With the development of industrialization, traditional manufacturing technologies are no longer able to meet the production needs of modern society. Additive manufacturing has successfully solved the problems existing in traditional manufacturing technology. Selective laser melting (SLM) is a powder bed melting technology that produces metal parts by selectively melting metal powders on a platform using a laser beam. It is widely used in additive manufacturing. This article introduces the characteristics and current development status of SLM technology, summarizes the main application fields and common defects of SLM, and finally explores and prospects the future development trend of SLM.

Background and Objectives: Acute lung injury (ALI) is an inflammatory response in the lung caused by bacteria, viruses, trauma and other factors that results in lack of alveolar surfactant and subsequently respiratory distress. Endothelial-to-mesenchymal transition (EndoMT) is closely related to ALI-induced pulmonary fibrosis development and progression. This study examined the effect of milk fat globulin factor 8 (MFGE8) knockdown and overexpression on lipopolysaccharide (LPS)-induced EndoMT. Methods: Total MFGE8 activity in patients with acute respiratory distress syndrome (ARDS) and healthy volunteers was assessed using a colorimetric kit. In vitro, cell morphology was observed by microscopy, and invasion and migration were tested by Transwell and scratch assays. Specific siRNAs were transfected into HLMECs to downregulate MFGE8, and CD31 and α-SMA protein expression was detected by fluorescence microscopy and FCM. MFGE8, BMP, Smad 1, Smad4, Smad5, Snail, CD31 and α-SMA protein and gene expression was assessed by western blotting (WB) and qRT‒PCR. In vivo, the changes in cell morphology and alveolar septum in the lung of mice (C57BL/6, aged 7-8 weeks, male) were observed by H&E staining. In addition, ECM deposition in lung tissue was detected by Masson staining. CD31 and α-SMA protein expression in lung tissue was measured by WB. Results: The serum level of MFGE8 was lower in the ARDS group than in the control group. MFGE8 was identified as a protective factor associated with hospital survival. In vitro, the treatment of human lung microvascular endothelial cells (HLMECs) with LPS for 96 h clearly changed the cells from the typical cobblestone shape of ECs to spindle-like fibroblasts. The scratch and Transwell assay results indicated that endothelial cell migration and invasion were enhanced in the LPS group compared with the control group. Fluorescence microscopy, FCM, WB and PCR showed that LPS greatly inhibited CD31 (endothelial marker) expression and increased α-SMA (mesenchymal marker) expression. These data showed that LPS could induce EndoMT in HLMECs. Notably, siRNA-treated HLMECs yielded the same results. The administration of rhMFGE8 to HLMECs in the LPS or LPS+siRNA group ameliorated the changes in cell morphology and decreased cell migration and invasion. rhMFGE8 attenuated the effect of LPS or LPS+siRNA on EndoMT induction by increasing CD31 and decreasing α-SMA protein and gene expression. Moreover, activation of BMP/Smad1/5-Smad4 signalling in response to LPS and Snail (related to EndoMT transcription factors) expression were increased by MFGE8 knockdown but inhibited by rhMFGE8. In vivo, H&E staining revealed a thickened alveolar septum in the LPS group, and the thickness increased over time; in contrast, rhMFGE8 reversed this effect. ECM deposition occurred early in ALI induced by LPS and increased over time, and the administration of rhMFGE8 reversed this effect. WB showed that LPS inhibited CD31 protein expression and increased α-SMA protein expression in lung tissue. Conclusions: rhMFGE8 exerts a protective effect early in LPS-induced EndoMT through BMP/Smad1/5/Smad4 signalling and could be a therapeutic target in ALI.

Malignancy is a fatal disease with an increasing incidence with each passing year, and the early diagnosis of malignancy can significantly improve the cure rate of patients, which has profound implications for saving patients' lives. The changes of miRNA are closely related to the occurrence of malignant tumors. The expression of miRNA in many malignant tumors is obviously different and unique from that in normal tissues. In this study, a strategy for amplifying microRNA (miRNA) signal was designed using duplex specific nuclease (DSN), which was then combined with Peptide nucleic acid (PNA) probe hybridization technology to prepare a sensitive and efficient paper-based lateral flow biosensor (LFB) for the detection of pancreatic cancer (PC) associated microRNA-10b. The performance evaluation results of the LFB showed that the detection limit of miR-NA-10b is 5 nM/mL, and carries demonstrated well specificity, stability, reproducibility. The biosensor prepared in this paper can provide accurate and rapid detection of miRNA-10b. The detection results play a guiding role in the early diagnosis of PC. Meeting the clinical need for largescale screening of individuals at high risk of PC. Providing new avenues to achieve early mass screening in individuals at high risk of PC.

Poplar is a globalized commercial tree species that supports humanity's economy, energy, and ecology. To evaluate the twelve hybrid Populus euramericana genotypes developed in China, a total of six locations were selected for the test, comprising four climatic types and three soil kinds. The objective of this study is to characterize the early stages of Populus euramericana growth and test locations; to identify good genotypes for stable and high yield that may be encouraged; and to offer practical experience and technical assistance for further breeding of Populus euramericana. Main research methods include the statistical description of tree heights and diameter at breast heights[DBH], the establishment of a mixed effect model to analyze the genotype and environmental interaction effect [G×E], the use of best linear unbiased prediction[BLUP] values as GGE biplots to achieve visual screening, and the calculation of genetic parameters. Results show that the genotype effect [G], the environmental effect [E], and the G×E is significant; the BLUP value has a strong correspondence with the observed value; the goodness of fit of all biplots can explain more than 85% of the variation; broad-sense heritability of tree height and DBH is 0.13 and 0.3, type-B correlation is 0.36 and 0.65; G5, G7, G4 and G9 are excellent genotypes with high yield and stability; using these four genotypes tree height and DBH can get 3.35% and 0.81% genetic gains.The study concludes as follows: Rank-change interaction and scale-effect interaction were distinctly occurred. The G, E, and G×E all had a significant effect on the growth of poplar trees during their early stage. G4, G5, G7, and G9 genotypes have favorable development characteristics. N146 is a great source of paternal genetics.

Farmers and seed companies constantly require high-quality seeds with excellent agronomic performance. However, faced with environmental adversity, limited natural resources and increasing food demand around the globe, more attention has turned to improving crop plant production by implementing efficient strategies. Seed priming technology has shown promising biological improvements leading to suitable agronomic performance in crop plants under adverse environmental conditions. Seeds are subjected to controlled conditions that are conducive to complex physiological, biochemical, and molecular changes, conferring specific stress tolerance to subsequent germination and growth conditions. In this review paper, we aimed to study the recent approaches in the efficiency of hydropriming, osmopriming, chemopriming, hormopriming, nanopriming, matrix priming, biopriming, physical priming and hybrid priming procedures in the production of crop plants under environmental adversity, as well as their biological mechanism changes. All priming methods demonstrated relevant changes in the biological mechanism related to crop plant production by mitigating salinity effects, heavy metals, and flooding stress and enhancing chilling, heat, drought and phytopathogen tolerance. We strongly recommend that researchers combine multiple priming methods, known as hybrid priming, in their investigations to provide novel technologies and additional biological approaches to enhance the knowledge of crop plant science. Thus, the findings shed light on the use of seed priming technology as a key strategy to increase crop plant production under environmental adversity by acquiring stress tolerance and enhancing agronomic traits to meet the global food demand.

A solid structure, such as a road, building wall or envelop, used as a solar collector is considered an effective and new way to use renewable energy. This paper focused on the temperature characteristics of four structures exposed to sunshine: asphalt, red brick, composite cement and concrete road slab. Furthermore, the collected heat based on a hydraulic system was investigated experimentally. For the four structure slabs, their temperature differences are due to solar radiation absorption varied greatly by the material’s heat absorptance and color. Through the test, asphalt slab attained the highest temperature and had the weakest reflection among the structures. Compared with the others, the temperature of the asphalt slab was greater by 8.1%, 14.9% and 16.4% than the brick, composite cement and concrete, respectively. The reflection intensity growth ratio was defined and indicates the growth potential for absorbing radiation in the solid slab surface. From the experiments, it was concluded that a suitable selection of road materials can greatly improve the thermal absorption, conduction and penetration into the solid slab. The collected heat capability was approximately 250 W/m2 to 350 W/m2 in the natural summer condition. A black coating or a surface modification can collect more heat, reaching greater than 250 W/m2. The solar collecting heat efficiency with a surface configuration of the road slab can reach above 30% in the summer time.

The origin and significance of the tonalite–trondhjemite–granodiorite (TTG) units and the familiar metabasite xenoliths they host in the Yangtze Craton, China, remain controversial, and resolving these issues is important if we are to understand the evolution of the early Yangtze Craton. We focused on biotite–tremolite schist xenoliths in the Archean TTG units of the Kongling high-grade metamorphic terrane, and U–Pb dating of their zircons yielded ²⁰⁷Pb/²⁰⁶Pb ages of ca. 3.00 Ga, which provides a minimum age for the formation of the pre-metamorphic basic igneous rock. The host TTGs and late intrusive granitic dikes yield three groups of upper intercept ages at 2.87–2.88, 2.91–2.94, and 3.07 Ga, and a concordant age at 2.94 Ga, which suggest that the Yangtze continental nucleus underwent three important metamorphic–magmatic events in the Mesoarchean at ca. 3.00, 2.94, and 2.87 Ga. The biotite–tremolite schists have high ratios of K₂O/Na₂O and high contents of CaO, Cr, and Ni, thus showing the characteristics of high-K calc-alkaline island-arc volcanic rocks (basalt–andesite) that form by the partial melting of subducted oceanic crust. The data also provide further proof that a Mesoarchean metamorphic basement exists in the Yangtze Plate. Derivation of the magmatic protoliths of the biotite–tremolite schist enclaves from an oceanic crust during slab subduction, and the presence of these xenoliths within the TTG suite, indicate the existence of the initiation of plate tectonics during the Mesoarchean (≤2.94 Ga).

Histone Lysine Specific Demethylase 1 (LSD1) is overexpressed in many cancers and become a new target for anticancer drugs. In recent years, the small molecule inhibitors with various structures targeting LSD1 have been reported. Here we report the binding interaction modes of a series of thieno[3,2-b]pyrrole-5-carboxamides LSD1 inhibitors using molecular docking, three dimensional quantitative structure-activity relationship (3D-QSAR). Comparative molecular field analysis (CoMFA q²=0.783, r²=0.944, r²_pred=0.851) and Comparative molecular similarity indices analysis (CoMSIA q²=0.728, r²=0.982, r²_pred=0.814) were used to establish 3D-QSAR models, which had good verification and prediction capabilities. Based on the contour maps and the information of molecular docking, 8 novel small molecules were designed in silico, among which compounds D4, D5 and D8 with high predictive activity were subjected to further molecular dynamics simulations (MD), and their possible binding modes were explored. It was found that Asn535 plays a crucial role in stabilizing the inhibitors. Furthermore, the ADME and bioavailability prediction for D4, D5 and D8 were carried out. The results would provide valuable guidance for designing new reversible LSD1 inhibitors in the future.

Current numerical methods for simulating biophysical processes in aquatic environments are typically constructed in a grid-based Eulerian framework or as an individual-based model in a particle-based Lagrangian framework. Often, the biogeochemical processes and physical (hydrodynamic) processes occur at different time and space scales, and changes in biological processes do not affect the hydrodynamic conditions. Therefore, it is possible to develop an alternative strategy to grid-based approaches for linking hydrodynamic and biogeochemical models that can significantly improve computational efficiency for this type of linked biophysical model. In this work, we utilize a new technique which links hydrodynamic effects and biological processes through a property-carrying particle model (PCPM) in a Lagrangian/Eulerian framework. The model is tested in idealized cases and its utility is demonstrated in a practical application to Sandusky Bay. Results show the integration of Lagrangian and Eulerian approaches allows for a natural coupling of mass transport (represented by particle movements and random walk) and biological processes in water columns which is described by a nutrient-phytoplankton-zooplankton-detritus (NPZD) biological model. This method is far more efficient than traditional tracer based Eulerian biophysical models for 3-D simulation, particularly for a large domain and/or ensemble simulations.

The concept of ‘big data’ has been widely discussed, and its value has been illuminated throughout a variety of domains. To quickly mine potential values and alleviate the ever-increasing volume of information, machine learning is playing an increasingly important role and faces more challenges than ever. Because few studies exist regarding how to modify machine learning techniques to accommodate big data environments, we provide a comprehensive overview of the history of the evolution of big data, the foundations of machine learning, and the bottlenecks and trends of machine learning in the big data era. More specifically, based on learning principals, we discuss regularization to enhance generalization. The challenges of quality in big data are reduced to the curse of dimensionality, class imbalances, concept drift and label noise, and the underlying reasons and mainstream methodologies to address these challenges are introduced. Learning model development has been driven by domain specifics, dataset complexities, and the presence or absence of human involvement. In this paper, we propose a robust learning paradigm by aggregating the aforementioned factors. Over the next few decades, we believe that these perspectives will lead to novel ideas and encourage more studies aimed at incorporating knowledge and establishing data-driven learning systems that involve both data quality considerations and human interactions.

In this paper, a novel integrated high precision vacuum microelectronic accelerometer is put forward based on the theory of field emission, the accelerometer consists of sensitive structure and interface ASIC. The sensitive structure has a mass of a cathode cone tips array, a folded beam, an emitter electrode and a feedback electrode. The sensor is fabricated on a double side polished (1 0 0) N-type silicon wafer, the tips array of cathode are shaped by wet etching with HNA (HNO3, HF and CH3COOH) and metalized by TiW/Au thin film. The structure of sensor is released by ICP process finally. The interface ASIC was designed and fabricated based on the P-JFET high voltage bipolar process. The accelerometer is tested through static field rollover test, and the test results show the integrated vacuum microelectronic accelerometer has good performances, which sensitivity is 3.081V/g and non-linearity is 0.84% in the measuring range of −1g~1g.

Signal preprocessing and feature extraction are two important and necessary steps of data analysis. In signal analysis, typically these two steps are implemented through multiple algorithms. Moreover, the significant parameters in most algorithms are set empirically. We have developed an algorithm that can preserve and highlight characteristic waveforms while attenuating non-feature waveforms. The parameters in the algorithm are set through difference analysis. We have conducted experiments on both clinical and open-source ECG data, obtaining effective test results.

Cholangiocarcinoma is the most common primary malignant tumor of the bile duct. The current standard first-line treatment for advanced or metastatic cholangiocarcinoma is gemcitabine and cisplatin. However, few effective treatment choices exist for refractory cholangiocarcinoma, and additional therapeutic drugs are urgently required. Our previous work demonstrated that the ALDH isoform 1A3 plays a vital role in the malignant behavior of cholangiocarcinoma and may serve as a new therapeutic target. In this study, we found a positive correlation between ALDH1A3 protein expression levels and cell migration abilities of three cholangiocarcinoma cell lines, which was verified using ALDH1A3-overexpressing and ALDH1A3-knockdown clones. We also used ALDH1A3-high and ALDH1A3-low populations of cholangiocarcinoma cell lines from the Library of Integrated Network-based Cellular Signatures (LINCS) program and assessed the effects of ruxolitinib, a commercially available JAK2 inhibitor. Ruxolitinib had a higher cytotoxic effect when combined with gemcitabine. Furthermore, the nuclear translocation STAT1 and STAT3 heterodimers were markedly diminished by ruxolitinib treatment, possibly resulting in decreased ALDH1A3 activation. Notably, ruxolitinib alone or combined with gemcitabine led to significantly reduced tumor size and weight. Collectively, our studies suggest that ruxolitinib might suppress the ALDH1A3 activation through the JAK2/STAT1/3 pathway in cholangiocarcinoma, and trials should be undertaken to evaluate its efficacy in clinical therapy.

Tumor invasion, metastasis, and recrudesce remain a considerable challenge in the treatment of gastric cancer (GC). Herein, we first identified that RBFOX3 (RNA binding protein fox-1 homolog 3) was significantly up-regulated in GC tissues and negatively linked to the survival rate of GC patients. RBFOX3 promoted cell division and cell cycle progression in vitro as well as in vivo. Furthermore, RBFOX3 increased cell invasion and migration ability. Interestingly, both the suppression of GC cell multiplication and invasion moderated by the silencing of RBFOX3 was rescued by HTERT up-regulation. Additionally, RBFOX3 augmented the resistance of GC cells to 5-fluorouracil (5-Fu) by repressing RBFOX3. Mechanistically, exogenous up-regulation of RBFOX3 triggered promoter activity and HTERT expression thereby enhancing the division and development of GC cells. Importantly, our findings revealed that RBFOX3 interacted with AP-2β to modulate the HTERT expression as demonstrated by co-immunoprecipitation analysis. In conclusion, our study indicates that high expression of RBFOX3 promotes GC progression and development but predicts worse prognosis by stimulating HTERT signaling. Moreover, the results suggest that the RBFOX3/AP-2β/HTERT pathway is a novel target for the development of therapeutic agents for the prevention and treatment of GC reappearance and metastasis.

Aging, a natural process occurring in both normal and degenerative conditions, is closely associated with collagen degradation, impacting various bodily systems such as the skin. The continuous aging of the skin, influenced by both intrinsic and extrinsic factors, underscores the importance of collagen in dermatological and cosmetic contexts. Notably, collagen supplements enriched with essential amino acids like proline and glycine along with marine fish collagen have become popular for their safety and effectiveness in mitigating the aging process. To compile relevant literature on the anti-aging applications of marine collagen, a systematic search and analysis of peer-reviewed papers was conducted using reputable databases including PubMed, Cochrane Library, Web of Science, and Embase, covering publications from 1956 to 2023. From in vitro to in vivo experiments, the reviewed studies elucidate the anti-aging benefits of marine collagen, emphasizing its role in combating skin aging and promoting overall skin health. Many bioactive marine peptides exhibit diverse anti-aging properties, including free radical scavenging, apoptosis inhibition, lifespan extension in various organisms, and protective effects in aging humans. Furthermore, the peptide production of hyaluronic acid is discussed as a mechanism to fortify collagen and enhance skin moisture, contributing to the anti-aging effects of collagen supplementation. The integration of bio-tissue engineering in marine collagen applications is also explored, highlighting its proven utility in addressing skin and bone damage. Insights from this review illuminate the diverse biomedical applications of marine collagen alongside keystone molecular editing tools such as CRISPR, positioning it as a versatile resource in anti-aging interventions. However, limitations to the scope of its application exist. Thus, by delving into these nuanced considerations, this review contributes to a comprehensive understanding of the potential and challenges associated with marine collagen in the realm of anti-aging applications.

Global agriculture has been forced to increase food production to feed the growing human population, while confronting various environmental obstacles such as global warming, resistance to pathogens, and constraints on arable land caused by soil salinity, drought, rising sea level, saltwater intrusion, and urbanization. Regarding abiotic stresses, salinity is a worldwide problem for agricultural production. Many efforts, therefore, have been made to cope with the environmental challenges, however, the progress of salinization, which is mainly caused and accelerated by anthropogenic activities, is likely faster than our progress in finding ways to deal with this problem. In addition, drought represents a global threat to the production of major crops. In addition, pests and pathogens cause significant crop losses and diminish global food security. Among the various strategies that have been investigated and applied in plant science, antimicrobial peptides derived from plants have caught widespread attention from scientists since these peptides exhibit beneficial biological activities. In agricultural science, there have been reports on the roles of antimicrobial peptides with active properties against biotic and abiotic stresses. Non-specific plant lipid transfer proteins, thionins, systemins, defensins, cyclotides, and heveins-like antimicrobial peptides are common antimicrobial peptides that have been found to be involved in the defense system against fungi and insect pests. Based on their potential ability to protect crops from pests, bacteria, and pathogenic fungi, the use of antimicrobial peptide genes in creating transgenic plants has been largely conducted during the last decades, and these studies have obtained positive results against the growth of fungi and bacteria. This review will focus on the latest progress in studies of antimicrobial peptides related to biotic and abiotic stress tolerance in plants. We will also update the current progress in the development of antimicrobial peptide-based transgenic crops.

This paper Numerically investigates the effectiveness of the turbine rotating blade nozzle position on the vortex and film composite cooling performance. The coolant injecting nozzles arranged near the pressure surface side (PS-side-in) .vs. arranged near the suction surface side (SS-side-in) are compared at the rotating speed range of 0-4000rpm with fluid and thermal conjugate approach. Results show that the nozzle position presents different influences under low and higher rotating speed. In terms of the mainstream flow, rotation makes the stagnation line move from the PS-side pressure surface side to the SS-side suc-tion surface side, which changes the coolant film attachment on the blade leading edge surface. The nozzle position however indicates limited influence on the coolant film flow. In terms of the internal channel vortex flow, the coolant injecting from the nozzles forms a high-velocity region near the target wall which brings about enhancing convective heat transfer. The direction of the near wall vortex flow is opposite and align to the Coriolis force direction in both the PS-side-in and SS-side-in, respectively. Therefore, the Coriolis force augments to the heat transfer of the internal vortex cooling in SS-side-in while weakens the internal heat transfer in PS-side-in. Such effects become more intense with higher rotational speed. The blade surface area-averaged dimensionless temperature that inversely proportional to the actual temperature is 7.8% higher in SS-side-in as compared to that in PS-side-in. The SS-side-in suggests more superior composite cooling perfor-mance under the relatively higher rotating speed.

The ultrasonic vibration assisted pressing process can improve the fluidity, the uneven distribution of density and particle size of WC-Co powder. However, the microscopic mechanism of ultrasonic vibration on the powder remains unclear. In this paper, WC and Co particles are simulated by three-dimensional spherical models of two particle sizes with the aide of the secondary development of Python. At the same time, the forming process of powder at mesoscale is simulated in the virtue of the finite element analysis software ABAQUS. The influence of vibration amplitude on the fluidity, the filling density and the stress distribution of WC-Co powder is investigated when the ultrasonic vibration is applied to the conventional pressing process. From simulation results, the ultrasonic vibration amplitude has great influences on the density of the compact. With the increase of the ultrasonic amplitude, the compact density also increases gradually. At the initial stage of the compaction, the particles move violently under the action of ultrasonic vibration, the fluidity is obviously enhanced, the arch bridge effect between particles is destroyed, the fine particles quickly fill the pores between the large particles, which increase the density, and the residual stress in the billet decreases after the compaction. From the experimental results, the size distribution of the billet is more uniform, the elastic aftereffect is reduced, the dimensional instability is improved, and the density curves obtained by experiment and simulation are within a reasonable error range.

β-glucosidases (BGLs) play a crucial role in the degradation of lignocellulosic biomass as well as in industrial applications such as pharmaceuticals, foods, and flavors. However, the application of BGLs has been largely hindered by issues such as low enzyme activity, product inhibition, low stability, etc. Many approaches have been developed to engineer BGLs to improve these enzymatic characteristics to facilitate industrial production. In this article, we review the recent advances in BGL engineering in the field, including the efforts from our laboratory. We summarize and discuss the BGL engineering studies according to the targeted functions as well as the specific strategies used for BGL engineering.

Fracture of viscoplastic materials is a complex process due to its time-dependent and plastic responses. Numerical simulation for fracture plays a significant role in crack prediction and failure analysis. In recent years, the phase field model is becoming a competitive approach to predict crack growth and has been extended to inelastic materials such as elasto-plastic, viscoelastic and viscoplastic materials, etc. However, the contribution of inelastic energy to crack growth is seldom studied. For this reason, we implement the phase field model coupled with a viscoplastic constitutive in finite element framework, in which the elastic energy and inelastic energy are used as crack driving energy. The implicit algorithm for a viscoplastic constitutive is presented, this procedure is suitable for other viscoplastic constitutive relations. The strain rate effect, creep effect, stress relaxation effect and cyclic loading responses are tested using a single element model with different inelastic energy contributions; A titanium alloy plate specimen and a stainless-steel plate specimen under tension are studied compared with the experimental observations in existing literature. The results show that the above typical damage phenomenon and fracture process can be well reproduced; The inelastic energy significantly affects the force-displacement responses but has slight effect on the crack paths.

Background: Exposure to inorganic arsenic (iAs) remains a global public health problem. The liver is the main target organ of arsenic, leading to arsenic-induced liver fibrosis. Autophagy is involved. Phosphatase and tensin homology deleted on chromosome ten (PTEN) may participate in arsenic-induced liver fibrosis by regulating autophagy, but the exact mechanisms remain unclear. We established a mouse model of arsenic poisoning through the drinking water, and a fibrosis model using the huma stellate cell (HSC) line LX-2, which was exposed to NaAsO₂ for 24h. HE and Masson staining was adopted to observe the degree of liver fibrosis. The cells were transfected using PTEN overexpression plasmid. Western blot and qRT-PCR were used to determine the levels of protein/mRNA expression. The in vivo results were confirmed in HSCs exposed to NaAsO₂, with changes suggesting fibrosis as seen in mice. NaAsO₂ upregulated the expression of the autophagic markers microtubule-associated protein light chain A/B (LC3), recombinant human autophagy effector protein (Beclin-1), hairy and enhancer of split homolog-1 (HES1), but downregulated PTEN. α-smooth muscle actin (α-SMA) expression was significantly upregulated in all NaAsO₂ groups. PTEN overexpression altered NaAsO₂-induced autophagy which LC3, Beclin-1 were downregulated. Notch1, HES1, α-SMA, and collagenⅠexpression were all downregulated in the NaAsO₂ groups. In conclusion, PTEN overexpression might decrease autophagy and inhibit fibrosis progression caused by this toxin. The NOTCH1/HES1 pathway is likely to be involved in this process. Most previous studies did not investigate PTEN and arsenic-induced liver fibrosis specifically. The present study highlights the importance of targeting PTEN for the management of arsenic exposure.

In this paper, MgAl Layered double hydroxides (LDH) were synthesized by co-precipitation method using a colloid mill and characterized by XRD, IR and SEM. The LDHs was repeatedly tested and compared with different bearing lifetime tester in lithium base grease, and it was found that the environmental-friendly LDHs had greater performance than the traditional antioxidant, and it was the development direction of a new generation of environmental-friendly antioxidants in the future. By adding LDHs into large electric shovel greats (GRK-A) in open-pit coal mine, it can be seen by PDSC evaluation that the service lifetime of grease is extended by 20% while the overall performance of grease is not affected. With the increase of LDHs addition, the grease sample gets the greater activation energy, the stronger thermal oxidation and decomposition resistance. Comparing the energy storage modulus and flow transition index at different temperatures, it can be seen that adding the right amount of LDHs needs close attention for the system oxidation resistance and viscoelasticity. For the electric shovel grease system, the best oxidation resistance and rheological properties can be achieved by adding 2% of LDHs. The rheological viscosity-temperature curves show that the grease samples with different ratios of solid LDHs have better low-temperature properties than the mine grease.

Surface activity of humic acid (HA) and its six sub-fractions isolated from forest soil were characterized by surface tension measurements, dynamic light scattering, and laser doppler electrophoresis. The surface tension of HA sub-fractions decreased from 72.4 mN·m-1 to 36.8 mN·m-1 with the increasing concentration from 0 to 20000 mg·L-1. The critical micelle concentration (CMC) of HA and its sub-fractions ranged from 216 to 1024 mg·L-1 with the multiple linear regression equation of CMC = 18896–6.9×C–296×alkyl-C–331×aromatic-C–17019×H/C+4054×HB/HI (p < 0.05). The Z-average particle size ranges from 108.2 nm to 186.9 nm. The maximum particle size was 5000 nm after filtered with a membrane of 0.45 μm, indicating HA and its sub-fractions progressed self-assembly during 2000 mg·L-1, pH = 6.86. The number-base particle size distribution of HA sub-fractions was identified as four peaks by Gaussian model, and the aggregate sizes were mainly in six clusters including 2 ± 1 nm, 5 ± 2 nm, 10 ± 3 nm, 21 ± 8 nm, 40 ± 10 nm, and > 50 nm indicating multiple aggregations of different particle sizes in the HA fractions solution.

Cholinergic innervation in pancreas controls both the release of digestive enzymes to support the intestinal digestion and absorption, as well as insulin release to promote nutrient use in the cells of the body. The effects of muscarinic receptor stimulation are described in detail for endocrine beta cells and exocrine acinar cells separately. Here we describe morphological and functional criteria to separate these two cell types in situ in tissue slices and simultaneously measure their response to ACh stimulation on cytosolic Ca2+ oscillations [Ca2+]c in stimulatory glucose conditions. Our results show that both cell types respond to glucose directly in the concentration range compatible with the glucose transporters they express. The physiological ACh concentration increases the frequency of glucose stimulated [Ca2+]c oscillations in both cell types and synchronizes [Ca2+]c oscillations in acinar cells. The pharmacological ACh concentration further increases the oscillation frequency on the level of individual beta cells, inhibits the synchronization between these cells, and abolishes oscillatory activity in acinar cells. We discuss possible mechanisms leading to the observed phenomena.

The relationship between the street environment and the health, education, mobility, and criminal behaviors of its citizens has long been investigated by economists, sociologists and urban planners. Home buyers were found to pay a premium for better street appearance. Prior studies considering streetscapes mainly focus on objective measures such as the number of nearby trees, the tree canopy area, or the view index of physical features such as greenery, sky or building. However, subjective perceptions may have complex or subtle relationships to physical features, individual physical features or simply summing them up do not capture people’s comprehensive perception. In contrast, this study proposed a new approach for the urban-scale application to quantify both subjectively and objectively measured streetscape scores for six important perception qualities, namely Greenness, Walkability, Safety, Imageability, Enclosure, and Complexity. Built on prior quantitative studies in urban design quality and emerging applications in deep learning and open source street view imagery for urban perceptions, we integrated existing frameworks to (1) effectively collect and evaluate both subjectively and objectively- measured perceptions; (2) investigate the coherence and divergence in ML-predicted subjective scores and formula-derived objective scores; and (3) compare their effects in affecting house prices taking Shanghai as a case study using a large-scale dataset on home transactions. The results implied: first, the percentage increase in sales price attributable to street scores is significant for both subjective and objective measurements. In general subjective scores explained more variance over structural attributes and objective scores in hedonic price model. Particularly, objective Greenness, subjective Safety and Imageability scores positively affected house prices. Second, for Greenness and Imageability scores, the subjective and objective measures exhibited opposite signs in affecting house prices, which implied that there might be mechanisms related to the psychological, social-demographical characteristics of street users that have not been fully incorporated by objective measures that taking view indices or recombination of them. In addition, certain objective measure might outperform subjective counterpart when the connotation of the perception is self-evident and not complicated, for example the Greenness. For those concepts were not familiar to the average person, subjective framework exhibits better performance. This is the first study comprehensively expanding hedonic price method with both subjectively and objectively measured streetscape qualities. It suggested that city authorities could levy a street environment tax to compensate the public budget invested in street environment where developers secured benefits from a price premium. This study enriches our understanding of the economic values of the subjective and objective measures street qualities. It sheds light on promising future study areas where the coherence and divergence of the two measurements should be further stressed.

The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called “McSnow”) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops >5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops <0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical “experiments” were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution.

Most recently, an outbreak of severe pneumonia caused by the infection of 2019-nCoV, a novel coronavirus first identified in Wuhan, China, imposes serious threats to public health. Many important aspects about 2019-nCoV remain largely unknown, among which, the limitation of antiviral therapies represents one of the most critical problems. More recently, it was confirmed that human ACE2 is the receptor for the entry of 2019-nCoV into lower respiratory tract epithelial cells. Give this observation, it is thus expected that the virus could be inhibited if we decrease the expression of ACE2. Here by screening two databases, Connectivity Map (CMap) and our JeaMoon Map (JMap), we identified a number of candidate agents that decrease ACE2 expression. CMap analysis identified 5 compounds, among which, Azathioprine is a possible therapeutic strategy for anti-2019-nCoV. Moreover, JMap analysis revealed a number of comounds, biologics, and traditional Chinese medicine, among which, Andrographis, Urtica, Sambucus, Astragalus, valproic acid, butyrate, and epoxomicin represent the most significant and possible strategies for anti-2019-nCoV therapies. This study provides a number of clues and possible therapeutic strategies for 2019-nCoV prevention and treatment.

The composition of bacteria in the gastrointestinal tract of piglets is easily affected by environmental changes, particularly during the weaning period. Compound strains of Lactobacillus reuteri and Lactobacillus salivarius were supplemented to piglets during pre- and post-weaning to determine their effects in improving the growth performance and ameliorating the diarrhea rate and stress caused by antioxidation in piglets. A larger number of L. reuteri and L. salivarius colonized the distal segment of the ileum and the total numbers of Lactobacillus spp. and Bifidobacterium were higher in the ileal mucous membrane and cecal lumen with probiotics supplementation. The numbers of antioxidative and immune molecules were increased in the plasma following compound bacteria (CL) supplementation, whereas cortisol and endotoxin levels were lower and growth hormone and insulin-like growth factor 1 were higher. Spearman’s and KEGG analysis of the bacterial operational taxonomic unit and antioxidative and immune indices and metabolic genes indicated that the body growth modulation by CL supplementation could be attributed to optimization of the intestinal bacterial composition. Collectively, these results suggest that supplementation with CL could reduce stress and improve the growth performance of piglets during weaning by optimizing the intestinal bacterial composition.

Prestress loss evaluation in prestressed strand is essential for prestressed structures. However, the sensors installed outside the duct can only measure the total prestress loss. The sensors attached on strand inside the duct also have several problems, such as inadequate durability in an aggressive environment, vulnerable damage at tensioning and so on. This paper proposes a new installation method for long-gauge fiber Bragg grating (LFBG) sensor to prevent accidental damage. Then the itemized prestress losses were determined in each stage of the pre-tensioning and post-tensioning according to the LFBG measurements. We verified the applicability of the LFBG sensors for prestress monitoring and the accuracy of the proposed prestress loss calculation method during pre-tensioning and post-tensioning. In the pre-tensioning case, the calculated prestress losses had less deviation from the true losses than those obtained from foil-strain gauges, and the durability of the LFBG sensors was better than foil-strain gauges, whereas in post-tensioning case, the calculated prestress losses were close to those derived from theoretical predictions. Finally, we monitored prestress variation in the strand for 90 days. The itemized prestress losses at each stages of post-tensioning were obtained by the proposed calculation method to show the prospect of the LFBG sensors in practical evaluation.

Due to poor ventilation conditions in the tunnel, if gas pipeline leaks, the consequence of the accident will be more serious. Therefore, before the emergency repair, gas in the tunnel needs to be excharged so as not to explode during the repair process. Therefore, it is necessary to study the ventilation of gas in the tunnel. Based on the computational fluid dynamics (CFD) theory and taking the Yanyingshan tunnel section of China-Myanmar pipeline as an example, this paper uses Fluent software to establish the leakage model of the gas pipeline and fan model in the tunnel and analyzes the influence of different fan locations and number of fans on gas concentration. It can be concluded that: (1) the use of press-in method makes it more efficient to discharge gas out of the tunnel. (2) In order to make ventilation efficient, the fan should be arranged in a higher position and needs to be at a distance from the top of the tunnel. (3) Parallel use of two fans has better ventilation effect than single fan.

The utilization of optical antennas for active control of far-field radiation at the subwavelength scale is crucial in various scientific and technological applications. We propose a thermally tunable disk design of indium tin oxide (ITO) and aluminum gallium nitride (Al0.18Ga0.82As), enabling a switch between absorption and scattering. Furthermore, the control of far-field radiation pattern can be easily realized by combining ITO and Al0.18Ga0.82As to enhance or suppress emission. Our results demonstrate that hybrid structure can be dynamically tuned with temperature variations. In the proposed design, a frequency is achieved at the epsilon-near-zero wavelength of 1240 nm. The thermal tunability of hybrid structure introduces new multifunctional possibilities for light manipulation, thereby enhancing the potential applications of new devices in the near-infrared range.

This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework's capabilities. Calibration and verification demonstrate the models' effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory's neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.

Electrochemical biosensors based on immobilized enzymes are among the most popular and commercially successful biosensors. Literature in this field suggests that modification of electrodes with nanomaterials is an excellent method for enzyme immobilization, which can greatly improve the stability and sensitivity of the sensor. However, the poor stability, weak reproducibility, and limited lifetime of the enzyme itself still limit the requirements for the development of enzyme electrochemical biosensors for food production process monitoring. Therefore, constructing sensing technologies based on enzyme electrochemical biosensors remains a great challenge. This article outlines the construction principles of four generations of enzyme electrochemical biosensors and discusses the applications of single-enzyme systems, multi-enzyme systems and nano-enzyme systems developed based on these principles. The article further describes methods to improve enzyme immobilisation by combining different types of nanomaterials such as metals and their oxides, graphene-related materials, metal-organic frameworks, carbon nanotubes and conducting polymers. In addition, the article highlights the challenges and future trends of enzyme electrochemical biosensors, providing theoretical support and future perspectives for further research and development of high-performance enzyme chemical biosensors.

We study the influence of high-order twisting phases on polarization states and optical angular momentum of a vector light field with locally linear polarization and a hybrid state of polarization (SoP). The initial SoP of a twisted vector optical field (TVOF) modulated by the high-order twisting phase possesses various symmetric distributions. The propagating properties of a high-order TVOF with locally linear polarization and hybrid SoP are explored, including the intensity compression, expansion, and conversion between the linear and circular polarization components. In particular, orbital angular momentum (OAM) appears in a high-order TVOF during propagation where no OAM exists in the initial field. The variation of OAM distribution in cross-section becomes more frequent with the increase of the twisting phase order. In addition, a non-symmetric OAM distribution appears in an anisotropic TVOF, leading to the rotation of the beam around the propagation axis during propagation. These results provide a new approach for optical field manipulation in a high-order TVOF.

Plant phenotype plays an important role in crop breeding and planting. Leaf phenotype is an important part of plant phenotype. In order to analyze the leaf phenotype, the target leaf is required to be segmented from the complex background image. In this paper, an automatic soybean leaf segmentation method based on object detection and interactive segmentation models is proposed. Firstly, the Libra R-CNN object detection algorithm is used to detect all soybean leaves in the image. Then, based on the idea that the target soybean leaf is located in the center of the image and the area is large, the detection bounding box of the target leaf is selected. In order not to destroy the segmentation result, the bounding box is optimized to completely enclose the whole leaf. Finally, according to the optimized bounding box, the prior channels of foreground and background are constructed using Gaussian model. The two channels together with the original image are as the input of the interactive object segmentation with inside-outside guidance model to segment the target soybean leaf. A large number of qualitative and quantitative experimental results show that the method has high segmentation accuracy and strong generalization capacity.

The direct Cr (VI) reduction process by oxalic acid was conducted and the results showed that the Cr (VI) was efficiently reduced by oxalic acid at high reaction temperature and high dosage of oxalic acid. The reduced product, Cr (III), was easily generated stable complex compounds (Cr(HC2O4)3) with oxalate, which displayed a negative effect on the reduction process. The high reaction temperature and high acidic medium could destroy the stable structure of a complex compound to release oxalate, and facilitate the reduction of Cr (VI). Generally, the present study provided a versatile strategy for Cr (VI) reduction, exhibiting a bright application future for real wastewater treatment.

TiC–high Mn steel-bonded carbide with a cellular structure was designed and fabricated by powder metallurgy techniques using coarse and fine TiC particles as the hard phase. This preparation process was carefully investigated and optimized. The microstructure of the TiC steel-bonded carbide was observed using a scanning electron microscope. Results showed that there are two types of microstructures in the TiC steel-bonded carbide: the coarse-grained TiC and fine-grained TiC. The transverse rupture strength and impact toughness of the alloy reach maximum values 2231 MPa and 12.87 J/cm2, respectively when the starting weight ratio of MP-A (containing coarse TiC particles) to MP-B (containing fine TiC particles) is 60:40. Hence, this study serves as a feasible example of how to prepare a high-strength and high-toughness TiC–high Mn steel-bonded carbide.

The cyber physical systems of smart cities are facing increasingly severe attack situations, and traditional separate protection methods are difficult to effectively respond to. It is urgent to coordinate public security and network security protection. However, the integration of the two faces many challenges and is a very promising research field. The aim of this study is to investigate technical approaches for the synergy between public safety and cyber security. This paper proposes a smart city safety protection model inspired by the human immune mechanism. It was found that through a three line defense architecture similar to the human immune mechanism, and with the help of certain algorithms and functional middleware modules, public security and network security protection components can be dynamically combined to achieve collaboration. This work has verified through experiments a promising path to effectively resist complicated attack threats intertwined with public safety and cyber security factors.

In this paper we present the exploration of indoor positioning technologies for UAVs, and navigation techniques for path planning and obstacle avoidance. The objective is to perform warehouse inventory tasks using a drone to search for barcodes or markers to identify the objects. For the indoor positioning techniques, we employ Visual-Inertial Odometry (VIO), Ultra-Wideband (UWB), AprilTag fiducial markers, and Simultaneous Localization and Mapping (SLAM). These algorithms encompass global positioning, local positioning, and pre-mapping positioning, comparing the merits and drawbacks of various techniques and trajectories. In UAV navigation, we combine SLAM-based RTAB-Map indoor mapping and navigation path planning of the ROS for indoor environments. This system enables precise drone positioning indoors and utilizes global and local path planners to generate flight paths that avoid dynamic, static, unknown, and known obstacles, demonstrating high practicality and feasibility. To achieve the warehouse inventory inspection, a reinforcement learning approach is proposed to recognize the markers by adjusting the UAV's viewpoint. We address several main problems in inventory management, including efficiently planning paths while ensuring a certain level of detection rate. Two reinforcement learning techniques, AC (Actor-Critic) and PPO (Proximal Policy Optimization), are implemented based on AprilTag identification. Testing is performed in both simulated and real-world environments, and the effectiveness of the proposed method is validated.Code is available at https://github.com/kellen080/Navigation and https://github.com/kellen080/Indoor\_Positioning.

This study explores the application of the Fully Convolutional Network (FCN) algorithm to the field of meteorology, specifically for the short-term nowcasting of severe convective weather events such as hail, convective wind gust (CG) and thunderstorms, short-term heavy rain(STHR) in Gansu. Training data comes from the European Center for Medium-Range Weather Forecasts (ECMWF) and real-time ground observations, the performance of the proposed FCN model based on 2017 to 2021 training datasets demonstrate a high prediction accuracy, with an overall error rate of 16.6%. Furthermore, the model exhibited an error rate of 18.6% across both severe and non-severe weather conditions when testing against the 2022 dataset. Operational deployment in 2023 has yielded an average Critical Success Index (CSI) of 24.3%, a Probability of Detection (POD) of 62.6%, and a False Alarm Ratio (FAR) of 71.2% for these convective events. It is noteworthy that the predicting performance for STHR was particularly effective with the highest POD and CSI, as well as the lowest FAR. CG and hail predictions had comparable CSI and FAR scores, although the POD for CG surpassed that for hail. The FCN model’s optimal performance for hail prediction occurred at the 4th, 8th, and 10th forecast hours, while for CG, the 6th hour was most accurate, and for STHR, the 2nd and 4th hours were most effective. These findings underscore the FCN model's ideal suitability for short-term forecasting of severe convective weather, presenting extensive prospects for the automation of meteorological operations in the future.

RNA, as an important substance for regulating biological growth and development, has significant implications for visualization research. However, many spontaneously fluorescent substances in plants greatly interfere with the effectiveness of plant bioimaging. Aggregetion- induced emission luminogens (AIEgens), due to their luminescent properties, tunable molecular size, high fluorescence intensity, good photostability, and low cell toxicity, have been widely applied in the animal and medical fields. We have found that AIEgens have great potential as RNA fluorescent probes for efficient imaging in plants. In this review, we first introduce several common RNA labeling forms and point out their pros and cons. We briefly describe the development of AIEgens and the AIE mechanism, and then present various practical applications of AIEgens, including detailed examples of their use as biological markers. To further promote the application of AIE in the field of RNA, we suggest the use of AIEgens to modify target RNA via techniques such as click chemistry or CRISPR/Cas, to achieve RNA visualization in plants. highly possible to modify target RNA with AIEgens in vivo for RNA visualization.

The overpopulation of feral pigeons in Hong Kong has significantly disrupted the urban ecosystem, highlighting the urgent need for effective strategies to control their population. In general, control measures should be implemented and re-evaluated periodically following accurate estimations of feral pigeon population in the concerned regions, which, however, is very difficult in urban envi-ronments due to the concealment and mobility of pigeons within complex building structures. With the advances in deep learning, computer vision can be a promising tool for pigeon monitoring and population estimation but has not been well investigated so far. Therefore, we propose an improved deep learning model based on Mask-RCNN (Swin-Mask R-CNN) for feral pigeon detection using computer vision techniques. Specifically, our model consists of a Swin transformer network (STN) as the backbone, a feature pyramid network (FPN) as the neck, and three decoupled detection heads. The STN is utilized to extract deep feature information of feral pigeons through local and cross-window attention mechanisms. The FPN is employed to fuse multi-scale features and enhance the multi-scale learning ability. Heads in the three branches are responsible for classification, pre-dicting best bounding boxes, and segmentation of feral pigeons, respectively. During the prediction phase, a Slicing Aided Hyper Inference (SAHI) tool is employed to zoom in on the feature infor-mation of small feral pigeon targets, and the segmentation head is frozen to expedite inference of large images. Experiments were conducted on feral pigeon dataset to evaluate model performance. The results reveal that our model is well-suited for detecting small targets in high-resolution images and achieves excellent recognition performance for feral pigeons with a mAP (mean average pre-cision) and an AP50 (average precision at 50% intersection over union) of 0.74 and 0.93, respectively. For small target feral pigeons, AP50 in small scale (AP50s) improved by 10% as compared to the Mask R-CNN (AP50s of 0.75), demonstrating its potential for dynamic pigeon detection and population estimation in the future.

It was of great practical significance to repair the toxicity of salt stress environment to soybean seedlings and maintain the balance between agricultural production and ecological environment in the Yellow River valley of China. ‘Xudou 20’ was used as the experimental material, a large-scale planting variety in the old Yellow River basin. Endophytes 131 and 137 isolated from soybean root nodule were taken as the research objects, and the soybean plants were cultivated by pot culture in intelligent artificial incubator. Salt stress group, bacteria suspension group and control group were set up to study the effects of inoculation treatments on the activities of superoxide dismutase (SOD) and catalase (CAT) of soybean seedlings under different NaCl stress. The results showed that when inoculated with endophyte 131 bacterial suspension and cultured for 14 days, the SOD activity was the highest (14.89 U•g−1•FW) at the salt concentration 50 mmol•L-1. When inoculated with 131 bacterial suspension (2:1) and cultured for 28 days, the SOD activity reached the highest (0.94 ug-1FW) at the salt concentration of 50 mmol•L-1, and the CAT activity amounted to the highest (1910 U•g−1•min−1). The 16S rDNA sequencing and phylogenetic analysis showed that the most similar strain of strain 137 was Bacillus cereus, and the most similar strain of strain 131 was Enterobacter ludwigii. Therefore, the activities of SOD and CAT in soybean seedlings inoculated with endophytes 131 and 137 increased at different degrees under salt stress, which could effectively alleviate the damage of salt stress environment to plants, and thus improve the stress resistance of plants.

The recognition of coal-rock interface is very crucial for the research in the intelligent production of coal mine. This study investigates the application of terahertz time-domain spectroscopy in the recognition of coal-rock interface, including the identification of coal-rock and coal-rock mixtures, as well as the accurate characterization of coal seam thickness. Terahertz detection was used to obtain the optical parameter information of the pressed pellets prepared by mixing two different kinds of coal and two kinds of rock. Based on the experiment results, the database was established for the identification of coal-rock interfaces in coal mining machines. The terahertz detection was performed on 10 different kinds of sheet anthracite with different thickness, and the terahertz spectra of coal seams with different thickness were simulated and calculated by using simulation software, which can accurately obtain the thickness of coal seams and provide effective mining thickness parameters for coal seam mining. Through the experiment and simulation, the terahertz time-domain spectroscopy technology has a promising application prospect in the identification of coal-rock interface.

Permeability has an important effect on drug absorption. In this study, the effect of different concentrations of sodium sulfobutyl ether-β-cyclodextrin (SBE-β-CD) on the absorption of ranitidine was investigated to examine the mechanism of permeability changes. The results of parallel artificial membrane permeability assay (PAMPA) showed that increasing the concentration of sodium sulfobutyl ether-β-cyclodextrin, 0, 0.12% (w/v), 0.36% (w/v) and 3.6% (w/v), respectively, the apparent permeability coefficient of ranitidine decreased to 4.62×10-5 , 4.5×10-5 , 3.61×10-5 and 1.08×10-5 in Caco-2 cells, respectively. The same results were obtained from oral pharmacokinetic study in rats; Further studies indicated that SBE-β-CD significantly increased the zeta potential of ranitidine. SBE-β-CD interacted with ranitidine charges to form a complex that reduced ranitidine permeability, and SBE-β-CD should be chosen with caution for drugs with poor permeability.

The present study was to investigate effects of total flavonoids from Taraxacum mongolicum Hand.-Mazz. (FT) on fermentation quality, antioxidant status and microbial community of Caragana korshinskii Kom. (CK) silage. CK was ensiled with no additive (CON), 1% FT and 2% FT on a fresh weight (FW) basis for 60 days. The results showed that 1% FT and 2% FT groups displayed higher DM content than CON group, and 2% FT group had the best effect on nutrient preservation. Compared with CON and 1% FT groups, 2% FT group exhibited the best silage fermentation quality and the highest antioxidant activity, including increased lactic acid, acetic acid concentrations and the activities of antioxidant enzymes, as well as decreased pH and the ammonia nitrogen (NH₃-N) concentration. Moreover, 2% FT addition significantly affected the microbial community, such as increased abundance of Lactobacillus and decreased abundances of Pseudomonas and unidentified Cyanobacteria. The abundances of Lactobacillus parafarraginis and Lactobacillus brevis were negatively correlated to pH, while they were positively correlated with T-AOC, GSH-Px and CAT activities. In conclusion, 2% FT may be used as additives to inhibit the growth of undesirable microorganisms and promote fermentation quality and antioxidant activity of CK silage.

The theory of electron spin has been proposed for a century, but the study of quantum effects in biological molecules is still in its infancy. Chirality-induced spin selectivity (CISS) is a very modern theory that can explain many biochemical phenomena. In this paper, we propose a new theoretical model based on CISS theory and quantum chemistry theory, which can well explain the theoretical explanation of the chiral selectivity of chiral proteins. Moreover, this theory can predict the spin state of corresponding chiral molecules. Taking L-DOPA and AADC enzyme as examples, this theoretical model solves the theoretical explanation of AADC enzyme's chiral catalysis selectivity problem and successfully predicts the spin state of L-DOPA and D-DOPA's valence electrons.

To predict the remaining useful life (RUL) of proton exchange membrane fuel cell (PEMFC) in advance, a prediction method based on the voltage recovery model and Bayesian optimization of a multi-kernel relevance vector machine (MK-RVM) is proposed in this paper. First, the empirical mode decomposition (EMD) method was used to preprocess the data, and then the MK-RVM was used to train the model. Then, the Bayesian optimization algorithm was used to optimize the weight coefficient of the kernel function to complete the parameter update of the prediction model, and the voltage recovery model was added to the prediction model to realize the rapid and accurate prediction of the RUL of PEMFC. Finally, the method proposed in this paper was applied to the open data set of PEMFC provided by FCLAB, and the prediction accuracy of the RUL of PEMFC was obtained by 95.35%, which showed that the method had good gen-eralization ability and verified the accuracy of the prediction for the RUL of PEMFC.

Building outlines extracted from remote sensing images and raster maps often have irregular boundaries, redundant points, inaccurate positions, and unclear turns due to factors such as image quality, complexity of the surrounding environment, and extraction methods. This study proposes a regularization algorithm for right-angled polygon building outlines with jagged edges. First, the minimum bounding rectangle of the building outline is established and populated with a square grid based on the smallest visible length principle. An overlay analysis is then applied to the grid and original building to extract the turning points of the outline. Finally, the building orientation is used as a reference axis to sort the turning points and reconstruct the simplified building outline. Analysis of the experimental results shows that the proposed simplification method enhances the morphological characteristics of building outlines, such as parallelism and orthogonality, while considering simplification principles, such as the preservation of direction, position, area, and shape of the building. The proposed algorithm provides a new regularization method for building outlines with jagged edges.

Aim: Aging is companied by deteriorations of insulin resistance (IR) and insulin secretion. However, little is known about the roles of aging on different phases of insulin secretion (ISEC); i.e., the first- and second-phase of insulin secretion (FPIS, SPIS) and glucose effectiveness (GE). Methods: Totally 169 individuals (43 men and 126 women) with the similar fasting plasma glucose (FPG: 90 mg/dL) and BMI (men: 23 kg/m2, women 22 kg/m2) were enrolled. IR, FPIS, SPIS, and GE were estimated using our previously developed equations shown below. Pearson correlation analysis was conducted to assess the correlations between age and four diabetes factors (DFs: IR, FPIS, SPIS and GE). The equations that are used to calculate the DF in the present study were built and published by our group. Results: The age of the participants ranged from 18- to 78-year-old. Men had higher FPIS but lower HDL-C levels than women (2.067±0.159, 1.950±0.186 μU/min and 1.130±0.306, 1.348±0.357 mmol/dl, accordingly). The results of Pearson correlation revealed that age was negatively related to IR and GE in both genders (IR: r = -0.39, p < 0.001 for men, r = -0.24, p < 0.003 for women; GE: r = 0.66, p < 0.001 for men, r = 0.78, p < 0.001 for women). In the meanwhile, FPIS was also only found to be negatively correlated with age in female (r = -0.238, p = 0.003). But there was no different with SPIS and age in both of genders. Conclusions: We have found that in Chinese with normal FPG level (90 mg/dl) and body mass index (men: 23 kg/m2, women: 22: kg/m2), age is negatively related to IR and GE in both genders. At the same time, only FPIS was found to be negatively related to age in women. The tightness of their relationships, from the highest to the lowest are, GE, FPIS and IR accordingly. The importance of GE should be re-evaluated. These results should be interpreted with caution because of the small sample size.

Bionic robotic hand can perform many movements similar to human hand. But there is still a significant gap in manipulation between robot and human hand. It is necessary to understand the finger kinematics and motion patterns of human hand to improve the performance of robotic hand. This study aimed to comprehensively investigate normal hand motion patterns by evaluating the kinematics of hand grip and release in healthy individuals. The data corresponding to rapid grip and release were collected from the dominant hand of 22 healthy people by sensory glove. The kinematics of 14 finger joints were analyzed, including the dynamic range of motion (ROM), peak velocity, joint sequence and finger sequence. The results show that the proximal interphalangeal (PIP) joint had a largest dynamic ROM than metacarpophalangeal (MCP) and distal interphalangeal (DIP) joints. Besides, the PIP joint had the highest peak velocity, both in flexion and extension. For joint sequence, the PIP joint moved prior to the DIP or MCP joints during flexion, while extension started in DIP or MCP joints, followed by PIP joint. Regarding the finger sequence, the thumb started to move before four fingers, and stopped moving after the fingers during both grip and release. This study explored the normal motion patterns in hand grip and release, which provided kinematic reference for the design of robotic hand and thus contribute to its development.

The primary cilium plays critical roles in homeostasis and development of neurons. Recent studies demonstrate that cilia length is regulated by the metabolic state of cells, as dictated by processes such as glucose flux and O-GlcNAcylation (OGN). The study of cilia length regulation during neuron development, however, has been an area left largely unexplored. This project aims to elucidate the roles of O-GlcNAc in neuronal development through its regulation of the primary cilium. Here, we present findings suggesting that OGN levels negatively regulate cilia length on differentiated cortical neurons derived from human-induced pluripotent stem cells. In neurons, cilia length increased significantly during neurons maturation (after day 35), while OGN levels began to drop. Long-term perturbation of OGN via drugs, which inhibit or promote its cycling, during neuron development also have varying effects. Diminishing OGN levels increases cilia length until day 25, when neural stem cells expand and undergo early neurogenesis, before causing cell cycle exit defects and multinucleation. Elevating OGN levels induces greater primary cilia assembly but ultimately results in the development of premature neurons, which have higher insulin sensitivity. These results indicate that OGN levels and primary cilia length are jointly critical in proper neuron development and function. Understanding the interplays between these two nutrient sensors, O-GlcNAc and the primary cilium, during neuron development is important in paving connections between dysfunctional nutrient-sensing and early neurological disorders.

This paper focuses on the effect of malondialdehyde-induced oxidative modification (MiOM) on the gel properties of duck myofibrillar proteins (DMPs). DMPs were first prepared and treated with oxidative modification at different concentrations of malondialdehyde (0, 0.5, 2.5, 5.0 and 10.0 mmol/L). The physicochemical changes (carbonyl and free thiol group content) and gel properties (gel whiteness, gel strength, water holding capacity, rheological properties and mi-cro-structural properties) were then investigated. The results showed that the content of protein carbonyl groups increased with increasing MDA oxidation (P<0.05), while the content of free thiol groups decreased significantly (P<0.05). Meanwhile, there was a significant trend of decrease in gel whiteness; the hardness and water-holding capacity of protein gels increased significantly under the oxidation of low concentration of MDA (0-5 mmol/L), while the hardness of gels decreased under the oxidation of high concentration (10 mM). The storage modulus and loss modulus of oxidized DMPs also increased with increasing concentration; moreover, microstructural analysis confirmed that the gels oxidized at low concentrations were more compact and homogeneous in terms of pore size compared to the high concentration or blank group. In conclusion, moderate oxidation of malondialdehyde was beneficial to improve the gel properties of duck; however, excessive oxidation was detrimental to the formation of dense structured gels.

Dams have made great contributions to human society, facilitating flood control, power generation, shipping, agriculture and industry. However, the construction of dams greatly impacts downstream ecological environments and nearby marine areas. To summarize these impacts, this review used recent research to comprehensively analyze how dam construction has affected river hydrology, geomorphology, and ecosystem of downstream reaches globally. Effects of dams on ecosystems occur through reduced river flow, reduced sediment flux, altered water temperature, changed estuary delta, altered composition and distribution of nutrients, altered structure and distribution of phytoplankton populations, caused habitat fragmentation, and blocked migration routes in river sections and adjacent seas. Besides, exploring new reservoir management strategies (including targeted control of dam storage and flushing sediment operations), banning fishing activities, and removing unnecessary dams (obsolete or small dams) are becoming crucial tools for ecosystem restoration.

This article presents, for the first time, the efficacy and curing depth analysis of photo-thermal dual polymerization in metal (Fe) polymer composites for 3D printing of a 3-component (A/B/M) system based on the proposed mechanism of our group, in which the co initiators A and B are Irgacure-369, and charge-transfer complexes (CTC), respectively; and the monomer M is TMPTA filled by Fe. Our formulas show the depth of curing (Zc) is an increasing function of the light intensity, but a decreasing function of the Fe and photoinitiator concentrations. Zc is enhanced by the additive [B] which produces extra thermal radical for polymerization under high temperature. The heat (or temperature) increase in the system has two components : (i) due to the light absorption of Fe filler, and (ii) heat released from the exothermic photopolymerization of the monomer. The heat is transported to the additive (or co-initiator) [B] to produce extra radical R' and enhance the monomer conversion function (CF). The CF has two opposite trends in their time profiles: (i) for small Fe concentration (F), it is a time decaying function; and (ii) for large Fe, it is a time increasing profile. This switching feature predicted by our formula is also justified by our measured data. The Fe filler leads to temperature increase, but also limits the light penetration leading to lower CF and Zc, which could be overcome by the additive initiator [B] in thick polymers. the new finding of optimal Fe for maximal CF and Zc are explored theoretically.

Pneumonia is the leading cause of hospitalization in pediatric patients. Disease severity greatly influences pneumonia progression and adverse health outcomes such as hospital readmission. Hospital readmissions have become a measure of healthcare quality to reduce excess expenditures. The aim of this study was to examine 30-day all-cause readmission rates and evaluate the association between pneumonia severity and readmission among pediatric pneumonia hospitalizations. Using 2018 Nationwide Readmissions Database (NRD), we conducted a cross-sectional study of pediatric hospitalizations for pneumonia. Pneumonia severity was defined by the presence of respiratory failure, sepsis, mechanical ventilation, dependence on long-term supplemental oxygen, and/or respiratory intubation. Outcomes of interest were 30-day all-cause readmission, length of stay, and cost. The rate of 30-day readmission for the total sample was 5.9%, 4.7% for non-severe pneumonia, and 8.7% for severe pneumonia (p&lt;0.01). Among those who were readmitted, hospitalizations for severe pneumonia had a longer length of stay (6.5 vs. 5.4 days, p&lt;0.01) and higher daily cost ($3,246 vs. $2,679, p&lt;0.01) than admissions for non-severe pneumonia. Factors associated with 30-day readmission were pneumonia severity, immunosuppressive conditions, length of stay, and hospital case volume. To reduce potentially preventable readmissions, clinical interventions to improve the disease course and hospital system interventions are necessary.

Consistent calibration and monitoring is a basic prerequisite for providing reliable time series of global and regional sea level variations from altimetry. The precision of sea level measurements and regional biases for six altimeter missions (Jason-1/2/3, Envisat, Saral, Sentinel-3A) is assessed at eleven GNSS-controlled tide gauge stations in the German Bight (SE North Sea) for the period 2002 to 2019. The gauges are partly located at the open water, partly at the coast close to mudflats. The altimetry is extracted at virtual stations with distances from 2 to 24 km from the gauges. The processing is optimized for the region and adjusted for the comparison with instantaneous tide gauges readings. An empirical correction is developed to account for mean height gradients and slight differences of the tidal dynamics between gauge and altimetry which improves the agreement between the two data sets by 15-75%. The precision of the altimeters is depending on location and mission and is shown to be at least 1.8 to 3.7 cm based on an assumed precision of 2 cm for the gauges. The accuracy of the regional mission biases is strongly dependent on the mean sea surface heights near the stations. The most consistent biases are obtained based on the CLS2011 model with mission dependent accuracies from 1.3 to 3.4 cm. Hence, the GNSS-controlled tide gauges operated operationally by WSV might complement the calibration and monitoring activities at dedicated CalVal stations.

This purpose of the study presented in this article is to comparing different service quality measurements between Kano and TRIZ that plays the critical roles in the catering industrial. Data collected from a DINESERV questionnaire comprises service-quality standards to increase customer satisfaction of mobile dining car. Finally, the TRIZ is standardized measure designed to improve the idealization of strategy for selecting the most appropriate service quality model. In addition, the preferences of more than one decision maker are internally aggregated into the TOPSIS procedure. All these things provide several important theoretical and practical implications for developing a successful mobile catering app.

Recent preclinical studies have shown the potential benefits of short-term calorie reduction (SCR) on cancer treatment. In this integrative review, we aimed to identify and synthesize current evidence regarding the feasibility, process, and effects of SCR in cancer patients receiving chemotherapy. PubMed, Cumulative Index to Nursing and Allied Health Literature, Ovid Medline, PsychINFO, and Embase were searched for original research articles using various combinations of Medical Subject Heading terms. Among the 311 articles identified, seven studies met the inclusion criteria. The majority of the reviewed studies was small randomized controlled trials or cohort study with fair quality. The results suggest that SCR is safe and feasible. SCR is typically arranged around the chemotherapy with the duration ranging from 24 to 96 hours. Most studies examined the protective effects of SCR on normal cells during chemotherapy. The evidence supports that SCR had the potential to enhance both physical and psychological wellbeing of patients during chemotherapy. SCR is a cost-effective intervention with great potential. Future well-controlled studies with sufficient sample sizes are needed to examine the full and long-term effects of SCR and its mechanism of action.

Fire behavior of natural rubber latex foam under different thickness conditions(d=1,2and 5cm)were explored though a little of experiments by using the self-built small scale experimental platform. It can be shown that the flame spread law of thermally thin and thermally thickness are different. Natural rubber latex foam with thickness of 2cm show higher fire risk, which value of flame spread rate, maximum flame height, maximum mass loss rate and maximum temperature is 0.00293m/s, 851.875mm, 1.83g/s, 948K,repectively.That may because the thickness of residue formed of thermally thick materials is larger than the thin one, obstructing the contact of the natural rubber latex foam with fresh air .In addition, a special phenomenon is noticed that during the second stage, the bottom unburned zone located in the four edges(thermally thin material) and middle player(thermally thick material).

In recent years, remote sensing technology has been widely used to predict forest stand parameters. In order to compare the effects of different features of remote sensing images and topographic information on the prediction of forest stand parameters, multivariate stepwise regression analysis method was used to build estimation models for important forest stand parameters by using textural and spectral features as well as topographic information of SPOT-5 satellite images in northeastern Heilongjiang Province in China as independent variables. The study results show that the optimal window to predict forest stand parameters using textural features of SPOT-5 satellite image is 9×9; the ability of textural features was better than that of spectral features in terms of predicting forest stand parameters; with the inclusion of topographic information, the accuracy of prediction of all models was improved, of which elevation has the most significant effect. The highest accuracy was achieved when predicting the stand volume (SV) (R²_adj=0.820), followed by basal area (BA) (R²_adj =0.778), accuracy of both above models exceeded 75%. The results show that models combined use of textural, spectral features and topographic information of SPOT-5 images have a good application prospect in predicting forest stand parameters.

In this paper, an improved system to efficiently utilize the low-temperature waste heat (WHUS) from the flue gas of coal-fired power plants is proposed based on heat cascade. The essence of the proposed system is that the waste heat of exhausted flue gas is not only used to preheat air for assisting coal combustion as usual but also to heat up feedwater and the low-pressure steam extraction. Preheated by both the exhaust flue gas in the boiler island and the low-pressure steam extraction in the turbine island, thereby part of the flue gas heat in the air preheater can be saved and introduced to heat the feedwater and the high-temperature condensed water. Consequently, part of the high-pressure steam is saved for further expansion in the steam turbine, which obtains additional net power output. Based on the design data of a typical 1000 MW ultra-supercritical coal-fired power plant in China, in-depth analysis of the energy-saving characteristics of the optimized WHUS and the conventional WHUS is conducted. When the optimized WHUS is adopted in a typical 1000 MW unit, net power output increases by 19.51 MW, exergy efficiency improves to 45.46%, and net annual revenue reaches 4.741 million USD. In terms of the conventional WHUS, these aforementioned performance parameters are only 5.83 MW, 44.80% and 1.244 million USD, respectively. The research of this paper can provide a feasible energy-saving option for coal-fired power plants.

Background Successful treatment for patients with metastatic colorectal cancer who failed to response to first-line treatment has been a challenge due to their low response rate for later-line treatment and poor progression free survival and overall survival. The application of dendritic cell-cytokine-induced killer cells (DC-CIK) immunotherapy combined with conventional treat-ment, either surgical resection or chemotherapy, showed improvement in survivals in first-line treatment for metastatic colorectal cancer. In this retrospective study, we aimed to evaluate the benefit of dendritic cell-cytokine-induced killer cells (DC-CIK) immunotherapy for patient with refractory metastatic colorectal cancer. Methods A total of 20 patients with refractory metastatic colorectal cancer receiving cell-cytokine-induced killer cells (DC-CIK) immunotherapy were enrolled to this study. Among these patients, 11 patients responded to the treatment and the remaining 9 patients did not. All patients were followed for at least one years and the determination of treatment response was mainly based on image study at 6 months after the completion of treatment. Data were analyzed with Kaplan-Meier method and log-rank test. Results The treatment response rate of the study group is 55% (11/20). The median progression free sur-vival (PFS) and median overall survival (OS) of responsive patients was 7 months and 12 months, respectively. The median overall survival of irresponsive patients was 9.5 months. Four responsive patients received subsequent metastectomy or cytoreduction plus hyperthermic in-traperitoneal chemotherapy surgery (CRS + HIPEC). Conclusion DC-CIK cell-based immunotherapy may provide benefits for patients with refractory mCRC with improved response rate and progression free survival.

The structure and expression of exogenous genes in transgenic crops are critical for the target traits. R7569 was a mutant event identified in this study with deletion at the 3' end of cry1Ac gene compared to the transgenic insect-resistant cotton MON531 event with commercial application. R7569 has the same exogenous insertion structure as MON531, but with a deletion in the 3' end of the cry1Ac gene and the terminator region. R7569 has a truncated cry1Ac gene with the length of 2,554 bp, encoding 881 amino acids. The transcription termination site was mainly concentrated downstream of the truncated position and extended 160-270 bp from the truncated position using rapid-amplification of cDNA ends (RACE). The transcript levels of cry1Ac genes of R7569 and MON531 decreased gradually at seedling, bud and bell stages, and the transcript levels of cry1Ac genes of R7569 were significantly higher than those of MON531 in seedling and bud stages, but there was no significant difference in the boll stage. The content of Cry1Ac protein in R7569 gradually decreased with the seedling, bud and boll stage, and the content of Cry1Ac protein in all three periods was higher than that of MON531. The insect resistance assay showed that the resistance levels of R7569 and MON531 were both at the high level, and the corrected mortality rate against bollworms was 99.5% and 95.2%, respectively, and there was no significant difference between them. The LC50 value of R7569 was 0.732ng/g dw, with a slope of 1.654 indicating a high level of resistance to bollworm. In this study, for the first time, we found a partial deletion of the target gene in commercially applied transgenic crops, and the partial deletion of the 3' end of the cry1Ac gene retained a better transcription, expression level and insecticidal activity, which can provide a specific case for the safety evaluation of transgenic crops.

In order to foster a more sustainable and eco-friendly trajectory for the construction industry, while concurrently mitigating environmental pollution and energy inefficiency, it is imperative to cultivate an environmentally conscious building and urban environment. Under the background of carbon peak and carbon neutrality, green building evaluation system (GBRS) has become a research hotspot in the field of green building. This paper systematically summarizes the current research progress based on GBRS, focuses on the current weight and indicators setting, analyzes it with Cite Space software, and puts forward its future development direction. The results show that the weight setting method of green building evaluation system is determined by multidimensional and multi-method. From the perspective of environment, society and economy, the scope of indicators setting is expanding. The green building evaluation system will play a guiding role in green building design, and the evaluation process will continue to be optimized and developed in the direction of intelligence and automation.

The utilization of smart IoT devices, commonly referred to as digital twins, is aimed at the digitalization of human knowledge within aquaculture processes. This involves the incorporation of cutting-edge technologies, including information-based management with big data and modeling, to automate machinery and gain comprehensive insights into the aquaculture environment and fish farm conditions. The ultimate objective is to empower farmers to make informed decisions, furnishing them with objective data to enhance their capacity in monitoring and controlling the various factors impacting fish production. As a result, farming decisions can be fine-tuned to enhance fish health and optimize farm output. In the context of large and modern aquaculture farms, technological innovation becomes imperative to automate processes, minimize labor requirements, and streamline fish feeding operations. Remarkably, the literature currently offers limited discussions on the digital transformation of aquaculture through the application of digital twin methodologies. A prior study underscores the critical influence of factors such as market prices and fish survival rates on the profitability of offshore caging culture. In this study, we embark on an analysis of the prerequisites for establishing a digital twin infrastructure tailored to intelligent fish feeding management. This infrastructure is designed to facilitate the integration of technology and data-driven decision-making, ultimately enhancing the efficiency of fish feeding processes. The proposed architecture for the fish feeding digital twin encompasses various digital twin components, encompassing water quality forecasting, fish population assessment, fish metrics estimation, fish feed prediction, and evaluation of fish feeding intensity. Furthermore, we optimize the daily fish feeding process through reinforcement learning algorithms. Finally, we implement a cloud-based AIoT system that provides the runtime environment for executing digital twins and controlling our intelligent fish feeding machinery. Experimental findings underscore the efficacy of the proposed digital twin system in significantly improving traditional fish feeding processes, notably in terms of reducing food costs and labor requirements.

The transition region is a very thin but most peculiar layer in the solar atmosphere, located between the solar chromosphere and the corona. It is a key region for understanding the coronal heating, the solar eruptions triggering, and the origin of solar winds. Here, the gradients of all physical parameters are very high, including plasma density, ionization degree, temperature, and magnetic fields, etc. Therefore, the transition region should be highly dynamic, such as fast energy releasing and transporting, plasma heating, and even particle accelerating. They include two physical aspects: thermal and non-thermal processes. The thermal processes can be observed from the ultraviolet (UV) and extreme ultraviolet (EUV) emission by multi-wavelength images. The non-thermal processes, however, should be related to radio emissions especially at millimeter wavelengths, and the frequency range should span from several GHz to beyond 300 GHz, and the emission mechanism should be highly related to the magnetic fields and variations. The ultra-wide broadband spectral observations at millimeter wavelengths with high spectral resolutions may provide rich dynamic information about the transition region, such as non-thermal energy release and transmission, the flows of plasma and energetic particles, the magnetic fields and their variations, the generation and transportation of various waves, and the formation and evolution of the source regions of solar eruptions. Here, we discussed the spectral characteristics of millimeter-wave emission from the transition region and proposed a new conception of ultra-wide broadband millimeter-wave spectrometers to observe them.

In order to assess the range of impact of thermal wastewater discharge from the third Nuclear Power Plant (NP_No.3) on the local ecosystem, a three-dimensional ocean model (MITgcm) driven by tidal and climatological forcings is employed to study the present work. Tides and daily wind forcings are incorporated into the MITgcm model to examine their effects on the thermal plume and the water circulation in Nan Wan Bay. The model results reveal that the thermal plume is most likely to disperse to the southwest in summer; it is unlikely to drift to the southeast or northeast because of the presence of gentle southwesterly monsoon. In winter, the thermal plume is most likely to be directed to the southwest but barely visible in the northeast or southeast directions because of prevailing northeasterly monsoon. Additionally, it is worth emphasizing that strong tidal currents generate a pair of counter-rotating eddies that significantly dominate the dispersal of the thermal plume. However, seasonal monsoons also play an essential role in modifying the plume’s direction and dispersion. The model results reveal that the flow field and thermal plume agree well with observational data.

SETD7 is a member of the SET domain-containing lysine methyltransferase family and is a crucial component in the development and spread of a number of human cancers. However, the specific function of the SETD7 gene in ovarian cancer (OC) is still unclear. The purpose of this research was to elucidate the expression and role of SETD7 in OC. In comparison to normal controls, OC tissues (83%, 73/88) and cell lines exhibited higher protein levels of SETD7 (p < 0.001). High SETD7 protein levels were substantially correlated with M category (p = 0.019) and FIGO stage (p = 0.021). Furthermore, the high mRNA levels of SETD7 were correlated to poor progression-free survival (PFS) in all patients and serous patients with OC (p < 0.05). Importantly, the biological function experiments showed that SETD7 behaved as an oncogene in OC by dramatically facilitating the proliferation and migration of A2780 and SKOV3 cells. Additionally, SETD7 might promote cell migration via accelerating the EMT process in A2780 and SKOV3 cells. Our findings reveal that SETD7 may be a valuable molecular marker for identifying and anticipating the development of OC.

Background: We screened key genes involved in the dedifferentiation process of thyroid cancer by analyzing differentially expressed genes in anaplastic thyroid carcinoma (ATC) using Gene Expression Omnibus (GEO) database. Methods: We analyzed differentially expressed genes in ATC from GEO database and constructed a co-expression network using Weighted Gene Co-expression Network Analysis (WGCNA) . Cytoscape was used to calculate top ten key genes based on their gene scores. DEPDC1 was selected as interest gene for further validation, including examination of its prognostic relationship with thyroid cancer, correlation analysis with thyroid differentiation markers, immune cell infiltration, and tumor microenvironment. The impact of DEPDC1 on cancer cell migration, invasion, and proliferation was validated through downregulation and overexpression of DEPDC1 gene in thyroid cancer cell lines c643 and BCPAP. Results: We identified top 10 key genes in ATC: AURKA, TPX2, RACGAP1, MELK, DLGAP5, DEPDC1, KIF2C, NCAPG, CCNB1, and PBK. DEPDC1 showed a strong correlation with the prognosis of thyroid cancer. The odds ratio (OR) for overall survival was 3.5 (P=0.016) in individuals with high DEPDC1 expression, and the OR for disease-free survival was 2.6 (P=0.003). Additionally, the analysis revealed a significant negative correlation between the expression of DEPDC1 and thyroid differentiation markers. Gene Ontology enrichment analysis demonstrated that DEPDC1 co-expressed genes were enriched in cellular processes, cell cycle pathways, and dynamic protein groups. Matrix and immune scoring indicated tumor microenvironment and immune scores were associated with DEPDC1 expression. TIMER2.0 online analysis revealed a strong correlation between DEPDC1 expression and immune cell infiltration in papillary thyroid carcinoma. After downregulation of DEPDC1 expression, the invasion, migration, and proliferation abilities of tumor cells were significantly reduced. Conversely, overexpression of DEPDC1 exhibited the opposite effect. Conclusion: DEPDC1, a newly identified dedifferentiation gene in thyroid cancer, inversely correlated with the degree of differentiation. High expression of DEPDC1 promotes cancer progression and leads to poor prognosis in thyroid cancer.

In view of the limitations of the existing eccentricity error separation method of the rotary table, an eccentricity error separation method based on the phase feature of the moiré signal of single reading head is proposed herein. A grating pair transmission model is established based on the analysis of the principle of the rotary table, thereby the influence of eccentricity error on the phase feature of the moiré signal in the rotation course of the rotary table is clarified, and the corresponding model between the phase feature spectral components and the eccentricity error is established. The verification experiments of the proposed method are carried out based on the laboratory-made circuit system. After verifying the accuracy of the data acquisition of the laboratory-made circuit board, the verification experiments of the eccentricity error separation effect of the proposed method are carried out. The experimental data are compared with those of the traditional method and the results show that the error between the two methods is 2.34μm and the relative error is 2.3%.

Constructed wetlands (CWs) is a kind of green environmental protection technology, which is widely used in sewage treatment. The traditional CWs is faced with the problem of low treatment effect of high concentration sewage. In recent years, biochar, as a new type of adsorption material, has been used in CWs because of its advantages of large specific surface area, strong adsorption capacity and wide material sources. This paper systematically summarized the characteristics of biochar and the preparation of biochar by studying the changes of microorganisms added to CWs, and compared the effects of different treatment methods coupled with biochar on the treatment performance of CWs, the effects of biochar coupled with CWs on enzyme activity, functional genes, metabolites and microbial communities were investigated. This review summarizes how different preparation methods affect the properties of biochar and how these biochar cause changes in the microorganisms added to CWs.

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

The guided ultrasonic wave (GUW) is extensively employed in non-destructive testing (NDT) for the purpose of detecting defects in aerospace vehicles, oil pipelines and mechanical equipment. The filtration of GUW signals, which often contain substantial environmental noise, is a crucial procedure in signal processing. This paper presents a novel denoising approach that combines Variational Mode Decomposition (VMD) with an enhanced Singular Value Decomposition (SVD). The VMD method is employed to preprocess the initial signal, thereby segregating the signal component from the noise component. Subsequently, the SampEn-SVD (Sample Entropy-SVD) method is utilized to extract the effective component from the VMD-preprocessed noise component. Finally, the VMD-preprocessed signal component and the SampEn-SVD-processed effective component are combined to yield the resultant signal, which effectively filters out the noise. The efficacy of this integrated denoising approach is substantiated through the examination of experimental signals. Furthermore, a comparative analysis is conducted to evaluate the efficacy of this method in relation to other denoising techniques. The results indicate that the SampEn-SVD method yields a superior signal-to-noise ratio (SNR) when processing the GUW signal transmitted through the steel strand. Moreover, the denoising procedure significantly reduces the discretization of characteristic parameters in the signal waveform, thereby addressing the issue of inadequate reproducibility in testing outcomes. Consequently, the denoised signal exhibits high fidelity and demonstrates a strong correlation between its combined eigenvector and strand stress.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our artificial intelligent image recognition system, AIIRS, could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Despite their anti-icing ability, hydrophobic coatings have the disadvantages of easy falling off and poor wear resistance, resulting in insufficient durability of ice/snow melting. To improve the surface stability and durability of superhydrophobic coatings, nanoparticle/epoxy coatings were prepared with three types of nanoparticles, two types of dispersion methods, three types of application methods and two types of introduction methods of epoxy resin. Water contact angles, ice adhesion force and icing rate of asphalt concrete coated with hydrophobic coatings were tested. The molecular structures of coatings were analyzed by Fourier transform infrared spectroscopy. The surface morphology of hydrophobic coatings was observed using Scanning electron microscopy. Results indicated that nano-ZnO, TiO2 and SiO2 particles can be modified into hydrophobicity by stearic acid. The hydrophobic coating could improve the hydrophobicity of concrete, reduce the adhesion strength of ice and asphalt concrete and delay the beginning icing time. Moreover, The dosages of stearic acid, nanoparticle and epoxy resin need to be in a certain range to ensure the best hydrophobicity and durability of coatings.

The assessment and prediction of drought risk under future climate change and land use land cover (LULC) scenarios is critically important for drought prevention and mitigation, as it enables a clearer understanding of potential shifts in drought patterns. The primary aim of this study is to evaluate sub-seasonal and seasonal meteorological and hydrological drought hazards across the Yellow River Basin (YRB) under projected future climate conditions and LULC patterns. The BCC-CSM1-1 climate model projections from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset are utilized to represent future climate for 2025-2060 under RCP 4.5 and 8.5 scenarios. The CA-Markov model is employed to predict future LULC distributions. Meteorological and hydrological drought risks across different YRB zones are evaluated through a copula-based risk assessment approach, based on the joint probability distribution of drought duration and severity. The results indicate that sub-seasonal meteorological and hydrological droughts will likely be the primary concern moving forward. Specifically, the upper YRB (zones A, B, C) exhibits greater vulnerability to sub-seasonal meteorological drought, while the Loess Plateau (zones C, E) shows higher susceptibility to sub-seasonal hydrological drought. Moreover, zone F in the downstream region may experience increased seasonal hydrological drought risk due to projected urban expansion in the middle and lower portions of the YRB.

Our image recognition system mainly judges whether the left upper limb in the image is the left upper limb or the right upper limb through our deep learning model in the image. The doctor then could give the correct surgical position. From the experimental results, it could be found that the precision rate and recall rate of the intelligent image recognition system proposed in this paper for preventing the upper limb dislocation surgery could reach 98% and 93%, respectively. It proved that our intelligent image recognition system could indeed assist orthopedic surgeons to prevent the occurrence of left and right dislocation in upper limb surgery. At the same time, this paper also completes the IRB application approval through the prototype experimental results and will conduct the second phase of human trials in the future. It showed that the research results of this paper will be of great benefit and research value to upper limb orthopedic surgery.

Alternative splicing can produce transcripts that affect cancer development and shows potential for cancer diagnosis and treatment. However, intron retention (IR), a type of alternative splicing, has been less systematically studied in cancer biology research. Here, we generated a pan-cancer IR landscape for more than 10,000 samples across 33 cancer types from The Cancer Genome Atlas (TCGA). We characterized differentially retained introns between tumor and normal samples and identified retained introns associated with survival. We discovered 988 differentially retained introns in 14 cancers, some of which demonstrated diagnostic potential in multiple cancer types. We also inferred a large number of prognosis-related introns in 33 cancer types, and the associated genes included well-known cancer hallmarks such as angiogenesis, metastasis, and DNA mutations. Notably, we discovered a novel intron retention event inside 5′UTR of STN1 that is associated with the survival of lung cancer patients. The retained intron reduces translation efficiency by producing upstream open reading frames (uORFs) and thereby inhibits colony formation and cell migration of lung cancer cells. Besides, the IR-based prognostic model achieved good stratification on certain cancers, as illustrated in acute myeloid leukemia. Taken together, we performed a comprehensive IR survey at a pan-cancer level, and the results implied that IR has the potential to be diagnostic and prognostic cancer biomarkers, as well as new drug targets.

Foliage-feeding fall armyworm (Spodoptera frugiperda) and root-feeding western corn rootworm (Diabrotica virgifera virgifera) are maize (Zea mays L.) pests that cause significant yield losses. Jasmonic acid (JA) play pivotal defense role against insects. 12-oxo-phytodienoic acid (12-OPDA) is converted into JA by peroxisome-localized OPDA reductases (OPR). However, little is known about the physiological functions of cytoplasmic OPRs. Here, we show that disruption of ZmOPR2 reduced wound-induced JA production and defense against FAW while accumulating more JA catabolites. Overexpression of ZmOPR2 in Arabidopsis enhanced JA production and defense against beet armyworm (Spodoptera exigua). In addition, lox10opr2 double mutants were more susceptible than either single mutant, suggesting that ZmOPR2 and ZmLOX10 uniquely and additively contributed to defense. In contrast to the defensive role of ZmOPR2 and ZmLOX10 in leaves, single mutants did not display any alteration in root herbivory defense against WCR. Feeding on lox10opr2 double mutants resulted in increased WCR mortality associated with greater herbivory-induced production of insecticidal death acids and ketols. Thus, ZmOPR2 and ZmLOX10 cooperatively inhibit synthesis of these metabolites during herbivory by WCR. We conclude that ZmOPR2 and ZmLOX10 regulate JA-mediated resistance in leaves against FAW while suppressing insecticidal oxylipin synthesis in roots during WCR infestation.

The study investigated the relationships between sarcopenia, frailty, and related factors in hemodialysis patients with chronic kidney disease. A prospective cross-sectional study with convenience sampling was conducted between August 2021 and February 2022 at a hospital-affiliated hemodialysis center. Ninety-six hemodialysis patients participated in the study. Quantitative data were collected with structured interviews. Sarcopenia was determined with a rapid screening tool. Frailty was determined with the Rockwood clinical frailty score. Descriptive analysis, Person Correlations, and Linear regression analysis were used to evaluate the associations between frailty, sarcopenia, and health-related factors in hemodialysis patients. The mean age of the participants was 65.4 11.5 years, with an average of 95.0 77.5 months of hemodialysis. The most common comorbidity was hypertension (72.9%), followed by diabetes mellitus (39.6%) and cardiovascular health problems (35.4%). A significant difference in frailty between sarcopenia patients and a healthy population (X2 =9.51, p &lt;.001) was identified. There was a strong negative correlation (r= −.853, p&lt;.001) between sarcopenia and frailty, while moderate correlations between sarcopenia and frailty in sarcopenia patients (r= −.66, p&lt;.001) and a healthy population (r= −.58, p&lt;.001) were observed. Age, body weight before dialysis, and hand grip strength were found to be potential predictors of sarcopenia and frailty. Left calf circumference was significantly associated with sarcopenia (ß= −.128, p = .049). Age, body weight before dialysis, and hand grip strength are potential predictors of sarcopenia and frailty in hemodialysis patients with chronic kidney disease. Comorbidities, which may be preventable, are common in this population.

Multi-source image registration often suffered from great radiation and geometric differences. Specifically, gray scale and texture from similar landforms in different source images often show significantly different visual features. And these differences disturb the corresponding point extraction in the following image registration process. Considering that edges between heterogeneous images can provide homogeneous information and more consistent features can be extracted based on image edges, an edge consistency radiation-change insensitive feature transform (EC-RIFT) method is proposed in this paper. Firstly, the noise and texture interference are reduced by preprocessing according to the image characteristics. Secondly, image edges are extracted based on phase congruency, and an orthogonal Log-Gabor filter is performed to replace the global algorithm. Finally, the descriptors are built with logarithmic partition of the feature point neighborhood, which improves the robustness of descriptors. Comparative experiments on datasets containing multi-source remote sensing image pairs show that the proposed EC-RIFT method outperforms other registration methods in terms of precision and effectiveness.

Extracting railway tracks is crucial for creating electronic railway maps. Traditional methods require significant manual labor and resources, while existing neural networks have limitations in efficiency and precision. To address these challenges, a railway track extraction method using an improved DeepLabV3+ model is proposed, which incorporates several key enhancements. Firstly, the encoder part of the method utilizes the lightweight network MobileNetV3 as the backbone extraction network for DeepLabV3+. Secondly, the decoder part adopts the lightweight universal upsampling operator CARAFE for upsampling. Lastly, to address any potential extraction errors, morphological algorithms are applied to optimize the extraction results. Additionally, a dedicated railway track segmentation dataset is created to train and evaluate the proposed method. The experimental results demonstrate that the model achieves impressive performance on the railway track segmentation dataset and DeepGlobe dataset. The MIoU scores are 88.93% and 84.72%, with Recall values of 89.02% and 86.96%. Moreover, the overall accuracy stands at 97.69% and 94.84%. The algorithm's operation time is about 5% lower in comparison to the original network. Furthermore, the morphological algorithm effectively eliminates errors like holes and spots. These findings indicate the model's accuracy, efficiency, and the enhancement brought by the morphological algorithm in error elimination.

Carbon dots have received much attention due to their unique physicochemical properties and diverse applications in bioimaging, optoelectronic devices, catalysis, and agriculture. Here in this work, we report a simple hydrothermal synthesis of nitrogen and phosphorus-doped carbon dots (N, P-CDs). The optical and physical properties of the synthesized N, P-CDs were analyzed using systematical spectroscopy and electrical characterization. The synthesized N, P-CDs show strong photoluminescence at 626 nm and demonstrate high stability under UV light and other conditions. Moreover, we incorporate the synthesized N, P-CDs into water spinach by root spraying and leaf spraying. It was found that N, P-CDs could effectively promote the growth of water spinach by increasing the photosynthetic rate, and the content of total phenols and anthocyanins in water spinach

Zero-dimensional (0D) tin halide perovskites feature extraordinary properties, such as broadband emission, high photoluminescence quantum yield, and self-absorption-free characteristics. The innovation of synthesis approaches for high-quality 0D tin halide perovskites has facilitated the flourishing development of perovskite-based optoelectronic devices in recent years. However, discovering an effective strategy to further enhance their emission efficiency remains a considerable challenge. Herein, we report a unique strategy employing rapid heat treatment to attain efficient self-trapped exciton (STE) emission in Cs4SnBr6 zero-dimensional perovskite. Compared to the pristine Cs4SnBr6, rapid thermal treatment (RTT) at 200°C for a duration of 120 seconds results in an augmented STE emission with photoluminescence (PL) quantum yield rising from an initial 50.1% to a substantial 64.7%. Temperature-dependent PL spectra analysis, Raman spectra, and PL decay traces reveal that the PL improvement is attributed to the appropriate electron-phonon coupling as well as the increased binding energies of STEs induced by the RTT. Our findings open up a new avenue for efficient luminescent 0D tin-halide perovskites toward the development of efficient optoelectronic devices based on 0D perovskites.

Eugenol is a widely used fishery anaesthetic. This study investigated the effects of various concentrations of eugenol on blood physiological and biochemical indexes, and muscle flavor, in crucian carp (Carassius auratus). To determine the appropriate concentration of eugenol anesthetic for use in crucian carp transportation and production operations, we evaluated seven anaesthesia groups of 20, 30, 40, 50, 60, 70 and 80 mg/L and one control group (without eugenol) to determine the effects on blood physiological and biochemical indexes, and muscle flavor. The red blood cells and platelets of crucian carp decreased significantly (P<0.05) with eugenol treatment. With increasing eugenol concentration, the white blood cells and hemoglobin did not change significantly, whereas lactate dehydrogenase, alkaline phosphatase, alanine aminotransferase and aspartate aminotransferase increased significantly (P<0.05). The content of phosphorus, magnesium and sodium increased after anaesthesia, whereas the content of potassium decreased with increasing eugenol concentration. After anaesthesia, the content of albumin and total protein in the serum decreased with increasing eugenol concentration (P<0.05); triglyceride first increased and subsequently decreased (P<0.05); blood glucose content first increased and then decreased (P<0.05); and no significant difference was observed in total cholesterol content (P>0.05). No significant difference was observed in muscle glycogen and liver glycogen content after eugenol anaesthesia (P>0.05). The eugenol-based anaesthesia test did not indicate major liver histomorphological effects, but the very small number of gill sheet edema cases observed requires further study. Analysis of electronic nose data indicated that eugenol treatment affected the flavor of the fish. The anaesthesia concentration of 20–80 mg/L had little effect on the physiology and biochemistry of crucian carp, thus providing a reference for the application of eugenol in crucian carp transportation and experimental research.

GNSS time series prediction plays a significant role in monitoring crustal plate motion, landslide detection, and maintenance of the global coordinate framework. Long Short-Term Memory (LSTM), a deep learning model has been widely applied in the field of high-precision time series prediction especially when combined with Variational Mode Decomposition (VMD) to form the VMD-LSTM hybrid model. To further improve the prediction accuracy of the VMD-LSTM model, this paper proposes a dual variational modal decomposition long short-term memory (DVMD-LSTM) model to effectively handle the noise in GNSS time series prediction. This model extracts fluctuation features from the residual terms obtained after VMD decomposition to reduce the prediction errors associated with residual terms in the VMD-LSTM model. Daily E, N, and U coordinate data recorded at multiple GNSS stations between 2000 and 2022 are used to validate the performance of the proposed DVMD-LSTM model. The experimental results demonstrate that compared to the VMD-LSTM model, the DVMD-LSTM model achieves significant improvements in prediction performance across all measurement stations. The average RMSE is reduced by 9.86%, and the average MAE is reduced by 9.44%. Furthermore, the average accuracy of the optimal noise model for the predicted results is improved by 36.50%, and the average speed accuracy of the predicted results is enhanced by 33.02%. These findings collectively attest to the superior predictive capabilities of the DVMD-LSTM model, thereby enhancing the reliability of the predicted results.

In recent years, with the rapid development of technology, artificial intelligence(AI) security issues represented by adversarial sample attack have aroused widespread concern in society. Adversarial samples are often generated by surrogate models and then transfer to attack the target model, and most AI models in real-world scenarios belong to black boxes, thus transferability becomes a key factor to measure the quality of adversarial samples. The traditional method relies on the decision boundary of the classifier and takes the boundary crossing as the only judgment metric without considering the probability distribution of the sample itself, which results in an irregular way of adding perturbations to the adversarial sample, an unclear path of generation, and a lack of transferability and interpretability. In the probabilistic generative model, after learning the probability distribution of the samples, a random term can be added to the sampling to gradually transform the noise into a new independent and identically distributed sample. Inspired by this idea, we believe that by removing the random term, the adversarial sample generation process can be regarded as static sampling of the probabilistic generative model, which guides the adversarial samples out of the original probability distribution and into the target probability distribution, and helps to improve transferability and interpretability. Therefore, we propose a Score Matching-Based Attack(SMBA) method to perform the adversarial sample attacks by manipulating the probability distribution of the samples, which can show good transferability in the face of different datasets and models, and give reasonable explanations from the perspective of mathematical theory and feature space. In conclusion, our research establishes a bridge between probabilistic generative models and adversarial samples, provides a new entry angle for the study of adversarial samples, and brings new thinking to AI security.

Oil-tea (Camellia oleifera) is a woody oil crop whose nectar includes galactose derivatives that are toxic to honey bees. Interestingly, some mining bees of the genus Andrena can entirely live on nectar (and pollen) of oil tea and are able to metabolize these galactose derivatives. We present the first next-generation genomes for five and one Andrena species that are respectively specialized and non-specialized oil-tea pollinators, and combining with published genomes of six other Andrena species which did not visit oil-tea, we performed molecular evolution analyses on genes involved in metabolism of galactose derivatives. Six genes (NAGA, NAGA-like, galM, galK, galT, and galE) involved in galactose derivatives metabolism were identified in the five oil-tea specialized species, but only five (with the exception of NAGA-like) were discovered in the other Andrena species. Molecular evolution analyses revealed that NAGA-like, galK and galT in oil-tea specialized species appeared under positive selection. RNASeq analyses showed that NAGA-like, galK, and galT were significantly up-regulated in the specialized pollinator A. camellia compared to the non-specialized pollinator A. chekiangensis. Our study demonstrated that the genes NAGA-like, galK, and galT had played an important role in the evolutionary adaptation of the oil-tea specialized Andrena species.

Elders have a higher rate of return visits to the emergency department (ED) than other patients. It is critical to understand the risk factors for return visits to the ED by elders. The aim of this study was to determine the factors associated with return visits to the ED by elders. This study retrospectively reviewed the hospital charts of elders who return visits to the ED within 72 hours after discharge. The risk factors identified in the Triage Risk Screening Tool were applied in this study. Of the elders discharged from the ED, 8.64% made a return visit to the ED within 72 hours. The highest revisit rate occurred within 24 hours after discharge. Factors associated with return ED visits within 24 hours by elders were difficulty walking and having discharge care needs. Factors associated with ED return visits within 24–48 hours were cognitive impairment and polypharmacy. Difficulty walking, having discharge care needs and hospitalization within the past 120 days were associated with return visits made within 48–72 hours following discharge. Identifying the reasons for return visits to the ED and providing a continuous review of geriatric assessment and discharge planning could reduce unnecessary revisits.

Catalyst with high catalytic activity and good stability are desirable in the electrocatalytic oxidation of glucose. Herein, Pt concave nanocubes with high-index facets (HIFs) supported by carbon black (Pt CNC/CB) are prepared through a hydrothermal method. The experimental results demonstrate that the peak current densities in different potential regions on the Pt CNC/CB anode are 0.22, 0.20, and 0.60 mA cm−2, respectively. The glucose oxidation reaction shows superior performances in basic and neutral conditions than in acid conditions. Better stability is achieved by Pt CNC/CB than Pt concave nanocubes (Pt CNCs). Abundant surface defects with low-coordinated atom numbers, such as the steps, kinks, and edges, are served as active sites in the electrocatalytic oxidation of glucose. With the addition of carbon black, the catalytic activity can be improved by facilitating the full exposure of the active surface defects on the HIFs of Pt CNCs. Moreover, to address the aggregation of Pt CNCs, caused by the high surface energy of HIFs, the introduction of carbon material is an effective way to preserve the HIFs, and thus enhance the stability of the catalyst. Hence, the prepared Pt CNC/CB electrocatalyst has great potential to be applied in the electrooxidation of glucose.

Purpose: To construct a hidden Markov model (HMM) for vigilance assessment to improve the real-time performance and accuracy of current vigilance measurement. Methods: ECG signal was collected by sensors, while the noise and baseline drift was eliminated from the original ECG signal. 10 volunteers were randomly selected. Their heart rate variability (HRV) were measured and trained parameters of the modified Hidden Markov model for vigilance assessment. Then, these data were collected to optimize using the Baum-Welch algorithm and obtained the state transition probability matrix A ̂ and the observation probability matrix B ̂. Finally, the data of three volunteers with different transition patterns of mental state were selected randomly and used the Viterbi algorithm to find the optimal state, which compared with the actual state. Results: The constructed vigilance assessment model had a high accuracy rate the accuracy rate of data prediction for these three volunteers exceeded 80%. Conclusion: The Hidden Markov model for vigilance assessment can accurately predict the vigilance level and indicate broad application prospects.

This paper reports a new global Mittag-Leffler synchronization criterion with regard to fractional-order hyper-chaotic financial systems by designing the suitable impulsive control and the state feedback controller. The significance of this impulsive synchronization lies in the fact that the backward economic system can synchronize asymptotically with the advanced economic system under the effective impulse macroeconomic management means. Matlab LMI-toolbox is utilized to deduce the feasible solution in numerical example, which shows the effectiveness of the proposed methods. It is worth mentioning that the LMI-based criterion usually requires the activation function of the system to be Lipschitz, but the activation function in this paper is fixed and truly nonlinear, which cannot be assumed to be Lipschitz continuous. This is another mathematical difficulty overcome in this paper.

During the Covid-19 pandemic in Taiwan, analytical tools of PEST (political, economic, social-cultural, and technological), SWOT (strength, weakness, opportunity, threat), nine building blocks of a business model canvas, and knowledge management were combined to develop a theoretical framework, and used to assess business, smart and sustainable management of two case companies: Tung Sheng Company Limited and its subsidiary, Strong Basic Enterprise Limited. A heuristic inquiry research design was adopted. In addition to secondary data from the two case companies, major top managers were interviewed to reveal constructive questions about the existing business models and to re-interpret strategy. The results showed that case companies own capabilities of R &amp; D (research and development) as a foundation to further apply new smart ICT (information and communication technology) and execute green manufacturing. Additionally, strong key partnerships are used to diversify business investment for leveraging on limited resources given current insufficient qualified employees. Resilient practices adopted new and green technology to help mitigate the negative impacts of the Covid-19 pandemic. This study provides a useful framework and practical information about how to examine business models, smart and sustainable management processes of the two case companies and to make adjustments in strategies for the future.

A partial aperture onboard calibration method can solve the onboard calibration problems of some large aperture remote sensors, which is of great significance for the development trend of increasingly large apertures in optical remote sensors. In this paper, the solar diffuser reflectance degradation monitor (SDRDM) in the onboard calibration assembly (CA) of the FengYun-4 (FY-4) advanced geostationary radiance imager (AGRI) is used as the reference radiometer for measuring the partial aperture factor (PAF) for the AGRI onboard calibration. First, the linear response count variation relationship between the two is established under the same radiance source input. Then, according to the known bidirectional reflection distribution function (BRDF) of the solar diffuser (SD) in the CA, the relative reflectance ratio coefficient between the AGRI observation direction and the SDRDM observation direction is calculated. On this basis, the response count value of the AGRI and the SDRDM is used to realize the high-precision measurement of the PAF of the AGRI B1 ~ B3 bands by simulating the AGRI onboard calibration measurement under the illumination of a solar simulator in the laboratory. According to the determination process of the relevant parameters of the PAF, the measurement uncertainty of the PAF is analyzed; this uncertainty is better than 2.04% and provides an important reference for the evaluation of the onboard absolute radiometric calibration uncertainty after launch.

The South-to-North Water Transfer Jiangsu Water Supply Area (JWSA) is a mega inter-basin water transfer area (water source) that provides water resources from JiangHuai, combines drainage and flooding management, and regulates nearby rivers and lakes. Analyzing the spatiotemporal soil moisture dynamics in the area will inform agricultural drought and flood disaster assessment and early warning studies. Therefore, we evaluated the quality of European Space Agency Climate Change Initiative Soil moisture (ESA CCI_SM) data in the South-North Water Transfer JWSA. Then, we used ensemble empirical modal decomposition, Mann-Kendall tests, and regression analysis to study the spatiotemporal variation in soil moisture for the past 29 years. The CCI _SM data showed a high correlation with local soil measurements at nine sites. We then analyzed the CCI_SM data from three pumping stations (the Gaogang, Hongze, and Liushan stations) in the South-North Water Transfer JWSA. These stations had similar periodic characteristics of soil moisture, with significant periodic fluctuations around 3.1 d. The overall soil moisture at the three typical pumping stations showed an increasing trend. We then investigated whether there were abrupt soil moisture changes at each station. The spatial distribution of soil moisture in the South-North Water Transfer JWSA was characterized by “dry north and wet south”, with higher soil moisture in winter, followed by autumn, and low soil moisture in spring and summer. Although the linear trend of soil moisture in the South-North Water Transfer JWSA varied in significance, the overall soil moisture in the JWSA has increased over the past 29 years. The areas with significantly enhanced soil moisture are mainly distributed in the Yangzhou and Huai'an areas in the southeastern part of the study area. The areas with significantly decreased soil moisture are small in size and mainly located in northern Xuzhou.

Heavy metals contamination in groundwater often occurs in various industrial processes. Stud-ies have confirmed that polysulfide could reduce hexavalent chromium to trivalent chromium, achieving the effect of in-situ stabilization. For other heavy metals contamination in groundwa-ter, whether polysulfide also had a stabilizing ability to achieve in-situ remediation. This re-search focused on heavy metals except for chromium that often contaminated in groundwater, including lead, nickel, zinc, copper, and cadmium to explore the feasibility of using calcium polysulfide (CaSx) as an in-situ stabilization technology for these heavy metals contamination groundwater. Results showed that CaSx had a great removal efficiency for heavy metals lead, nickel, zinc, copper, and cadmium. However, for nickel, zinc, copper and cadmium, when CaSx was added excessively, complexes would be formed, causing the result of re-dissolve and this would also reduce the removal efficiency. Since it is difficult to accurately control the dosage of agents for in-situ groundwater remediation, the concentration of re-dissolved nickel, zinc, cop-per, and cadmium may not be able to meet the groundwater control standards. CaSx had high lead removal efficiency, and it would not cause re-dissolution due to excessive CaSx dosing. CaSx can be used as an in-situ stabilization technique for lead contaminated groundwater.

CO₂ enhanced oil recovery (EOR) has been proven its capability to explore the unconventional tight oil reservoirs and potential for geological carbon storage. Meanwhile, the extremely low permeability pores exaggerate the difficulty CO₂ EOR and geological storage processing in the actual field. This paper initiates the ultrasonic-assisted approach to facilitate the oil-gas miscibility development and finally contribute to unlock more tight oils. First, the physical properties of crude oil with and without ultrasonic treatments were experimentally analysed through gas chromatography (GC), Fourier-transform infrared spectroscopy (FTIR) and viscometer. Second, the oil-gas minimum miscibility pressures (MMPs) were measured from the slim-tube test and the miscibility developments with and without ultrasonic treatments were interpreted from the mixing-cell method. Third, the nuclear-magnetic resonance (NMR) assisted coreflood tests were conducted to physically model the recovery process in porous media and directly obtain the recovery factor. Basically, the ultrasonic treatment (40KHz and 200W for 8 hours) was found to substantially change the oil properties, with viscosity (at 60°C) reduced from 4.1 to 2.8mPa·s, contents of resin and asphaltene decreased from 27.94% and 6.03% to 14.2% and 3.79%, respectively. The FTIR spectrum shows the unsaturated C-H bond, C-O bond and C≡C bond in macromolecules were broken from ultrasonic, which caused the macromolecules (e.g., resin and asphaltenes) to be decomposed into smaller carbon-number molecules. Accordingly, the MMP was determined to be reduced from 15.8 to 14.9MPa from the slim-tube test and the oil recovery factor increased by over 10%. This study reveals the mechanisms of ultrasonic-assisted CO₂ miscible EOR in producing tight oils.

Patients with lean NAFLD make up an increasing subset of liver diseases. The association between lean NAFLD and feutin-A, which serves as a hepatokine and adipokine, has never been examined. Our study aimed to explore the association of serum fetuin-A among lean and nonlean patients. The study comprised 606 adults from the community, stratified into lean or nonlean (BMI </≥ 24 kg/m2) and NAFLD or non-NAFLD (scoring of ultrasonographic fatty liver indicator, US-FLI ≥ 2/<2). Multivariate logistic regression analyses were performed to estimate the odds ratio of having NAFLD among the tertiles of fetuin-A after adjustment. The least square means were computed by general linear models to estimate marginal means of the serum fetuin-A concentrations in relation to the NAFLD groups. The OR of having NAFLD for the highest versus the lowest tertile of fetuin-A was 2.62 (95% CI: 1.72-3.98; P for trend<0.001). Stratifying by BMI, the OR of having lean NAFLD for the highest versus the lowest tertile of fetuin-A was 2.09 (95% CI: 1.09-3.98; P for trend 0.026), while nonlean NAFLD had no significant association with the fetuin-A gradient after adjustments. Fetuin-A was positively associated with lean NAFLD after adjusting for central obesity and insulin resistance.

Karst wetlands are being seriously damaged, and protecting it has become an important matter. Karst vegetation is the essential component of wetland and plays an important role in in the ecological functions of wetland ecosystems. Classifying karst vegetation is important for karst wetlands protection and management. This paper addressed to classify karst vegetation in Huixian National Wetland Park, located in China using the improved SegNet Deep-Learning Algorithm and UAV images. This study proposed a method to fuse single-class SegNet models using the maximum probability algorithm for karst vegetation classification, and compared with object-based RF classification and multi-class SegNet classification, respectively. This paper evaluated the performance of multi-class SegNet model and fusion of single-class SegNet model with different EPOCH values for mapping karst vegetation. A new optimized post-classification algorithm was proposed to eliminate the stitching traces caused by SegNet model prediction. The specific conclusions of this paper include the followings:(1) fusion of four single-class SegNet models produced better classification for karst wetland vegetation than multi-class SegNet model, and achieved the highest overall classification accuracy (87.34%); (2) The optimized post-classification algorithm was able to improve prediction accuracy of SegNet model, and it could eliminate splicing traces; (3) The karst wetland vegetation classifications produced by single-class SegNet model outperformed multi-class SegNet model, and improved classification accuracy(F1-Score) between 10%~25%;(4)The EPCOH values and textural feature important impact on karst wetland vegetation classifications. The SegNet model with EPCOH 15 achieved greater classification accuracy(F1-Score) than the model with EPOCH 5 or 10. The textural feature improved improves the capability of the SegNet model for mapping karst vegetation;(5) Fusion of single-class SegNet models and object-based RF model could provide high classifications results for karst wetland vegetation, and both achieved greater 87% overall accuracy.