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The high crystallinity and sophisticated hierarchical architecture of native animal silk endow it with comprehensive mechanical properties that are superior to those of most synthetic fibers. However, these features also make the direct exfoliation of silk nanofibrils (SNFs) highly challenging. On the other hand, silk‐based materials prepared by conventional method (i.e., through silk fibroin aqueous solution) are usually weak, so the preparation methods based on SNFs have attracted much attention in recent years. Herein, a facile and environmentally friendly route is developed to directly exfoliate SNFs from natural Bombyx mori silkworm silk via ammonium persulfate oxidation followed by ultrasonication. The obtained SNFs have a high yield (nearly 40%) and are well dispersed in water in a wide pH range, so they can act as a good starting material to prepare subsequent silk‐based materials. The main application of the SNFs demonstrated in this article is a curcumin (Cur)/SNFs hydrogel as wound dressing. In vivo experimental results show that the Cur/SNFs hydrogel significantly enhanced the healing rate of wounds on diabetic mice. Therefore, the preparation method developed in this study provides an efficient way to produce SNFs, which have great potential for a wide range of applications, including as wound dressings for diabetics. [ABSTRACT FROM AUTHOR]

The herbaceous peony (Paeonia lactiflora Pall.) plant is world-renowned for its ornamental, medicinal, edible, and oil values. As global warming intensifies, its growth and development are often affected by high-temperature stress, especially in low-latitude regions. Superoxide dismutase (SOD) is an important enzyme in the plant antioxidant systems and plays vital roles in stress response by maintaining the dynamic balance of reactive oxygen species (ROS) concentrations. To reveal the members of then SOD gene family and their potential roles under high-temperature stress, we performed a comprehensive identification of the SOD gene family in the low-latitude cultivar 'Hang Baishao' and analyzed the expression patterns of SOD family genes (PlSODs) in response to high-temperature stress and exogenous hormones. The present study identified ten potential PlSOD genes, encoding 145–261 amino acids, and their molecular weights varied from 15.319 to 29.973 kDa. Phylogenetic analysis indicated that PlSOD genes were categorized into three sub-families, and members within each sub-family exhibited similar conserved motifs. Gene expression analysis suggested that SOD genes were highly expressed in leaves, stems, and dormancy buds. Moreover, RNA-seq data revealed that PlCSD1-1, PlCSD3, and PlFSD1 may be related to high-temperature stress response. Finally, based on the Quantitative Real-time PCR (qRT-PCR) results, seven SOD genes were significantly upregulated in response to high-temperature stress, and exogenous EBR and ABA treatments can enhance high-temperature tolerance in P. lactiflora. Overall, these discoveries lay the foundation for elucidating the function of PlSOD genes for the thermotolerance of herbaceous peony and facilitating the genetic breeding of herbaceous peony cultivars with strong high-temperature resistance. [ABSTRACT FROM AUTHOR]

Herein, a green biocatalytic approach using lipase as a catalyst has been developed for the synthesis of 3-selanyl-isoflavones through the selenylation/cyclization of 2-hydroxyphenyl enaminones and diphenyl di-selenide under mild conditions. The environmentally friendly method reached high yields of 87–95% in a short time at 30 °C, with 17 examples of 3-selanyl-isoflavones successfully prepared. Furthermore, we have investigated the possible mechanisms underlying this reaction. [ABSTRACT FROM AUTHOR]

Gene function verification is a crucial step in studying the molecular mechanisms regulating various plant life activities. However, a stable and efficient homologous genetic transgenic system for herbaceous peonies has not been established. In this study, using virus-induced gene silencing technology (VIGS), a highly efficient homologous transient verification system with distinctive advantages was proposed, which not only achieves true "intact-plant" infiltration but also minimizes the operation. One-year-old roots of the representative species, Paeonia lactiflora Pall., were used as the materials; prechilling (4 °C) treatment for 3–5 weeks was applied as a critical precondition for P. lactiflora to acquire a certain chilling accumulation. A dormancy-related gene named HOMEOBOX PROTEIN 31 (PlHB31), believed to negatively regulate bud endodormancy release (BER), was chosen as the target gene in this study. GFP fluorescence was detected in directly infiltrated and newly developed roots and buds; the transgenic plantlets exhibited remarkably earlier budbreak, and PlHB31 was significantly downregulated in silenced plantlets. This study established a homologous transient silencing system featuring intact-plant infiltration and minimized manipulation for gene function research, and also offers technical support and serves as a theoretical basis for gene function discovery in numerous other geophytes. [ABSTRACT FROM AUTHOR]

The BFGS method is a common and effective method for solving unconstrained optimization problems in quasi-Newton algorithm. However, many scholars have proven that the algorithm may fail in some cases for nonconvex problems under Wolfe conditions. In this paper, an adaptive projection BFGS algorithm is proposed naturally which can solve nonconvex problems, and the following properties are shown in this algorithm: ➀ The generation of the step size α j satisfies the popular Wolfe conditions; ➁ a specific condition is proposed which has sufficient descent property, and if the current point satisfies this condition, the ordinary BFGS iteration process proceeds as usual; ➂ otherwise, the next iteration point x j + 1 is generated by the proposed adaptive projection method. This algorithm is globally convergent for nonconvex problems under the weak-Wolfe-Powell (WWP) conditions and has a superlinear convergence rate, which can be regarded as an extension of projection BFGS method proposed by Yuan et al. (J. Comput. Appl. Math. 327:274-294, 2018). Furthermore, the final numerical results and the application of the algorithm to the Muskingum model demonstrate the feasibility and competitiveness of the algorithm. [ABSTRACT FROM AUTHOR]

With the wide application of ultra-wideband (UWB) ranging technology in industry, production and aerospace, how to improve the accuracy of UWB ranging has become a research hotspot. If the UWB ranging data is treated as sequence data, it is possible to improve the ranging performance by sequence analysis, which has low computation complexity compared to direct UWB signal processing. However, as the UWB ranging data has its inherent properties, existing sequence analysis methods may not achieve good performance on UWB ranging data. In this paper, a two-path deep-learning framework to process, namely the Multiple Network model with Second order motion (MNS), is proposed the improve UWB ranging performance via ranging sequence analysis. The proposed method fuses the target motion prediction via Newton's laws of motion and error estimation via GRU, LSTM and Bayes. To evaluate our algorithm, we also proposed a method to collect both UWB ranging data and the accurate answer via laser ranging. The collected dataset D A T A _ T S , the proposed MNS algorithm, and the trained model are all open sourced to the community to help researchers for further research,please visit(https://github.com/xiaojiuwotongxue/data-store.git). Experiments on D A T A _ T S shows our proposed method outperforms traditional regresion methods significantly. [ABSTRACT FROM AUTHOR]

Background: Existing panels for lower respiratory tract infections (LRTIs) are slow and lack quantification of important pathogens and antimicrobial resistance, which are not solely responsible for their complex etiology and antibiotic resistance. BioFire FilmArray Pneumonia (PN) panels may provide rapid information on their etiology. Methods: The bronchoalveolar lavage fluid of 187 patients with LRTIs was simultaneously analyzed using a PN panel and cultivation, and the impact of the PN panel on clinical practice was assessed. The primary endpoint was to compare the consistency between the PN panel and conventional microbiology in terms of etiology and drug resistance, as well as to explore the clinical significance of the PN panel. The secondary endpoint was pathogen detection using the PN panel in patients with community-acquired pneumonia (CAP) or hospital-acquired pneumonia (HAP). Results: Fifty-seven patients with HAP and 130 with CAP were included. The most common pathogens of HAP were Acinetobacter baumannii and Klebsiella pneumoniae, with the most prevalent antimicrobial resistance (AMR) genes being CTX-M and KPC. For CAP, the most common pathogens were Haemophilus influenzae and Staphylococcus aureus, with the most frequent AMR genes being CTX-M and VIM. Compared with routine bacterial culture, the PN panel demonstrated an 85% combined positive percent agreement (PPA) and 92% negative percent agreement (NPA) for the qualitative identification of 13 bacterial targets. PN detection of bacteria with higher levels of semi-quantitative bacteria was associated with more positive bacterial cultures. Positive concordance between phenotypic resistance and the presence of corresponding AMR determinants was 85%, with 90% positive agreement between CTX-M-type extended-spectrum beta-lactamase gene type and phenotype and 100% agreement for mecA/C and MREJ. The clinical benefit of the PN panel increased by 25.97% compared with traditional cultural tests. Conclusion: The bacterial pathogens and AMR identified by the PN panel were in good agreement with conventional cultivation, and the clinical benefit of the PN panel increased by 25.97% compared with traditional detection. Therefore, the PN panel is recommended for patients with CAP or HAP who require prompt pathogen diagnosis and resistance identification. [ABSTRACT FROM AUTHOR]

The spatter generated by the interaction between laser and powder during Powder Bed Fusion-Laser Melting (PBF-LM) can significantly affect the quality of printed parts. A high-speed camera is used to observe the dynamic process of spatter's behavior under different layer thickness and laser powers during the printing process, and to analyze the printed samples' surface roughness, microstructure, and mechanical properties. In terms of spatter image processing, employing an optical flow approach to track and quantify the number of spatters efficiently eliminates statistical redundancy and improves statistical correctness. It is found that under the same laser power, the number of spatters produced by the laser scan direction with the gas flow (LSD-W) is more than that by the laser scan direction against the gas flow (LSD-A), and the number of spatters produced increases with the increase of laser power. Analyzing the mechanical properties and surface roughness of the printed samples under different process parameters quantitatively reveals that differences in the spatter amount generated under different process parameters in the PBF-LM process is not the determining factor affecting the difference in tensile strength of printed parts. During LSD-W, the number of spatters generated at laser power of 170 W and layer thickness of 0.03 mm is 87, and the tensile strength of the printed sample is 618 MPa. During LSD-W, the number of spatters generated at laser power of 320 W and layer thickness of 0.05 mm is 211, and the tensile strength of the printed sample is 680 MPa. Instead, spatter generation has a more direct impact on the surface roughness of printed parts. The layer thickness is 0.03 mm, the laser power is 170 W, and (Ra = 2.372 μm) is the surface roughness of the sample. The layer thickness is 0.05 mm, the laser power is 320 W, and (Ra = 8.163 μm) is the surface roughness of the sample. [ABSTRACT FROM AUTHOR]

Extant literature has extensively examined the diffusion of performance-based budgeting (PBB) from the standpoint of central governments, with a special focus on European and American countries. However, how PBB reforms diffuse within a unitary state, especially among mid-level governments, still remains elusive. To better understand the mechanism of PBB diffusion, this research use Event History Analysis to investigate how leadership characteristics, intergovernmental relations, financial standing, and organizational culture affect provincial PBB diffusion in China. The findings suggest that (1) the reasons for PBB adoption vary across different types of public leaders; (2) PBB reforms are primarily diffused through the bottom-up inducement, with central advocacy and horizontal competition playing an insignificant role; (3) provinces with a greater financial standing are more likely to adopt PBB reforms; (4) a culture that values reforms and transparency of information can drive the diffusion of PBB reforms. As a result, our research has clear implications for performance budgeting literature and practice: it provides valuable insights to policy-makers and public leaders on how to facilitate PBB reforms and policy diffusion across mid-level governments, particularly in a unitary state. [ABSTRACT FROM AUTHOR]

The three-dimensional (3D) geometrical information that depth maps contain is useful in many applications such as 3D reconstruction or simultaneous localization and mapping (SLAM). Kinect is widely used in depth image acquisition due to its low cost and good real-time performance. However, the quality of depth images obtained by Kinect is influenced by holes which make depth image inadequate for further applications. To suppress the influence of holes on a subsequent application, a fixing algorithm of Kinect depth image based on non-local means (NLM) is proposed in this paper. The holes in depth image are filled using the weights which are calculated on the corresponding gray image by distance factor and value consistent factor. And the experiment results demonstrate that the proposed method achieves good performance in both evaluation in metrics and subjectively visual effect. This research provides a solution idea for depth image fixing algorithm with low complexity. [ABSTRACT FROM AUTHOR]

Coal's calorific value and carbon content are crucial in calculating carbon emissions. Accurately detecting these two indicators is of great significance for carbon accounting. In this study, we developed a compact coal quality rapid detection integrated machine based on laser‐induced breakdown spectroscopy (LIBS), which can directly measure coal particle flow. A partial least squares model, based on data set selection according to cluster analysis results, was applied to establish the relationship between coal quality and plasma spectra. The R2 of the calorific value is.93, the root mean square error of prediction (RMSEP) is 0.41 MJ/kg, and the mean absolute error (MAE) is 0.33 MJ/kg. The R2 of carbon content is.94, the RMSEP is 0.97%, and the MAE is 0.91%. These results indicated that the developed compact coal quality rapid detection integrated machine could conduct precise coal quality analysis in real time. [ABSTRACT FROM AUTHOR]

Bismuth (Bi)‐based materials merit high theoretical volumetric specific capacity (3800 mAh mL⁻1) but suffer from huge volume variations and sluggish reaction kinetics during cycling. Herein, the optimal framework of Bi/Bi2O3 nanodots enriched in suitable outer amorphous carbon sheets (Bi/Bi2O3 NDs@CSs) is first proposed to alleviate volume variations and accelerate stable charge transport to boost K+ storage performance. The introduction of proper Bi2O3 not only provides an efficient K+ adsorption path, but also effectively buffers volume changes via conversion reaction. Accordingly, the as‐prepared anode exhibits a remarkable rate capability (149.3 mAh g−1 at 60 A g−1, 42% capacity retention with a 120‐fold current‐density increase) and extraordinary durability (1800 cycles at 5.0 A g−1, 95% capacity retention), among the best rate and cycling performance to date in potassium ion batteries (PIBs) anodes. Theoretical calculations reveal the feasible structures of Bi/Bi2O3 NDs@CSs with double protection of carbon sheets and Bi2O3 are conducive to enhance charge transfer and efficiency of electrochemical reaction. Substantial in situ/ex situ characterizations and finite element simulation further unveil high reversibility and robust mechanical behavior of Bi/Bi2O3 NDs@CSs, favorable for the reinforcement of structural stability. This study provides new insights into developing high‐performance and durable Bi‐based anodes for PIBs. [ABSTRACT FROM AUTHOR]

Despite the relatively low stiffness of sulfide solid‐state electrolytes (SSEs), which makes them capable of better formability and accommodation for volume changes of active materials, the low fracture toughness (KIC) indicates a high susceptibility to fracture caused by electrochemo‐mechanical stresses. This susceptibility to mechanical damages and the subsequent lithium filament penetration, manifesting as micro‐short circuit events, seriously hinders the practical application of lithium metal in high‐energy‐density sulfide‐based all‐solid‐state lithium metal batteries (ASSLMBs). A full understanding of the stress evolution of Li metal anodes during cycling is key to decoding the mechanical damage‐induced micro‐short circuit behavior. Here, an operando and quantitative measurement of the stress evolution of an LTO/SSE/Li configuration all‐solid‐state battery (ASSB) operating with various parameters, including cell capacity and current density, is shown. Two micro‐short circuit modes and their corresponding mechanisms are revealed based on the electrochemo‐mechanical response of the Li metal anode. Furthermore, a finite element model (FEM) is used to explain this mechanical failure and a ′safety zone″ for the Li metal anode related to the ′internal stress″ is given. These findings provide new insight into the micro‐short circuit events induced by electrochemo‐mechanical damage in sulfide‐based ASSLMBs. [ABSTRACT FROM AUTHOR]

This study aimed to evaluate the effectiveness of double ABCX-based psychotherapy for psychological distress during in vitro fertilization-embryo transfer (IVF-ET) among a female group (FG), couple group (CoG) and control group (CG). A total of 201 women undergoing their first IVF-ET cycle were randomized into three groups. The 6-session intervention was delivered at each visit to the IVF clinic. The primary outcomes were depression and anxiety, and the secondary outcomes included sleep quality, serum cortisol (nmol/L) levels and the clinical pregnancy rate, which were assessed before and after the intervention. The group-by-time effects were significant for depression, anxiety, sleep quality and serum cortisol levels, with larger effect sizes in the FG than in the CoG. There was no significant difference in the pregnancy rate among the three groups. Psychotherapy effectively mitigated psychological distress, suggesting greater effectiveness for couples undergoing IVF couples than for women only. It is structured and easy to use during the IVF treatment cycle. (NCT03931187, retrospectively registered on April 23, 2019) Double ABCX-based psychotherapy, which was developed in this study, effectively mitigated depression, anxiety, sleep disturbance and increased cortisol levels, suggesting greater effectiveness for couples undergoing IVF-ET than women only. Double ABCX-based psychotherapy is structured and easy to use during the IVF-ET treatment cycle, thereby presenting a promising and feasible approach to improve care for couples or women with assisted reproductive technique-related stress. [ABSTRACT FROM AUTHOR]

During the process of determining carbon emissions from coal using the emission factor method, third-party organizations in China are responsible for verifying the accuracy of the carbon emission data. However, these verifiers face challenges in efficiently handling large quantities of data. Therefore, this study proposed a fast screening method that utilizes multiple linear regression (MLR), in combination with the stepwise backward regression method, to identify problematic carbon emission data for the lower calorific value (LCV) and carbon content (C) of coal. The results demonstrated the effectiveness of the proposed method. The regression models for LCV and C exhibited high R-squared (R2) values of 0.9784 and 0.9762, respectively, and the root mean square error (RMSE) values of the validation set were 0.32 MJ/kg and 0.80% for LCV and C, respectively, indicating strong predictive capabilities. By analyzing the obtained results, the study established the optional error threshold interval for the LCV and C of coal as 2RMSE–3RMSE. This interval can be utilized as a reliable criterion for judging the quality and reliability of carbon emission data during the verification process. Overall, the proposed screening method can serve as a valuable tool for verifiers in assessing the quality and reliability of carbon emission data in various regions. [ABSTRACT FROM AUTHOR]

Remote sensing images are very vulnerable to cloud interference during the imaging process. Cloud occlusion, especially thick cloud occlusion, significantly reduces the imaging quality of remote sensing images, which in turn affects a variety of subsequent tasks using the remote sensing images. The remote sensing images miss ground information due to thick cloud occlusion. The thick cloud removal method based on a temporality global–local structure is initially suggested as a solution to this problem. This method includes two stages: the global multi-temporal feature fusion (GMFF) stage and the local single-temporal information restoration (LSIR) stage. It adopts the fusion feature of global multi-temporal to restore the thick cloud occlusion information of local single temporal images. Then, the featured global–local structure is created in both two stages, fusing the global feature capture ability of Transformer with the local feature extraction ability of CNN, with the goal of effectively retaining the detailed information of the remote sensing images. Finally, the local feature extraction (LFE) module and global–local feature extraction (GLFE) module is designed according to the global–local characteristics, and the different module details are designed in this two stages. Experimental results indicate that the proposed method performs significantly better than the compared methods in the established data set for the task of multi-temporal thick cloud removal. In the four scenes, when compared to the best method CMSN, the peak signal-to-noise ratio (PSNR) index improved by 2.675, 5.2255, and 4.9823 dB in the first, second, and third temporal images, respectively. The average improvement of these three temporal images is 9.65%. In the first, second, and third temporal images, the correlation coefficient (CC) index improved by 0.016, 0.0658, and 0.0145, respectively, and the average improvement for the three temporal images is 3.35%. Structural similarity (SSIM) and root mean square (RMSE) are improved 0.33% and 34.29%, respectively. Consequently, in the field of multi-temporal cloud removal, the proposed method enhances the utilization of multi-temporal information and achieves better effectiveness of thick cloud restoration. [ABSTRACT FROM AUTHOR]

Background: This study aimed to validate the efficacy the multiplication of neutrophils and monocytes (MNM) and a novel dynamic nomogram for predicting in-hospital death in patients with aneurysmal subarachnoid hemorrhage (aSAH). Methods: Retrospective study was done on 986 patients with endovascular coiling for aSAH. Independent risk factors associated with in-hospital death were identified using both univariate and multivariate logistic regression analysis. In the development cohort, a dynamic nomogram of in-hospital deaths was introduced and made available online as a straightforward calculator. To predict the in-hospital death from the external validation cohort by nomogram, calibration analysis, decision curve analysis, and receiver operating characteristic analysis were carried out. Results: 72/687 patients (10.5%) in the development cohort and 31/299 patients (10.4%) in the validation cohort died. MNM was linked to in-hospital death in univariate and multivariate regression studies. In the development cohort, a unique nomogram demonstrated a high prediction ability for in-hospital death. According to the calibration curves, the nomogram has a reliable degree of consistency and calibration. With threshold probabilities between 10% and 90%, the nomogram's net benefit was superior to the basic model. The MNM and nomogram also exhibited good predictive values for in-hospital death in the validation cohort. Conclusions: MNM is a novel predictor of in-hospital mortality in patients with aSAH. For aSAH patients, a dynamic nomogram is a useful technique for predicting in-hospital death. [ABSTRACT FROM AUTHOR]

It is well known that under the Wolfe–Powell inexact line search, the global convergence of the nonlinear conjugate gradient method always requires the Lipschitz continuous condition for nonconvex functions. In this paper, we find that the Lipschitz continuous condition is unnecessary for proving the global convergence for particular algorithms if its searching direction has the well-known sufficient descent property and the trust region feature. Thus, the global convergence of the family conjugate gradient algorithms proposed by Yuan et al. (Numer. Algorithms, 84(2020)) is established without the Lipschitz condition for nonconvex functions since they have these two properties. Furthermore, a new algorithm without a line search technique is presented, and its global convergence is also analysed under suitable assumptions. The numerical results show that the performance of the proposed algorithm is competitive with some particular problems. [ABSTRACT FROM AUTHOR]

Failure is inevitable in the process of enterprise development. Previous studies have found that the negative emotions (such as anger) of employees after failure may have an important impact on their subsequent learning behaviour. However, no concrete conclusions have been drawn from related studies. Using 764 data samples from high-tech industries in mainland China, this study investigated the impact of employee anger on learning from failure and explored the moderating roles of resilience and project commitment in this process. The results showed that (1) anger has a negative effect on learning from failure; (2) resilience alleviates the negative effect caused by anger; and (3) project commitment alleviates the negative effect caused by anger. Our study has enriched the theoretical research in relevant fields and provided suggestions for Chinese companies on how to motivate employees to overcome the negative effects of failure and learn from failure. [ABSTRACT FROM AUTHOR]

The digestion, absorption, and utilization of sialic acid (SA) in the ready-to-eat peptide-containing and the traditional stewed edible bird's nest products were compared. Male SD rats aged 8 weeks (n=32) were divided into four groups randomly, including blank control group (BC), peptide-containing edible bird's nest group (PB), traditional edible bird's nest group (TB), and sialic acid standard control group (SC). After oral gavage, the feces and urine were collected over 2 days to evaluate the absorption and retention of SA by calculating its digestion and absorption rates. Blood was collected intermittently during 60-day consecutive gavage to monitor the content alteration of the free and protein-bound SA in plasma and the erythrocyte membrane-bound SA, and the degree of sialyation was adopted to evaluate exogenous SA utilization. The results of the 2-day feces and urine monitoring did not reveal any significant statistical differences in SA digestion and absorption among all groups. The results of 60-day consecutive gavage revealed that the free SA concentration (P<0.005) and protein-bound SA content (P<0.005) in plasma and the erythrocyte membrane-bound SA content (P<0.001) were significantly higher in each intervention group compared to the BC group. After 10 days of intervention, the protein-bound SA content in the PB group was 36.36% higher than that in the BC group (P<0.05), and the erythrocyte membrane-bound SA in the PB group increased by 28.13% and 13.89% compared to the TB and SC groups (P<0.05), respectively. In conclusion, the sialylation of blood can reflect exogenous SA utilization and peptides can promote the utilization of SA. Long-term consumption of all types of edible bird's nests can effectively improve the sialylation level of the body, surpassing the benefits derived from the intake of free SA. [ABSTRACT FROM AUTHOR]

In this study, the evolution of the Si atom distribution within an Al metallization layer in an insulated gate bipolar transistor (IGBT) module during power cycling is studied experimentally through electron backscatter diffraction (EBSD) observations, X-ray diffraction (XRD) measurements, and scanning electron microscopy (SEM) characterization. Molecular dynamics (MD) simulations are applied to study the effects of Si segregation on the mechanical properties of the Al metallization layer. The results show that Si segregation toward the Al grain boundaries occurs as the number of power cycles increases, and this behaviour strongly influences the recrystallization, texture, grain size and mechanical performance of the Al metallization layer. [ABSTRACT FROM AUTHOR]

Ultrasonic welding technology represents an advanced method for joining thermoplastic composites. However, there exists a scarcity of systematic investigations into welding parameters and their influence on the morphological characteristics and quality of the welded regions. Furthermore, a comprehensive experimental understanding of the welded joint failure mechanisms remains deficient. A robust model for simulating the failure behavior of welded joints under loading has yet to be formulated. In this study, ultrasonic welded specimens were fabricated using distinct welding control methods and varied parameter combinations. Diverse experimental methodologies are employed to assess the morphological features of the welded areas, ascertain specimen strength, and observe welding interface failure modes. Based on a cohesive model, a finite element model is developed to predict the strength of the ultrasonic welded joints and elucidate the failure mechanisms. The results showed that, under identical welding parameters, the specimens welded with a high amplitude and low welding force exhibit superior welding quality. The specimens produced under displacement control exhibit minimal dispersion in strength. The proposed finite element model effectively prognosticates both welded joint strength and failure modes. [ABSTRACT FROM AUTHOR]

Background : The present study aimed to synthesize the effects of five types of child maltreatment (physical abuse, emotional abuse, sexual abuse, physical neglect and emotional neglect) on late-life depression. Method : Four English-language databases (Web of Science, PsycINFO and PsycARTICLES, PubMed, and Cochrane Library) and three Chinese databases (China National Knowledge Infrastructure, Wanfang Database, and Weipu Database) were systematically reviewed, and data related to the association between child maltreatment and late-life depression were extracted. Ten studies involving 30,308 older adults were included, and the effect sizes were pooled using random-effect models. Findings : Except for sexual abuse, four types of child maltreatment were found to be positively associated with late-life depression. Physical abuse, emotional abuse and physical neglect were associated with elderly depression (PA: OR = 1.73, 95% CI = 1.55–1.95, p <.001; EA: OR = 1.92, 95% CI = 1.73–2.12, p <.001; PN: OR = 2.05, 95% CI = 1.15–3.67, p <.01) at a small level, and emotional neglect was associated with elderly depression (OR = 3.25, 95% CI = 1.43–7.39, p <.001) at an approximately moderate level. Gender moderated the relationship between physical neglect, emotional neglect, and late-life depression. Conclusion : Our findings highlight the significance of child maltreatment in the development of late-life depression, and underscore the need for future research and practice to explore potential ways to address late-life depression among older adults who suffered child maltreatment. [ABSTRACT FROM AUTHOR]

Intergranular cracking of Ni‐rich layered LiNi1‐x‐yCoxMnyO2 (1‐x‐y ≥ 0.8) cathode particles deteriorate the chemo–electro–mechanical stability of high‐energy lithium‐ion batteries (LIBs), thus presenting a challenge to typical modification methods to establish robust structures with highly efficient lithium‐ion storage. Herein, the ZrTiO4 (ZTO) as an epitaxial layer to enhance mechanical stability of ultrahigh‐Ni LiNi0.9Co0.05Mn0.05O2 (NCM90) is reported for the first time. Intensive exploration from structure characterizations (X‐ray absorption spectroscopy and in situ X‐ray diffraction techniques), multi‐physics field analysis, and first‐principles calculations disclose that the conformal ZTO layers and Zr doping effectively suppresses the internal strain and the release of lattice oxygen, which prodigiously restrains the local stress accumulation during whole (de)lithiation processes, thereby maintaining good mechanical stability of the materials. Meanwhile, the protective ZTO layer also prevents electrolyte erosion, thus keeping an intact surface structure of NCM90. Notably, ZTO‐modified NCM90 achieves significantly improved cyclability under high‐voltage (4.5 V) operation, expressing a 17% increase in capacity retention (71% vs 88%) after 100 cycles. Overall, this work reveals the role of internal strain in the original degradation behavior and effectiveness of surface engineering strategy to solve the challenge, emphasizing that the conformal surface protection mitigates the internal stress of Ni‐rich NCM by anchoring the lattice oxygen. [ABSTRACT FROM AUTHOR]

For exploring an effective heat treatment schedule to enhance the strength–plasticity balance of the ferrite–austenite 12CrNi2 alloy steel additively manufactured by directed energy deposition (DED), 12CrNi2 was heat-treated with deliberately designed direct quenching (DQ) and cyclic quenching (CQ), respectively, and the differently quenched steels were then tempered at a temperature from 200 °C to 500 °C. It was found that the CQ, in contrast to the DQ, led the 12CrNi2 to have significantly increased tensile strength without losing its plasticity, based on the introduction of fine-grained lath martensite and the {112}<111>-type nanotwins. The nanotwins were completely degenerated after the 200 °C tempering. This led the CQ-treated steel to decrease in not only its tensile strength, but also its plasticity. In addition, an interesting phenomenon observed was that the DQ-induced laths and rod-like precipitates, and the tempering-induced laths and rod-like precipitates were all prone to be generated along the {112} planes of the martensitic crystal (α -Fe), which were exactly fitted with the {112}-type crystalline orientation of the long or short nanotwins in the CQ-induced martensite. The quenching–tempering-induced generation of the {112}-orientated laths and rod-like precipitates was explicated in connection with the {112}<111>-type long or short nanotwins in the CQ-induced lath martensite. [ABSTRACT FROM AUTHOR]

In this paper, a new stochastic quasi-Newton method (SQN) is proposed which has a different approximation of the Hessian inverse matrix H k . The modified quasi-Newton Broyden–Fletcher–Goldfarb–Shanno (BFGS) formula which has a better approximation to Hessian matrix has not only the gradient variation but also the function value. Because of the special nature of the sum function, the mini-batch setting is built in the algorithm, and less compution cost can be guaranteed. The number of iterations reduce to at most O (ε - 1 1 - β ) . The convergence analysis is established in this paper. The numerical experiments show that this algorithm is competitive to other algorithms. [ABSTRACT FROM AUTHOR]

Excess phosphate in water can cause eutrophication, which must be addressed. Despite many efforts devoted to the adsorptive removal of phosphate from water, the development of new adsorbents with high adsorption capacity is highly desirable. Herein, a novel nanocomposite was proposed for phosphate removal by confining hydrated ferric oxide (HFO) nanoparticles into a cellulose aerogel (CA) network named as HFO@CA. Benefiting from the characteristics of the low density and porous structure of CA, the internal surface of the nanocomposite is more accessible and thus improves the utilization of the HFO nanoparticles. Batch adsorption experiments were carried out to evaluate the phosphate uptake by the prepared adsorbent. The maximum adsorption capacity of HFO@CA occurs at near-acidic pH. With increasing temperature, the composite adsorbent is more favorable for phosphate adsorption. Moreover, the hybrid aerogel exhibited fast kinetic behavior for phosphate removal, which could be accurately depicted by pseudo-second-order model. HFO@CA shows excellent adsorption selectivity in solutions containing competitive anions at higher levels. In addition, five cycles of the phosphate adsorption experiments without obvious capacity loss indicated that HFO@CA has great regenerability. These results demonstrate that HFO@CA has a wide field of application with good prospects in phosphate removal from wastewater, which also provides a new strategy to prepare adsorbents with excellent performance using renewable cellulose resources. [ABSTRACT FROM AUTHOR]

High-quality remote sensing images play important roles in the development of ecological indicators' mapping, urban-rural management, urban planning, and other fields. Compared with natural images, remote sensing images have more abundant land cover along with lower spatial resolutions. Given the embedded longitude and latitude information of remote sensing images, reference (Ref) images with similar scenes could be more accessible. However, existing traditional super-resolution (SR) approaches always depend on increases in network depth to improve performance, which limits the acquisition and application of high-quality remote sensing images. In this paper, we proposed a novel, reference-image-based, super-resolution method with feature compression module (FCSR) for remote sensing images to alleviate the above issue while effectively utilizing high-resolution (HR) information from Ref images. Specifically, we exploited a feature compression branch (FCB) to extract relevant features in feature detail matching with large measurements. This branch employed a feature compression module (FCM) to extract features from low-resolution (LR) and Ref images, which enabled texture transfer from different perspectives. To decrease the impact of environmental factors such as resolution, brightness and ambiguity disparities between the LR and Ref images, we designed a feature extraction encoder (FEE) to ensure accuracy in feature extraction in the feature acquisition branch. The experimental results demonstrate that the proposed FCSR achieves significant performance and visual quality compared to state-of-the-art SR methods. Explicitly, when compared with the best method, the average peak signal-to-noise ratio (PSNR) index on the three test sets is improved by 1.0877%, 0.8161%, 1.0296%, respectively, and the structural similarity (SSIM) index on four test sets is improved by 1.4764%, 1.4467%, 0.0882%, and 1.8371%, respectively. Simultaneously, FCSR obtains satisfactory visual details following qualitative evaluation. [ABSTRACT FROM AUTHOR]

In this paper, the cam connecting rod system of the high-speed group vertical machine flipping shaping mechanism is the research object. In order to solve the key problem that the flipping shaping mechanism cannot accurately complete the action when the vibration of the mechanism is large. In this paper, the finite element method is used to construct the dynamic model of the connecting rod subsystem of the flipped shaping mechanism. And The dynamic model of cam roller subsystem is established by centralized parameter method. Based on the MATLAB Genetic Algorithm toolbox and using Newmark's method, the dynamic equations of the flipped plastic mechanism system are solved. The optimal parameters of the connecting rod of the mechanism, the cam profile curve and the swing power and swing torque of the mechanism at different speeds are analyzed. The results show that the speed and convex contour line are important factors affecting the performance of the mechanism. And the pendulum force (swing torque) is the main cause of the vibration of the mechanism on the frame. Therefore, the mechanism pendulum dynamic and the swing moment are selected as the objective functions of the optimization model. By selecting the node parameters of the sixth order spline motion law and the cross-section parameters of the connecting rod as the design variables. The cam linkage system is optimally designed to obtain the optimal value. Finally, the optimal design of the flipped shaping mechanism was analyzed and compared with the original mechanism. [ABSTRACT FROM AUTHOR]

Vehicular Ad Hoc Network (VANET) is an important part of the modern intelligent transportation system, which can provide vehicle communication at a certain distance. More importantly, VANET can provide route planning and autonomous driving for drivers by analyzing data. However, VANET's data privacy and security are a huge challenge when serving drivers. In this paper, we propose a VANET data-sharing model (DSVN) that combines ciphertext-based attribute encryption (CP-ABE), blockchain, and InterPlanetary File System (IPFS). DSVN uses an outsourced and revocable ciphertext policy attribute-based encryption (ORCP-ABE) scheme, which is improved based on CP-ABE. ORCP-ABE uses key encryption key (KEK) trees to manage user attribute groups and revoke user-level attributes. It eliminates redundant attributes in the access policy by attribute-weighted access trees. Moreover, DSVN has no single point of failure. We demonstrate the indistinguishability under the chosen-plaintext attack (IND-CPA) security of DSVN by a game based on the computational Diffie–Hellman (CDH) assumption. Experimental results show that DSVN can store and share data with low overhead. Additionally, it can revoke attributes of users safely. [ABSTRACT FROM AUTHOR]

Summary: N-enriched biochar can increase the accumulation of carbon (C), nitrogen (N), phosphorus (P), and biomass in rice plants. On the other hand, the biomass and C, N, and P contents of plant organs are important indicators to reflect plant C, N, and P storages. We established control, 4 t ha−1, and 8 t ha−1 N-enriched biochar treatment plots in a subtropical paddy field in China to investigate the effect of these treatments on C, N, and P storages, ecological stoichiometry in various rice plant organs, and their relationships with edaphic factors. The application of N-enriched biochar increased the biomass and storages of C, N, and P in rice roots, stems, leaves, and grains, mainly at 4 t ha−1. The application of N-enriched biochar decreased the C/N and C/P ratios of rice organs, but increased their N/P ratio. Changes in C/N were mainly due to the changes in storage, while N/P was positively correlated with N storage of stems, leaves, and grains and negatively correlated with P storage in roots. Pearson's correlation analysis revealed that pH was negatively correlated, and soil N content was positively correlated with P storage in various organs of rice. In addition, soil P content and chlorophyll were positively correlated with N storage. In conclusion, we found that the application of N-enriched biochar improved plant N and P storage and stoichiometrical relations among rice organs. [ABSTRACT FROM AUTHOR]

The WAAM molding process is complex, and the morphology, microstructure, and mechanical properties of the printed parts are affected by multiple factors. In this study, the heat input in the process of WAAM research has made the comprehensive elaboration. The numerical simulation method is used to simulate the molten pool in the process of WAAM, and the force, heat transfer, and velocity of the molten pool are analyzed. Path planning is also an important part of WAAM research, and there are many methods for additive manufacturing path planning, all of which are aimed at improving the dimensional accuracy and performance of the printed parts. Reasonable path planning can also be used for additive components with complex shapes and structures. This study comprehensively expounds on the research on WAAM path planning by scholars in recent years. [ABSTRACT FROM AUTHOR]

Bulked segregant analysis (BSA) is a rapid, cost-effective method for mapping mutations and quantitative trait loci (QTLs) in animals and plants based on high-throughput sequencing. However, the algorithms currently used for BSA have not been systematically evaluated and are complex and fallible to operate. We developed a BSA method driven by deep learning, DeepBSA, for QTL mapping and functional gene cloning. DeepBSA is compatible with a variable number of bulked pools and performed well with various simulated and real datasets in both animals and plants. DeepBSA outperformed all other algorithms when comparing absolute bias and signal-to-noise ratio. Moreover, we applied DeepBSA to an F 2 segregating maize population of 7160 individuals and uncovered five candidate QTLs, including three well-known plant-height genes. Finally, we developed a user-friendly graphical user interface for DeepBSA, by integrating five widely used BSA algorithms and our two newly developed algorithms, that is easy to operate and can quickly map QTLs and functional genes. The DeepBSA software is freely available to non-commercial users at http://zeasystemsbio.hzau.edu.cn/tools.html and https://github.com/lizhao007/DeepBSA. The authors developed a bulked segregant analysis (BSA) method driven by deep learning, DeepBSA, for quantitative trait loci mapping and functional gene cloning, that is compatible with a variable number of bulked pools and performed well in both animals and plants. Furthermore, a user-friendly graphical user interface for DeepBSA, which integrated five widely used BSA algorithms and our two newly developed algorithms, was provided. [ABSTRACT FROM AUTHOR]

Mixed-cation lead mixed-halide perovskites simultaneously possess structural stability and high power conversion efficiency. A thorough study of both carrier and exciton dynamics is needed to understand the photophysical properties that underpin its superior photovoltaic performance. By utilizing a broadband transient absorption spectroscopy, we observe the carrier and exciton dynamics in a FA0.85Cs0.15Pb(I0.97Br0.03)3 (FCPIB) perovskite by simultaneously resolving the carrier and exciton contribution to the transient change of the absorption spectra, from which the carrier density and exciton oscillator strength can be determined. Our data reveal a quick and significant conversion of the photogenerated carriers to excitons, on top of the usual carrier recombination process. Moreover, the decay of carrier density shows a change of kinetics from a second-order recombination at high pump fluence to a third-order recombination at low pump fluence. Our analysis utilizes band anharmonicity, presents an independent determination of electronic temperature and quasi-Fermi energy, and reveals an interesting interplay among the processes of carrier cooling, exciton formation/decay and carrier recombination, all as a function of time after photoexcitation. Our work demonstrates the use of pump fluence as a knob to tune the relative populations of carriers and excitons in halide perovskite materials. Lead halide perovskites have many suitable features as materials for solar cells and a better understanding of the underlying physics will help engineer improved performance values. Here, the authors use broadband transient absorption spectroscopy to probe the excited state dynamics of mixed-halide perovskites and the role of excitons and carriers. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSNs) technology and Internet technology penetrate and extend each other. It is a good way for physical changes of objects, state recognition and data collection, and becomes an important source of network data in big data. Compared with traditional wireless networks, WSNs have the characteristics of integrating sensing, processing, and transmission, limited hardware resources, limited power supply capacity, no center, self-organization, multi-hop routing, dynamic topology, large number of nodes, and dense distribution. In order to improve the energy utilization rate of a single node to a greater extent, reduce the energy consumption of the entire WSNs, and extend the life cycle of WSNs, high-efficiency networking is essential in the application of WSNs. Networking is one of the foundations to the large-scale WSNs. The network model and node location deployment are important technologies for WSNs networking. Based on the network characteristics of large-scale WSNs and the transmission capacity of big data, a new type of network model suitable is presented which combined the advantages of Star model and Mesh model. More importantly, the deployment environment of sensor nodes is a spatial network. The data collected and transmitted by large-scale WSNs is very large. The deployment of sensor nodes in space can ensure that the big data collected and transmitted are true and effective. This research proposes the space density first (SDF) algorithm, which improves the neighbor density first algorithm with the space node deployment and the density-optimized SDF algorithm. The SDF algorithm saves network energy and extends the life of the network. Experimental results show that large-scale WSNs built with a new networking model and SDF algorithm can collect and transmit big data stably and reliably, which saves network energy and improves the accuracy of big data. [ABSTRACT FROM AUTHOR]

To study the effects of Bacillus subtilis supplementation in a high-fat diet on the gut microbiota and nonalcoholic fatty liver disease in grass carp (Ctenopharyngodon idella), juveniles (60 ± 5 g) were fed three diets: (a) a control diet (CON), (b) a high-fat diet (HFD) and (c) a high-fat diet supplemented with B. subtilis (HFD + BS). After 8 weeks of feeding, fish growth, serum biochemical indices and total liver lipid content were measured, and gut microbiota analysis was performed using the MiSeq250 high-throughput sequencing platform. The results of this study showed that B. subtilis could improve growth and blood serum indices and reduce lipid deposition in the fish liver, preventing fatty liver disease. A grass carp model of fatty liver induced by a high-fat diet was successfully established. Moreover, B. subtilis altered the intestinal microbiota of HFD-fed grass carp, making it more similar to that of the control group. This study revealed the important effects of B. subtilis on grass carp with fatty liver induced by a high-fat diet and provides the foundation for the application of probiotics in grass carp farming. [ABSTRACT FROM AUTHOR]

Axitinib is one of the most potent inhibitors of the vascular endothelial growth factor (VEGF) receptor and shows strong antitumor activity toward various malignant tumors. However, its severe side effects affect the quality of life and prognosis of patients. Losartan, which functions as a typical angiotensin receptor blocker, controls the average arterial pressure of patients with essential hypertension and protects against hypertension-related secondary diseases, including proteinuria and cardiovascular injury. To explore the effects of losartan on side effects caused by axitinib and its antitumor activity, several animal experiments were conducted. This study first analyzed and explored the effect of losartan on the amelioration of side effects in Wistar rats caused by axitinib. The results showed that the systolic blood pressure of Wistar rats was significantly increased by about 30 mmHg in 7 days of axitinib treatment, while the combination of losartan significantly reduced the blood pressure rise caused by axitinib. The Miles experimental model and mouse xenograft tumor model were further used to evaluate the effect of losartan on the antitumor effect of axitinib. The result clearly demonstrated that losartan has no significant influence on axitinib-related low vascular permeability and antitumor activity. In summary, our results showed that the combination of axitinib and losartan significantly reduced the side effects and maintained the antitumor effects of axitinib. This study provides information for overcoming VEGF receptor inhibitor-related side effects. [ABSTRACT FROM AUTHOR]

Hordeum jubatum L. is a potential ornamental grass species. Spermidine (Spd) plays a regulatory role in plant stress. This study measured seedling growth, photosynthesis, chlorophyll fluorescence, osmotic regulatory substance contents, and antioxidant enzyme activities in H. jubatum seedlings pretreated with Spd (0–1.5 mM at 0.5 mM intervals) in drought treatments simulating natural water loss. The results indicated that the water content, photosynthetic parameters maximal quantum yield of PSII photochemistry (Fv/Fm), actual quantum yield of photochemical energy conversion in PSII (ϕPSII), and photochemical quenching coefficient (qp) values of H. jubatum shoots decreased significantly with increasing drought intensity. Simultaneously, the contents of malondialdehyde (MDA) and the nonphotochemical quenching coefficient (NPQ) value increased. Spd improved growth and photosynthesis under drought stress. Spd also increased osmotic regulatory substance contents and antioxidant enzyme activities. These results suggest that the drought stress inhibited the growth of H. jubatum and damaged the photosynthetic systems, triggering a range of protective responses. Exogenous Spd mitigated the damage by promoting a variety of responses and adaptive mechanisms, such as adjusting stomatal conductance, promoting photosynthetic capacity, accelerating the synthesis of osmoregulatory molecules, and activating antioxidant enzyme systems. Additionally, 1.5 mM Spd-treated H. jubatum had the best drought tolerance. This study will help to develop an understanding of the effects of exogenous Spd on improving drought resistance and provide a strategy for the H. jubatum landscape effect to be achieved under water-limited conditions. [ABSTRACT FROM AUTHOR]

Hexavalent chromium [Cr(VI)], a recognized heavy metal pollutant, has attracted much attention because of its negative impact on the ecological environment and human health. A chromium-resistant strain, Sporosarcina saromensis M52, was discovered, and the functional genes orf2987, orf3015, orf0415, and orf3237 were identified in the strain by genomics. With the advancement of DNA recombination and gene-splicing technology, genetic engineering technology was used to produce recombinant strains 2987, 3015, 0415, and 3237. The study revealed Cr(VI) tolerance in the order of M52 ≈ 2987 > 3015 ≈ 0415 > 3237 and reduction abilities in the order of M52 ≈ 2987 > 3015 > 0415 ≈ 3237. SEM-EDS, XRD, FT-IR and XPS were utilized to examine the surface structure of the recombinant strains and analyze the surface components and main functional groups. A comprehensive review of the recombinant strains' capacity to tolerate and reduce Cr(VI) revealed that orf2987 and orf0415 were the main functional genes in Sporosarcina saromensis M52, which may play a key role in removing Cr(VI) and protecting the strain, respectively. The optimum pH for recombinant strains 2987 and 0415 was 7.5–8.5, and the optimum temperature was 37°C. Cu2+ had the greatest promotional effect when Cr(VI) was removed by them, while SDS had an inhibitory effect. This research provided the foundation for further study into the mechanism of Cr(VI) reduction in Sporosarcina saromensis M52, as well as a theoretical basis for the development of effective engineered strains to repair Cr(VI) contamination. [ABSTRACT FROM AUTHOR]

Introduction: Acute traumatic intraparenchymal hematoma (tICH) expansion is a major cause of clinical deterioration after brain contusion. Here, an accurate prediction tool for acute tICH expansion is proposed. Methods: A multicenter hospital-based study for multivariable prediction model was conducted among patients (889 patients in a development dataset and 264 individuals in an external validation dataset) with initial and follow-up computed tomography (CT) imaging for tICH volume evaluation. Semi-automated software was employed to assess tICH expansion. Two multivariate predictive models for acute tICH expansion were developed and externally validated. Results: A total of 198 (22.27%) individuals had remarkable acute tICH expansion. The novel Traumatic Parenchymatous Hematoma Expansion Aid (TPHEA) model retained several variables, including age, coagulopathy, baseline tICH volume, time to baseline CT time, subdural hemorrhage, a novel imaging marker of multihematoma fuzzy sign, and an inflammatory index of monocyte-to-lymphocyte ratio. Compared with multihematoma fuzzy sign, monocyte-to-lymphocyte ratio, and the basic model, the TPHEA model exhibited optimal discrimination, calibration, and clinical net benefits for patients with acute tICH expansion. A TPHEA nomogram was subsequently introduced from this model to facilitate clinical application. In an external dataset, this device showed good predicting performance for acute tICH expansion. Conclusions: The main predictive factors in the TPHEA nomogram are the monocyte-to-lymphocyte ratio, baseline tICH volume, and multihematoma fuzzy sign. This user-friendly tool can estimate acute tICH expansion and optimize personalized treatments for individuals with brain contusion. [ABSTRACT FROM AUTHOR]

Background: There is no unified treatment standard for patients with extranodal NK/T-cell lymphoma (ENKTL). Cancer neoantigens are the result of somatic mutations and cancer-specific. Increased number of somatic mutations are associated with anti-cancer effects. Screening out ENKTL-specific neoantigens on the surface of cancer cells relies on the understanding of ENKTL mutation patterns. Hence, it is imperative to identify ENKTL-specific genes for ENKTL diagnosis, the discovery of tumor-specific neoantigens and the development of novel therapeutic strategies. We investigated the gene signatures of ENKTL patients.Methods: We collected the peripheral blood of a pair of twins for sequencing to identify unique variant genes. One of the twins is diagnosed with ENKTL. Seventy samples were analyzed by Robust Multi-array Analysis (RMA). Two methods (elastic net and Support Vector Machine-Recursive Feature Elimination) were used to select unique genes. Next, we performed functional enrichment analysis and pathway enrichment analysis. Then, we conducted single-sample gene set enrichment analysis of immune infiltration and validated the expression of the screened markers with limma packages.Results: We screened out 126 unique variant genes. Among them, 11 unique genes were selected by the combination of elastic net and Support Vector Machine-Recursive Feature Elimination. Subsequently, GO and KEGG analysis indicated the biological function of identified unique genes. GSEA indicated five immunity-related pathways with high signature scores. In patients with ENKTL and the group with high signature scores, a proportion of functional immune cells are all of great infiltration. We finally found that CDC27, ZNF141, FCGR2C and NES were four significantly differential genes in ENKTL patients. ZNF141, FCGR2C and NES were upregulated in patients with ENKTL, while CDC27 was significantly downregulated.Conclusion: We identified four ENKTL markers (ZNF141, FCGR2C, NES and CDC27) in patients with extranodal NK/T-cell lymphoma. [ABSTRACT FROM AUTHOR]

Purpose of Review We review recent literature on the effects of climate change on child and adolescent mental health and discuss treatment and engagement by clinicians. Recent Findings Climate change affects child and adolescent mental health in many intersecting ways, including as a social and ecological determinant of health, a threat amplifier, and a source of trauma and distress. Single extreme weather events contribute to significant negative mental health consequences; however, subacute and chronic climate events also have mental health sequelae. Furthermore, awareness of the climate crisis is associated with emotional distress. Young people with pre-existing mental illness and lacking social support may be at elevated risk for climate change-related mental health effects. Climate activism is associated with resilience and positive development, but may also be a source of increased stress, particularly for marginalized youths. Summary Climate change can affect the mental health of children and adolescents in complex and diverse ways. Sources of coping and resilience also vary greatly between individuals. Mental health clinicians must respond to this existential crisis by addressing research gaps in this area, obtaining relevant clinical training, educating their communities, and joining and supporting young people in their advocacy efforts. [ABSTRACT FROM AUTHOR]

mRNA vaccines against cancer have advantages in safety, improved therapeutic efficacy, and large-scale production. Therefore, our purpose is to identify immune biomarkers and to analyze immune status for developing mRNA vaccines and selecting appropriate patients for vaccination. We downloaded clinical information and RNA-seq data of 494 LUAD patients from TCGA. LUAD mutational information was hierarchically clustered by NMF package (Version 0.23.0). DeconstructSigs package (Version 1.8.0) and NMF consistency clustering were used to identify mutation signatures. Maftools package (Version 2.6.05) was used to select LUAD-related immune biomarkers. TIMER was used to discuss the correlation between genetic mutations and cellular components. Unsupervised clustering Pam method was used to identify LUAD immune subtypes. Log-rank test and univariate/multivariate cox regression were used to predict the prognosis of immune subtypes. Dimensionality reduction analysis was dedicated to the description of LUAD immune landscape. LUAD patients are classified into four signatures: T >C, APOBEC mutation, age, and tobacco. Then, GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Next, we clustered five LUAD-related immune subtypes (IS1–IS5) by prognostic prediction. IS3 showed prolonged survival. The reliability of our five immune subtypes was validated by Thorsson's results. IS2 and IS4 patients had high tumor mutation burden and large number of somatic mutations. Besides, we identified that immune subtypes of cold immunity (patients with IS2 and IS4) are ideal mRNA vaccination recipients. Finally, LUAD immune landscape revealed immune cells and prognostic conditions, which provides important information to select patients for vaccination. GPRIN1, MYRF, PLXNB2, SLC9A4, TRIM29, UBA6, and XDH are potential LUAD-related immune biomarker candidates to activate the immune response. Patients with IS2 and IS4 might potentially be immunization-sensitive patients for vaccination. [ABSTRACT FROM AUTHOR]

The nucleation and growth of Li metal during deposition and the associated dendrite penetration are the critical and fundamental issues influencing the safety and power density of solid‐state lithium metal batteries (SSLBs). However, investigations on Li metal deposition/dissolution especially the formation and growth of Li dendrites and their determining factors in the all‐solid‐state electrochemical systems are still lacking. In this work, in situ observations of the Li metal growth process, and defects induced heterogeneous deposition under cathodic load, are reported. By exploiting in situ scanning electron microscopy, along with electrochemical analytical approaches, the spatial distribution and morphological evolution of the deposited Li at the electrode|solid electrolyte interface are obtained and discussed. This investigation reveals that the formation of lithium whiskers is decided by the local Li ion flux and the deposition active sites, which are closely dependent on the content and types of defects in the polycrystalline electrolyte. Moreover, the defect regions exhibit faster Li deposition kinetics and higher nucleation tendency. These results can advance the fundamental understanding of the Li penetration mechanism in SSLBs. [ABSTRACT FROM AUTHOR]

The emotional experience brought about by failure, especially the important roles of negative emotions in learning behavior after failure, has received increasingly more attention from organization management scholars. Research on the impact of employees' sense of failure-induced shame is still controversial. Based on the Chinese context, according to the process model of emotion regulation theory, we have studied the influence of failure-induced shame on employees' learning from failure and the conditions that have boundary effects on this process. Through a questionnaire analysis of 776 samples from Chinese high-tech enterprises, the results show the following: (1) shame has a negative relationship with learning from failure (2) project commitment alleviates the negative relationship between shame and learning from failure, and (3) restoration orientation alleviates the negative relationship between shame and learning from failure while loss orientation cannot. Our results further enrich the research on negative emotions related to failure and provide a theoretical basis for the failure management of Chinese companies. [ABSTRACT FROM AUTHOR]

This study aimed to determine the effect of the growth stage of Procambarus clarkii on their intestinal microbiota. Intestinal samples of five different growth stages of P. clarkii (first instar, second instar, third instar, juvenile, and adult) from laboratory culture were analyzed through the Illumina MiSeq high-throughput sequencing platform to determine the intestinal microbiome of crayfish. The alpha diversity decreased along with the growth of the crayfish, with the relative abundance of the microbiota changing among stages; crayfish at closer development stages had a more comparable intestinal microbiota composition. A comparative analysis by principal component analysis and principal coordinate analysis showed that there were significant differences in the intestinal microbiota of crayfish among the different growth stages, except for the first two stages of larval crayfish, and the intestinal microbiota showed a consistent progression pattern from the larval stage to the juvenile stage. Some microbiota showed stage specificity, which might be the characteristic microbiota of different stages of growth. According to FAPROTAX functional clustering analysis, the three stages of larvae were clustered together, while the juvenile and adult stages were clustered separately according to the growth stage, indicating that, in the early stages of larval development, the function of the intestinal flora was similar; as the body grew and developed, the composition and function of the intestinal microbiota also changed. [ABSTRACT FROM AUTHOR]