresponded to the same goaf depth, and both occurred at the junction between the air-leakage and oxidation zones. By using a logistic model to fit the CO and C2H4 data, we developed a model that characterizes the relationships among CO, C2H4, and coal temperature based on statistical laws. The model provides direct information about the inflection point temperatures of C2H4 and CO, with the former being slightly lower within the same coal sample. The overall difference between the inflection point temperatures is relatively small, about 10°C. The initial temperature ratio of C2H4 and CO remains essentially constant at 3.8. C2H2 concentrations are low and irregular, and the presence of this gas can be used to assess when coal enters the accelerated oxidation stage. This research result provides a new research view for elucidating the distribution characteristics of coal spontaneous combustion index gas. [ABSTRACT FROM AUTHOR]

Investigating the neurocircuit and synaptic sites of action of oxytocin (OT) in the brain is critical to the role of OT in social memory and behavior. To the same degree, it is important to understand how OT is transported to the brain from the peripheral circulation. To date, of these, many studies provide evidence that CD38, CD157, and receptor for advanced glycation end-products (RAGE) act as regulators of OT concentrations in the brain and blood. It has been shown that RAGE facilitates the uptake of OT in mother’s milk from the digestive tract to the cell surface of intestinal epithelial cells to the body fluid and subsequently into circulation in male mice. RAGE has been shown to recruit circulatory OT into the brain from blood at the endothelial cell surface of neurovascular units. Therefore, it can be said that extracellular OT concentrations in the brain (hypothalamus) could be determined by the transport of OT by RAGE from the circulation and release of OT from oxytocinergic neurons by CD38 and CD157 in mice. In addition, it has recently been found that gavage application of a precursor of nicotinamide adenine dinucleotide, nicotinamide riboside, for 12 days can increase brain OT in mice. Here, we review the evaluation of the new concept that RAGE is involved in the regulation of OT dynamics at the interface between the brain, blood, and intestine in the living body, mainly by summarizing our recent results due to the limited number of publications on related topics. And we also review other possible routes of OT recruitment to the brain.

Elucidation of the molecular mechanisms involving the initiation and progression of radiation-induced esophageal injury (RIEI) is important for prevention and treatment. Despite ongoing advances, the underlying mechanisms controlling RIEI remain largely unknown. In the present study, RNA-seq was performed to characterize mRNA profiles of the irradiated rat esophagus exposed to 0, 25, or 35 Gy irradiation. Bioinformatics analyses including dose-dependent differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Gene and Genome (KEGG) pathway, protein-protein interaction (PPI) network, and immune infiltration were performed. 134 DEGs were screened out with a dose-dependent manner (35 Gy > 25 Gy > control, or 35 Gy < 25 Gy < control). GO and KEGG analyses showed that the most significant mechanism was IL-17 signaling-mediated inflammatory response. 5 hub genes, Ccl11, Cxcl3, Il17a, S100a8, and S100a9, were identified through the intersection of the DEGs involved in inflammatory response, IL-17 pathway, and PPI network. Additionally, immune infiltration analysis showed the activation of macrophages, monocytes, T cells, NKT cells, and neutrophils, among which macrophages, monocytes, and neutrophils might be the main sources of S100a8 and S100a9. Thus, these findings further our understanding on the molecular biology of RIEI and may help develop more effective therapeutic strategies.

Abstract Background Heterotopic pregnancy occurred after frozen embryo transfer with two D3 embryos, and the case had a history of bilateral salpingectomy due to salpingocyesis. An ectopic heterotopic pregnancy was implanted in the left psoas major muscle, which has not been previously reported. Case presentation A 33-year-old woman presented with left back pain after curettage due to foetal arrest in the uterus without vaginal bleeding and spotting, and painkillers relieved the pain initially. When the painkillers ceased to work, the patient returned to the hospital. The β-human chorionic gonadotropin (β-hCG) level remained increased compared with the time of curettage, and a diagnosis of retroperitoneal abdominal pregnancy was suggested by ultrasonography and computerized tomography (CT) with the gestational sac implanted in the left psoas major muscle at the left hilum level. Laparotomy was performed to remove the ectopic pregnancy. During the operation, we carefully separated the adipose tissue between the space of the left kidney door and left psoas major muscle, peeled away the gestational sac that was approximately 50 mm × 40 mm with a 25-mm-long foetal bud, and gave a local injection of 10 mg of methotrexate in the psoas major muscle. Fifty days later, β-hCG decreased to normal levels. Conclusion It is necessary to pay more attention to the main complaints to exclude rare types of ectopic pregnancies of the pelvis and abdomen after embryo transfer.

In order to solve the problem of complex information representation in automatic video description tasks,a multi-dimensional and multi-modal visual feature extraction and fusion method was proposed.Firstly,multi-dimensional features such as static and dynamic attributes of the video sequence were extracted by transfer learning,and the image description algorithm was also used to extract the semantic information of the key frames in the video.By doing this,the video features extraction was carried out.Then,multi-layer long and short memory networks were used to fuse multi-dimensional and multi-modal information,and finally generated a language description of the video content.Compared with the existing methods,experimental simulations results show that the proposed method achieves better results in the video automatic description task.

Video description technique has been widely used in the computer community for many applications. The typical approaches are mainly based on the encode-decode framework: the fixed-length video representation vectors are extracted by the encoder using the upper layer output of pre-trained convolutional neural networks (CNNs); The decoder uses the recurrent neural networks to generate a textual sentence. However, the upper layers of convolutional neural networks contain low-resolution, semantically strong, while the lower layers contain high-resolution, semantically weak features. In the existing method, the multi-scale information of CNNs is hardly considered to be used in the video description. Ignoring this information will lead to the problem that the video description is not detailed and comprehensive. This paper applies the hierarchical convolutional long short-term memory (ConvLSTM) in the encode-decode framework to conduct feature extraction of the upper and lower layers in CNNs. Moreover, multiple network structures are designed to explore the Spatio-temporal feature extraction performance of ConvLSTM, which can approach the optimal accuracy in the three-layer ConvLSTM. In order to efficiently improve the language quality of video description, the attention mechanism focuses on visual feature output by ConvLSTM. The extensive experimental results demonstrate that the proposed method outperforms the existing approaches.

Autism spectrum disorder (ASD) is a congenital, lifelong neurodevelopmental disorder whose main symptom is impaired social communication and interaction. However, no drug can treat social deficits in patients with ASD, and treatments to alleviate social behavioral deficits are sorely needed. Here, we examined the effect of oral supplementation of maca (Lepidium meyenii) on social deficits of in utero-exposed valproic acid (VPA) mice, widely used as an ASD model. Although maca is widely consumed as a fertility enhancer and aphrodisiac, it possesses multiple beneficial activities. Additionally, it benefits learning and memory in experimental animal models. Therefore, the effect of maca supplementation on the social behavioral deficit of VPA mice was assessed using a social interaction test, a three-stage open field test, and a five-trial social memory test. The oral supplementation of maca attenuated social interaction behavior deficit and social memory impairment. The number of c-Fos-positive cells and the percentage of c-Fos-positive oxytocin neurons increased in supraoptic and paraventricular neurons of maca-treated VPA mice. These results reveal for the first time that maca is beneficial to social memory and that it restores social recognition impairments by augmenting the oxytocinergic neuronal pathways, which play an essential role in diverse social behaviors.

The worker’s unsafe behavior is the key cause of mine accidents.The human activity is closely related with the context.Ontology is widely used in computer science in the field of information exchange and knowledge sharing,which contains complex structures and various semantics.Firstly,the research on the description of the miners’ situational information in the mining field was summarized.It introduced the general situation in the field of the Internet of things.The importance and necessity of the description of the state information of mine personnel was presented.It introduced the research background,including semantic web,context description and knowledge representation.After that,the method of information description of mine personnel was described.The ontology model was proposed based on oneM2M international technical specifications.In order to construct this ontology,it was drawed on some of the core concepts of oneM2M Base Ontology.The concept classes,attributes and relationships that are specific to the information description of mine personnel were put forward.The context description of mine personnel proposed was aimed at achieving the purposes of specification information description,data semantic labeling,knowledge sharing and reuse.Finally,the conclusions were drawn and the prospect of using the ontology method for context perception and the miners’ unsafe behavior recognition was presented.

A well-designed loss function can effectively improve the characterization ability of network features without increasing the amount of calculation in the model inference stage, and has become the focus of attention in recent research. Given that the existing lightweight network adds a loss to the last layer, which severely attenuates the gradient during the backpropagation process, we propose a hierarchical polynomial kernel prototype loss function in this study. In this function, the addition of a polynomial kernel loss function to multiple stages of the deep neural network effectively enhances the efficiency of gradient return, and only adds multi-layer prototype loss functions in the training stage without increasing the calculation of the inference stage. In addition, the good non-linear expression ability of the polynomial kernel improves the characteristic expression performance of the network. Verification on multiple public datasets shows that the lightweight network trained with the proposed hierarchical polynomial kernel loss function has a higher accuracy than other loss functions.

Atomically precise control over anisotropic nanoclusters constitutes a grand challenge in nanoscience. In this work, we report our success in achieving a periodic series of atomically precise gold quantum rods (abbrev. Au QRs) with unusual excitonic properties. These QRs possess hexagonal close-packed kernels with a constant three-atom diameter but increasing aspect ratios (ARs) from 6.3 to 18.7, all being protected by the same thiolate (SR) ligand. The kernels of the QRs are in a Au1-(Au3)n-Au1 configuration (where n is the number of Au3 layers) and follow a periodic elongation with a uniform Au18(SR)12 increment consisting of four Au3 layers. These Au QRs possess distinct HOMO-LUMO gaps (Eg = 0.6 to 1.3 eV) and exhibit strongly polarized excitonic transition along the longitudinal direction, resulting in very intense absorption in the near-infrared (800 to 1,700 nm). While excitons in gapped systems and plasmons in gapless systems are distinctly different types of excitations, the strongly polarized excitons in Au QRs surprisingly exhibit plasmon-like behaviors manifested in the shape-induced polarization, very intense absorption (~106 M-1 cm-1), and linear scaling relations with the AR, all of which resemble the behaviors of conventional metallic-state Au nanorods (i.e., gapless systems), but the QRs possess distinct gaps and very long excited-state lifetimes (10 to 2,122 ns), which hold promise in applications such as near-infrared solar energy utilization, hot carrier generation and transfer. The observation of plasmon-like behaviors from single-electron transitions in Au QRs elegantly bridges the distinct realms of single-electron and collective-electron excitations and may stimulate more research on excitonics and plasmonics. [ABSTRACT FROM AUTHOR]

Abstract Background Circulatory osteocalcin (OC) has been widely used as a biomarker to indicate bone turnover status in postmenopausal osteoporosis (PMO). However, the change of serum OC (sOC) level in PMO cases compared to postmenopausal controls remains controversial. Methods We searched the online database of PubMed and Cochrane Library. A meta-analysis of case-control studies was performed to compare the pooled sOC level between PMO patients and postmenopausal controls. Subgroup analysis according to potential confounding factors (different OC molecules and regions of the study population) was also performed. Results Ten case-control studies with 1577 postmenopausal women were included in this meta analysis. We found no significant difference in the pooled sOC level [mean difference (MD) = 1.84, 95% confidence interval (CI): (− 1.49, 5.16), p = 0.28] between PMO patients and controls. Subgroup analysis also revealed no significant difference in intact OC [MD = 1.76, 95%CI: (− 1.71, 5.23), p = 0.32] or N-terminal mid-fragment of the OC molecule [MD = 0.67, 95%(− 5.83, 7.18), p = 0.84] between groups. For different regions, no significant difference in sOC was found in Asian population between cases and controls [MD = -0.06, 95%(− 6.02, 5.89), p = 0.98], while the pooled sOC level was significantly higher in European PMO cases than controls [MD = 3.15, 95%(0.90, 5.39), p = 0.006]. Conclusions Our analysis revealed no significant difference in sOC level between PMO cases and controls according to all the current eligible studies. OC molecules are quite heterogeneous in the circulation and can be influenced by glucose metabolism. Therefore, sOC is currently not a good indicator for the high bone turnover status in PMO. More trials with standardized methodologies for the evaluation of circulatory OC are awaited to update our current findings.

The mine is a complicated environment.The intelligent recognition of such behavior requires not only the data-driven activity recognition method,but also the machine-readable domain knowledge based approach.However,the data of IoT for mines lacks the semantic information.Besides,there is no standard way of describing the worker’s context and representing the knowledge of worker’s unsafe behavior.In order to solve the above problems,a semantic ontology based approach to describing the worker’s context and a hybrid method based framework for worker’s unsafe behavior recognition were presented.This method combines the data-driven approach and the knowledge-driven approach.Firstly,an introduction to the semantic ontology in the Internet of things was given.Then,the importance and necessity of worker’s unsafe behavior recognition was introduced.After that,the research background on human activity recognition,context-awareness and semantic ontology was presented.This was followed by the semantic ontology based approach to the worker’s context description.Based on the context modeling,the framework that combined the data-driven method and the knowledge-driven method for the worker’s unsafe behavior recognition was proposed.The application of the framework was illustrated with the recognition of a kind of worker’s unsafe behavior who don’t wear the protective and safety equipment.Finally,the conclusions were drawn and the prospect of using the artificial intelligence method in the application layer of mine IoT was presented.

Meta-learning aims to teach the machine how to learn. Embedding model-based meta-learning performs well in solving the few-shot problem. The methods use an embedding model, usually a convolutional neural network, to extract features from samples and use a classifier to measure the features extracted from a particular stage of the embedding model. However, the feature of the embedding model at the low stage contains richer visual information, while the feature at the high stage contains richer semantic information. Existing methods fail to consider the impact of the information carried by the features at different stages on the performance of the classifier. Therefore, we propose a meta-learning method based on adaptive feature fusion and weight optimization. The main innovations of the method are as follows: firstly, a feature fusion strategy is used to fuse the feature of each stage of the embedding model based on certain weights, effectively utilizing the information carried by different stage features. Secondly, the particle swarm optimization algorithm was used to optimize the weight of feature fusion, and determine each stage feature’s weight in the process of feature fusion. Compared to current mainstream baseline methods on multiple few-shot image recognition benchmarks, the method performs better.

ObjectiveThis study examined the feasibility and safety of allogeneic uterus transplantation (UTx) from a living donor and assessed short-term graft viability in a rhesus model. This research is an important step towards further clinical application of UTx in humans.Materials and methodsFour female rhesus monkeys with regular menstrual cycles were used in this study, the animals were either donors or recipients depending on ABO blood type compatibility. Retrieval surgery was performed to connect the uterus and uterine arteries together with the ovarian uterine vein from the living donor, and the vagina of the recipient was excised. After the back table had been prepared, bilateral uterine arteries were anastomosed end-to-side with the iliac externa arteries, and bilateral ovarian uterine veins were anastomosed end-to-side with the iliac externa vena. The transplanted uterus was evaluated based on the conditions of arterial blood, and flow was evaluated by transabdominal ultrasonography one month post operation. The conditions of the transplanted uterus were examined by secondary laparotomy. The reproductive function of rhesus monkeys was evaluated on the basis of the menstrual cycle.ResultsAll 4 rhesus monkeys received the transplantation surgery without any surgical complications. No injury occurred in the other organs, and no vascular injury was observed in the allogeneic uterus. All recipients survived after the surgery with a 100% short-term survival rate. All recipients resumed normal menstruation within two months after surgery.ConclusionsOur short follow-up shows that allogeneic UTx surgery is a safe and feasible technology in the rhesus model. The arterial conditions and blood flow of the grafted uterus can be monitored by ultrasonography examination.

A tightly coupled fluid-structure interaction (FSI) methodology is developed for aeroelasticity analysis in the time domain. The preconditioned Navier–Stokes equations for all Mach numbers are employed and the structural equations are tightly coupled with the fluid equations by discretizing their time derivative term in the same pseudo time-stepping method. A modified mesh deformation method based on reduced control points radial basis functions (RBF) is utilized, and a RBF based mapping algorithm is introduced for data exchange on the interaction interface. To evaluate the methodology, the flutter boundary and the limit cycle oscillation of Isogai wing and the flutter boundary of AGARD 445.6 wing are analyzed and validated.