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Abstract In today’s globalized agricultural system, information leakage of agricultural biological risk factors can lead to business risks and public panic, jeopardizing corporate reputation. To solve the above problems, this study constructs a blockchain network for agricultural product biological risk traceability based on agricultural product biological risk factor data to achieve traceability of biological risk traceability data of agricultural product supply chain to meet the sustainability challenges. To guarantee the secure and flexible sharing of agricultural product biological risk privacy information and limit the scope of privacy information dissemination, the blockchain-based proxy re-encryption access control method (BBPR-AC) is designed. Aiming at the problems of proxy re-encryption technology, such as the third-party agent being prone to evil, the authorization judgment being cumbersome, and the authorization process not automated, we design the proxy re-encryption access control mechanism based on the traceability of agricultural products’ biological risk factors. Designing an attribute-based access control (ABAC) mechanism based on the traceability blockchain for agricultural products involves defining the attributes of each link in the agricultural supply chain, formulating policies, and evaluating and executing these policies, deployed in the blockchain system in the form of smart contracts. This approach achieves decentralization of authorization and automation of authority judgment. By analyzing the data characteristics within the agricultural product supply chain to avoid the malicious behavior of third-party agents, the decentralized blockchain system acts as a trusted third-party agent, and the proxy re-encryption is combined with symmetric encryption to improve the encryption efficiency. This ensures a efficient encryption process, making the system safe, transparent, and efficient. Finally, a prototype blockchain system for traceability of agricultural biological risk factors is built based on Hyperledger Fabric to verify this research method’s reliability, security, and efficiency. The experimental results show that this research scheme’s initial encryption, re-encryption, and decryption sessions exhibit lower computational overheads than traditional encryption methods. When the number of policies and the number of requests in the access control session is 100, the policy query latency is less than 400 ms, the request-response latency is slightly more than 360ms, and the data uploading throughput is 48.7 tx/s. The data query throughput is 81.8 tx/s, the system performance consumption is low and can meet the biological risk privacy protection needs of the agricultural supply chain. The BBPR-AC method proposed in this study provides ideas for achieving refined traceability management in the agricultural supply chain and promoting digital transformation in the agricultural industry.

Abstract Diffusion involving atom transport from one location to another governs many important processes and behaviors such as precipitation and phase nucleation. The inherent chemical complexity in compositionally complex materials poses challenges for modeling atomic diffusion and the resulting formation of chemically ordered structures. Here, we introduce a neural network kinetics (NNK) scheme that predicts and simulates diffusion-induced chemical and structural evolution in complex concentrated chemical environments. The framework is grounded on efficient on-lattice structure and chemistry representation combined with artificial neural networks, enabling precise prediction of all path-dependent migration barriers and individual atom jumps. To demonstrate the method, we study the temperature-dependent local chemical ordering in a refractory NbMoTa alloy and reveal a critical temperature at which the B2 order reaches a maximum. The atomic jump randomness map exhibits the highest diffusion heterogeneity (multiplicity) in the vicinity of this characteristic temperature, which is closely related to chemical ordering and B2 structure formation. The scalable NNK framework provides a promising new avenue to exploring diffusion-related properties in the vast compositional space within which extraordinary properties are hidden.

To investigate the role of pre-twins in Mg alloy sheets during warm planar deformation, the stretch forming is conducted at 200 °C. Results suggest the formability of the pre-twinned AZ31 Mg alloy sheet is enhanced to 11.30 mm. The mechanisms for the improved formability and the deformation behaviors during the planar stretch forming are systematically investigated based on the planar stress states. The Schmid factor for deformation mechanisms are calculated, the results reveal that planar stress states extremely affect the Schmid factor for {10-12} twinning. The detwinning is activated and the prismatic slip is enhanced in the pre-twinned sheet, especially under the planar extension stress state in the outer region. Consequently, the thickness-direction strain is accommodated better. The dynamic recrystallization (DRX) type is continuous DRX (CDRX) regardless of the planar stress state. However, the CDRX degree is greater under the planar extension stress state. Some twin lattices deviate from the perfect {10-12} twinning relation due to the planar compression stress state and the CDRX. The basal texture is weakened when the planar stress state tends to change the texture components.

Introduction: On the propagation path to the satellite, the ionosphere will distort the nuclear electromagnetic pulse (NEMP) and change its physical properties.Methods: This paper proposes a method for calculating the propagation of NEMP to the satellite. The method decomposes NEMP into the superposition of simple harmonic waves, and each simple harmonic wave is calculated separately in the ionosphere. With the consideration of different time of arrival and critical frequency of the ionosphere, the NEMP after propagating in the ionosphere is obtained by superposition of simple harmonic waves in time domain rather than the inverse Fourier transform which will erase the time domain information.Results: The results show that NEMP is dispersive in ionosphere with the pulse broadened, the speeds changed and the bandwidth narrowed. The time-frequency spectrum can provide the frequency band where the signal energy is located.Discussion: Our proposed method provides a simple and effective way to calculate the NEMP propagation in the ionosphere, which should afford help to the design of NEMP receivers and the selection of satellite orbit altitude.

As a new type of topology inverter, the isolated quasi-Z-source inverter is suitable for photovoltaic power generation systems because of its high efficiency in power conversion, high boost ratio and electrical isolation. By increasing the operating frequency of the inverter, the inductance and capacitance volume of the inverter can be reduced, so that the inverter has higher power density. However, high-frequency switching actions will produce a large number of current and voltage sudden changes, leading to electromagnetic interference (EMI), affecting other components or the entire system and the stable operation of the power grid. Chaotic frequency modulation is a method to reduce the electromagnetic interference level of switching converters from the source. This method using the 10-scroll chaotic signal of the even-symmetric segmented Chen system as a spread spectrum signal to broaden the electromagnetic interference noise energy spikes to the surrounding continuous frequency bands, thereby reducing the spectrum peaks and making the system has better electromagnetic compatibility performance. In this paper, the high frequency isolated quasi Z-source photovoltaic grid-connected micro-inverter is studied, and the chaotic frequency modulation technology is used to suppress the electromagnetic interference of the inverter.

Abstract Background Poor in vivo targeting of tumors by chemotherapeutic drugs reduces their anti-cancer efficacy in the clinic. The discovery of over-expressed components on the tumor cell surface and their specific ligands provide a basis for targeting tumor cells. However, the differences in the expression levels of these receptors on the tumor cell surface limit the clinical application of anti-tumor preparations modified by a single ligand. Meanwhile, toxicity of chemotherapeutic drugs leads to poor tolerance to anti-tumor therapy. The discovery of natural active products antagonizing these toxic side effects offers an avenue for relieving cancer patients’ pain during the treatment process. Since the advent of nanotechnology, interventions, such as loading appropriate drug combinations into nano-sized carriers and multiple tumor-targeting functional modifications on the carrier surface to enhance the anti-tumor effect and reduce toxic and side effects, have been widely used for treating tumors. Results Nanocarriers containing doxorubicin hydrochloride (DOX) and salvianolic acid A (Sal A) are spherical with a diameter of about 18 nm; the encapsulation efficiency of both DOX and salvianolic acid A is greater than 80%. E-[c(RGDfK)2]/folic acid (FA) co-modification enabled nanostructured lipid carriers (NLC) to efficiently target a variety of tumor cells, including 4T1, MDA-MB-231, MCF-7, and A549 cells in vitro. Compared with other preparations (Sal A solution, NLC-Sal A, DOX solution, DOX injection, Sal A/DOX solution, NLC-DOX, NLC-Sal A/DOX, and E-[c(RGDfK)2]/FA-NLC-Sal A/DOX) in this experiment, the prepared E-[c(RGDfK)2]/FA-NLC-Sal A/DOX had the best anti-tumor effect. Compared with the normal saline group, it had the highest tumor volume inhibition rate (90.72%), the highest tumor weight inhibition rate (83.94%), led to the highest proportion of apoptosis among the tumor cells (61.30%) and the lowest fluorescence intensity of proliferation among the tumor cells (0.0083 ± 0.0011). Moreover, E-[c(RGDfK)2]/FA-NLC-Sal A/DOX had a low level of nephrotoxicity, with a low creatinine (Cre) concentration of 52.58 μmoL/L in the blood of mice, and no abnormalities were seen on pathological examination of the isolated kidneys at the end of the study. Sal A can antagonize the nephrotoxic effect of DOX. Free Sal A reduced the Cre concentration of the free DOX group by 61.64%. In NLC groups, Sal A reduced the Cre concentration of the DOX group by 42.47%. The E-[c(RGDfK)2]/FA modification reduced the side effects of the drug on the kidney, and the Cre concentration was reduced by 46.35% compared with the NLC-Sal A/DOX group. These interventions can potentially improve the tolerance of cancer patients to chemotherapy. Conclusion The E-[c(RGDfK)2]/FA co-modified DOX/Sal A multifunctional nano-drug delivery system has a good therapeutic effect on tumors and low nephrotoxicity and is a promising anti-cancer strategy. Graphical Abstract

Chemo-photothermal/photodynamic synergistic therapy is a new effective cancer treatment method to overcome the limitations of single chemotherapy. However, the limited low photothermal conversion efficiency, the hypoxic tumor microenvironment, and premature leakage of the drug constrain their clinical applications. To address these challenges, an all-in-one biodegradable polydopamine-coated UiO-66 framework nanomedicine (DUPM) was developed to co-deliver the drug doxorubicin hydrochloride (DOX) and the excellent photothermal material MoOx nanoparticles (NPs). The results showed that DUPM exhibited good physicochemical stability and efficiently accumulated tumor tissues under pH-, glutathione-, and NIR-triggered drug release behaviour. Of note, the synthesized MoOx NPs endowed DUPM with self-supporting oxygen production and generated more reactive oxygen species (1O2 and·OH), besides, it induces Mo-mediated redox reaction to deplete excessive glutathione thus relieving tumor hypoxia to enhance PDT, further improving synergistic therapy. Meanwhile, DUPM showed strong absorption in the near-infrared range and high photothermal conversion efficiency at 808 nm (51.50%) to realize photoacoustic imaging-guided diagnosis and treatment of cancer. Compared with monotherapy, the in vivo anti-tumor efficacy results showed that DUMP exerted satisfactory tumor growth inhibition effects (94.43%) with good biocompatibility. This study provides a facile strategy to develop intelligent multifunctional nanoparticles with tumor hypoxia relief for improving synergistic therapy and diagnosis against breast cancer.

Nano-targeted delivery systems have been widely used for breast tumor drug delivery. Estrogen receptors are considered to be significant drug delivery target receptors due to their overexpression in a variety of tumor cells. However, targeted ligands have a significant impact on the safety and effectiveness of active delivery systems, limiting the clinical transformation of nanoparticles. Phytoestrogens have shown good biosafety characteristics and some affinity with the estrogen receptor. In the present study, molecular docking was used to select tanshinone IIA (Tan IIA) among phytoestrogens as a target ligand to be used in nanodelivery systems with some modifications. Modified Tan IIA (Tan-NH2) showed a good biosafety profile and demonstrated tumor-targeting, anti-tumor and anti-tumor metastasis effects. Moreover, the ligand was utilized with the anti-tumor drug Dox-loaded mesoporous silica nanoparticles via chemical modification to generate a nanocomposite Tan-Dox-MSN. Tan-Dox-MSN had a uniform particle size, good dispersibility and high drug loading capacity. Validation experiments in vivo and in vitro showed that it also had a better targeting ability, anti-tumor effect and lower toxicity in normal organs. These results supported the idea that phytoestrogens with high affinity for the estrogen receptor could improve the therapeutic efficacy of nano-targeted delivery systems in breast tumors.

Chronic wounds are a major health challenge that require new treatment strategies. Hydrogels are promising drug delivery systems for chronic wound healing because of their biocompatibility, hydration, and flexibility. However, conventional hydrogels cannot adapt to the dynamic and complex wound environment, which involves low pH, high levels of reactive oxygen species, and specific enzyme expression. Therefore, smart responsive hydrogels that can sense and respond to these stimuli are needed. Crucially, smart responsive hydrogels can modulate drug release and eliminate pathological factors by changing their properties or structures in response to internal or external stimuli, such as pH, enzymes, light, and electricity. These stimuli can also be used to trigger antibacterial responses, angiogenesis, and cell proliferation to enhance wound healing. In this review, we introduce the synthesis and principles of smart responsive hydrogels, describe their design and applications for chronic wound healing, and discuss their future development directions. We hope that this review will inspire the development of smart responsive hydrogels for chronic wound healing.

In this study, AZ31 Mg alloy sheet was pre-twinned at room temperature along the transverse direction (TD) to introduce {10–12} tensile twins. The uniaxial tensile experiment was conducted at 200 °C to investigate the dynamic recrystallization, twinning behaviors and mechanical response. The strain paths tilted angles of 0°, 15°, 30°, 45°, 60°, 75° and 90° in respect to the rolling direction (RD) on the RD-TD plane were considered. Results revealed that the strain path has significant effects on the microstructural evolution and mechanical response at warm temperature. When the strain path tilts were 0°, 15°, 30°, 45° and 60° with the RD, continuous dynamic recrystallization (CDRX) was the main mechanism to coordinate strain. The detwinning dominated the microstructural evolution but retarded by CDRX for the pre-twinned sample with a strain path angle of 75°. Detwinning and CDRX played an important role on the microstructural evolution in the pre-twinned sample when the strain path was tilted 90°. Additionally, the effect of CDRX on {10–12} twinning and three types of {10–12} tensile twin behaviors were discussed. Both strengthening and weakening effects were observed in pre-twinned samples.

The ANSI/AGMA 2003-B97 is a widely used bending stress checking standard for spiral bevel gears. The calculation formula of bending strength checking is carried out， the key parameters are modified， the problem of insufficient safety margin of bending strength checking solved， and this method is verified by finite element contact analysis. Based on the modified bending strength checking standard， the strength checking software of spiral bevel gear is developed， and the optimal design scheme of tooth surface is given. The proposed method can improve the accuracy and efficiency of tooth surface bending strength checking calculation.

In order to improve the structural performance of the aero-engine gearbox housing and reduce the adverse effects of the engine bad working conditions on the supporting components， the topology optimization theory based on variable density method is adopted， and the minimum flexibility index and weighted average transverse eigenvalue are taken as the target number， and the coupling of thermal-elastohydrodynamic-lubrication effects of the supporting components are considered. Taking the maximum deformation less than 0.15 mm and the equivalent stress less than the material stress as the constraint conditions， the topology optimization design of the aero-engine gearbox housing is carried out. According to the topology optimization results， the geometric reconstruction of the housing structure is carried out， and the strength， stiffness and mass of the shell structure before and after optimization are compared and analyzed. The results show that， after optimization， the housing mass is reduced from 5.53 kg to 5.107 kg， the weight is reduced by 7.6%， the maximum deflection of the housing is reduced from 0.173 1 mm to 0.127 mm， the deformation is reduced by 26.6%， the maximum equivalent stress of the housing is reduced from 124 MPa to 116.9 MPa， the stress is reduced by 5.7%.The maximum deformation and equivalent stress of the housing are effectively reduced， and the strength and stiffness of the housing are significantly improved. It is of great significance to improve the reliability and service life of aero-engine central transmission shell.

Bridge operational accident analysis is a critical process in bridge operational risk management. It provides valuable knowledge support for responding to newly occurring accidents. However, there are three issues: (1) research specifically focused on the past bridge operational accidents is relatively scarce; (2) there is a lack of mature research findings regarding the bridge operational accidents knowledge representation; and (3) in similar case retrieval, while case-based reasoning (CBR) is a valuable approach, there are still some challenges and limitations associated with its usage. To tackle these problems, this research proposed an automated analysis approach for bridge operational accidents based on a knowledge graph and CBR. The approach includes case representation and case retrieval, leveraging advancements in computer science and artificial intelligence. In the proposed approach, the case representation involves the adoption of a knowledge graph to construct multi-dimensional networks. The knowledge graph captures the relationships between various factors and entities, allowing for a comprehensive representation of accidents domain knowledge. In the case retrieval, a multi-circle layer retrieval strategy was innovatively proposed to enhance retrieval efficiency. Three target cases were randomly selected to verify the validity of the proposed methodology. The combination of a knowledge graph and CBR can indeed provide useful tools for the automated analysis of bridge operational accidents. Additionally, the proposed methodology can serve as a reference for intelligent risk management in other types of infrastructures.

BackgroundPatients' subjective experiences during clinical interactions may affect their engagement in healthcare, and better understanding of the issues patients consider most important may help improve service quality and patient-staff relationships. While diagnostic imaging is a growing component of healthcare utilization, few studies have quantitatively and systematically assessed what patients deem most relevant in radiology settings. To elucidate factors driving patient satisfaction in outpatient radiology, we derived quantitative models to identify items most predictive of patients' overall assessment of radiology encounters.MethodsPress-Ganey survey data (N = 69,319) collected over a 9-year period at a single institution were retrospectively analyzed, with each item response dichotomized as "favorable" or "unfavorable." Multiple logistic regression analyses were performed on 18 binarized Likert items to compute odds ratios (OR) for those question items significantly predicting Overall Rating of Care or Likelihood of Recommending. In a secondary analysis to identify topics more relevant to radiology than other encounter types, items significantly more predictive of concordant ratings in radiology compared to non-radiology visits were also identified.ResultsAmong radiology survey respondents, top predictors of Overall Rating and Likelihood of Recommending were items addressing patient concerns or complaints (OR 6.8 and 4.9, respectively) and sensitivity to patient needs (OR 4.7 and 4.5, respectively). When comparing radiology and non-radiology visits, the top items more predictive for radiology included unfavorable responses to helpfulness of registration desk personnel (OR 1.4-1.6), comfort of waiting areas (OR 1.4), and ease of obtaining an appointment at the desired time (OR 1.4).ConclusionsItems related to patient-centered empathic communication were the most predictive of favorable overall ratings among radiology outpatients, while underperformance in logistical issues related to registration, scheduling, and waiting areas may have greater adverse impact on radiology than non-radiology encounters. Findings may offer potential targets for future quality improvement efforts.

Granulosa cell tumor (GCT) is a rare tumor that originates from neural/Schwann cells. GCTs can occur at any age and at any site in the body. The most common site is the tongue, followed by the mammary gland, upper respiratory tract ( throat and bronchus), and gastrointestinal tract (esophagus, large intestine and perianal area, stomach, small intestine, and bile duct). Malignant GCTs account for less than 1%–2% of all GCTs. Fewer than five GCTs in the thoracic wall have been reported, almost all of these benign. Here, we report a new case of malignant GCT of the thoracic wall, with rib invasion and pleural metastasis, in an Asian male. Microscopic examination revealed round, granular cells with eosinophilic cytoplasm and without prominent atypia. Despite these findings the disease showed rapid clinical progression. In summary, the tumor, although histologically ‘benign’, was clinically ‘malignant’.

This case report describes a 58-year-old, never-smoking housewife with chief complaints of progressively worsening cough, dyspnea, and intermittent fever, who was initially misdiagnosed with community-acquired pneumonia (CAP). However, her pulse oximetry oxygen saturation continued to decline, and eventually, she underwent an endotracheal intubation. Fortunately, transbronchial cryobiopsy (TBCB) assisted by extracorporeal membrane oxygenation (ECMO) was performed in the most critical situation, and it revealed an organizing pneumonia (OP) pattern. OP describes a histological pattern of acute or subacute pulmonary damage, which may be idiopathic or associated with a known or unknown underlying disease. A definitive diagnosis of OP usually obtained from pathology, and surgical lung biopsy with large lung tissue is recommended. However, since the surgical lung biopsy was not convenient for this patient after mechanical ventilation, bedside TBCB supported by ECMO was selected. To our knowledge, we are the first to report the pathological diagnosis of ECMO assisted TBCB in acute respiratory failure. When oxygenation cannot be maintained after endotracheal intubation and surgical lung biopsy is not feasible, ECMO-supported TBCB may be a good choice to obtain lung tissue for histopathological diagnosis in patients with acute lung injury of unknown etiology.

In mammals, the retinoic acid-inducible gene I (RIG-I)-like receptors (RLR) has been demonstrated to play a critical role in activating downstream signaling in response to viral RNA. However, its role in ducks’ antiviral innate immunity is less well understood, and how gene-mediated signaling is regulated is unknown. The regulatory role of the duck laboratory of genetics and physiology 2 (duLGP2) in the duck RIG-I (duRIG-I)-mediated antiviral innate immune signaling system was investigated in this study. In duck embryo fibroblast (DEF) cells, overexpression of duLGP2 dramatically reduced duRIG-I-mediated IFN-promotor activity and cytokine expression. In contrast, the knockdown of duLGP2 led to an opposite effect on the duRIG-I-mediated signaling pathway. We demonstrated that duLGP2 suppressed the duRIG-I activation induced by duck Tembusu virus (DTMUV) infection. Intriguingly, when duRIG-I signaling was triggered, duLGP2 enhanced the production of inflammatory cytokines. We further showed that duLGP2 interacts with duRIG-I, and this interaction was intensified during DTMUV infection. In summary, our data suggest that duLGP2 downregulated duRIG-I mediated innate immunity against the Tembusu virus. The findings of this study will help researchers better understand the antiviral innate immune system’s regulatory networks in ducks.

The access control (AC) system in an IoT (Internet of Things) context ensures that only authorized entities have access to specific devices and that the authorization procedure is based on pre-established rules. Recently, blockchain-based AC systems have gained attention within research as a potential solution to the single point of failure issue that centralized architectures may bring. Moreover, zero-knowledge proof (ZKP) technology is included in blockchain-based AC systems to address the issue of sensitive data leaking. However, current solutions have two problems: (1) systems built by these works are not adaptive to high-traffic IoT environments because of low transactions per second (TPS) and high latency; (2) these works cannot fully guarantee that all user behaviors are honest. In this work, we propose a blockchain-based AC system with zero-knowledge rollups to address the aforementioned issues. Our proposed system implements zero-knowledge rollups (ZK-rollups) of access control, where different AC authorization requests can be grouped into the same batch to generate a uniform ZKP, which is designed specifically to guarantee that participants can be trusted. In low-traffic environments, sufficient experiments show that the proposed system has the least AC authorization time cost compared to existing works. In high-traffic environments, we further prove that based on the ZK-rollups optimization, the proposed system can reduce the authorization time overhead by 86%. Furthermore, the security analysis is presented to show the system’s ability to prevent malicious behaviors.

Abstract Novel duck reovirus (NDRV) causes severe economic losses to the duck industry, which is characterized by hemorrhagic spots and necrotic foci of the livers and spleens. DEAD-box helicase 1 (DDX1) plays a critical role in the innate immune system against viral infection. However, the role of duck DDX1 (duDDX1) in anti-RNA virus infection, especially in the anti-NDRV infection, has yet to be elucidated. In the present study, the full-length cDNA of duDDX1 (2223 bp encode 740 amino acids) was firstly cloned from the spleen of healthy Cherry valley ducks, and the phylogenetic tree indicated that the duDDX1 has the closest relationship with Anas platyrhynchos in the bird branch. The duDDX1 mRNA was widely distributed in all tested tissues, especially in the duodenum, liver, and spleen. Overexpression of duDDX1 in primary duck embryo fibroblast (DEF) cells triggered the activation of transcription factors IRF-7 and NF-κB, as well as IFN-β expression, and the expression of the Toll-like receptors (TLR2, TLR3, and TLR4) was significantly increased. Importantly, after overexpressing or knocking down duDDX1 and infecting NDRV in DEF cells, duDDX1 inhibits the replication of NDRV virus and also regulates the expression of pattern recognition receptors and cytokines. This indicates that duDDX1 may play an important role in the innate immune response of ducks to NDRV. Collectively, we first cloned DDX1 from ducks and analyzed its biological functions. Secondly, we proved that duck DDX1 participates in anti-NDRV infection, and innovated new ideas for the prevention and control of duck virus infection.

Abstract Background At present, serum Aspergillus IgG and IgM antibody detection is mainly used in the diagnosis of chronic pulmonary aspergillosis (CPA), but its value in the diagnosis of invasive pulmonary aspergillosis (IPA) in non-agranulocytic patients is still unclear. IgM can be used as a marker of acute infection to help diagnose acute infection-related diseases. IgG is a marker of long-term infection and is used to assist in the diagnosis of pre-existing or chronic infection-related diseases. The aim of this study was to investigate and compare the value of serum Aspergillus IgG and IgM antibody detection in the diagnosis of IPA and CPA in non-agranulocytic patients. Methods Fifty-eight cases of pulmonary aspergillosis (37 IPA and 21 CPA cases), 15 cases of community-acquired bacterial pneumonia and 50 cases in the healthy control group were collected. The serum (1,3)-β-D-glucan test (G test) was performed with a chromogenic method, and the galactomannan test (GM test) and Aspergillus IgG and IgM antibody detection were performed by commercial enzyme-linked immunosorbent assay (ELISA) in all patients. The sensitivity and specificity, cut-off value and area under the curve (AUC) of Aspergillus IgG and IgM antibodies were further obtained by receiver operating characteristic (ROC) curves. Results The positive rate of the G test, Aspergillus IgG antibody detection and the GM test also showed notable differences among the IPA, CPA, community-acquired bacterial pneumonia and healthy groups (P = 0.006, P

In the present study Ar+ cluster ions accelerated by voltages in the range of 5–10 kV are used to irradiate single crystal ZnO substrates and nanorods to fabricate self-assembled surface nanoripple arrays. The ripple formation is observed when the incidence angle of the cluster beam is in the range of 30–70°. The influence of incidence angle, accelerating voltage, and fluence on the ripple formation is studied. Wavelength and height of the nanoripples increase with increasing accelerating voltage and fluence for both targets. The nanoripples formed on the flat substrates remind of aeolian sand ripples. The ripples formed at high ion fluences on the nanorod facets resemble well-ordered parallel steps or ribs. The more ordered ripple formation on nanorods can be associated with the confinement of the nanorod facets in comparison with the quasi-infinite surface of the flat substrates.

Abstract Support vector machine (SVM) is one of the effective classifiers in the field of network intrusion detection; however, some important information related to classification might be lost in the reprocessing. In this paper, we propose a granular classifier based on entropy clustering method and support vector machine to overcome this limitation. The overall design of classifier is realized with the aid of if-then rules that consists of a premise part and conclusion part. The premise part realized by the entropy clustering method is used here to address the problem of a possible curse of dimensionality, while the conclusion part realized by support vector machines is utilized to build local models. In contrast to the conventional SVM, the proposed entropy clustering-based granular classifiers (ECGC) can be regarded as an entropy-based support function machine. Moreover, an opposition-based genetic algorithm is proposed to optimize the design parameters of the granular classifiers. Experimental results show the effectiveness of the ECGC when compared with some classical models reported in the literatures.

ABSTRACT: Interferon regulatory factor 8 (IRF8) is also known as interferon (IFN) consensus sequence binding protein (ICSBP), which plays an important role in IFN signal transduction. In this study, we cloned the full-length coding sequence of Cherry Valley duck IRF8 (duIRF8) and analyzed its structure. In addition, we tested the distribution of IRF8 in the tissues of healthy Cherry Valley ducks, and the changes in IRF8 expression levels in the tissues after virus infection. The results show that the open reading frame (ORF) of IRF8 is 1293 bp, encodes 430 amino acids, and have 3 conserved domains: the N-terminal DBD domain, the C-terminal IAD domain, and the NLS domain. Besides, from the analysis of the phylogenetic tree, it can be known that the duIRF8 has the highest homology with the anser cygnoides, and has less homology with the fish. Analyzing the distribution level of IRF8 in the tissues, it is found that the expression level of IRF8 in the liver of Cherry Valley duck is the highest. However, after infection with duck Tambusu virus, novel duck reovirus, and duck plague virus, the expression of IRF8 in the spleen and brain all showed up-regulation. These data indicate that IRF8 is involved in the host's innate immune response against virus in Cherry Valley duck.

Fibrosis and cancer is described by some epidemiological studies as chronic stages of different disease conditions typically characterized by uncontrolled accumulation of extra-cellular matrix (ECM), thereby leading to inflammation of tissues and organ (lungs, heart, liver and kidney) dysfunction. It is highly prevalent, and contributes to increased mortality rate worldwide. Currently, the therapeutical approaches involving selected medications (bemcentinib, pirfenidone and nintedanib) obtained synthetically, and used in clinical practices for fibrosis and cancer management and treatment has shown to be unsatisfactorily, especially during progressive stages of the disease. With regards to finding a more potent, effective, and promising curative for fibrosis and cancer, there is need for continuous experimental studies universally. However, phytochemical constituents’ particularly phenolic compounds [Chlorogenic acid (CGA)] obtained from coffee, and coffee beans have been predominantly utilized in experimental studies, due to its multiple pharmacological properties against various disease forms. Considering its natural source alongside minimal toxicity level, CGA, a major precursor of coffee have gained considerable attention nowadays from researchers worldwide, owing to its wide, efficacious and beneficial action against fibrosis and cancer. Interestingly, the safety of CGA has been proven. Furthermore, numerous experimental studies have also deduced massive remarkable outcomes in the use of CGA clinically, as a potential drug candidate against treatment of fibrosis and cancer. In the course of this review article, we systematically discussed the beneficial contributions of CGA with regards to its source, absorption, metabolism, mechanistic effects, and molecular mechanisms against different fibrosis and cancer categorization, which might be a prospective remedy in the future. Moreover, we also highlighted CGA (in vitro and in vivo analytical studies) defensive effects against various disorders.

ABSTRACT: Interferon regulatory factor 4 (IRF4) is a multifunctional transcription factor that plays an important regulatory role in the interferon (IFN) signaling. IRF4 participates in the process of antivirus, Th cell differentiation and B cell maturation by regulating the expression of IFN and some lymphokines. In this study, Cherry Valley duck IRF4 (duIRF4) was cloned and its cDNA was analyzed. Expression of duIRF4 in a wide variety of tissues and changes in duIRF4 expression due to viral infection also was detected by quantitative real-time PCR. The results show that duIRF4 contains 1,341 bp of ORF encoding a protein with 446 amino acids and contains 3 domains: DNA-binding domain (DBD), IRF-association domain (IAD) and nuclear localization signal (NLS). Quantitative real-time PCR analysis showed that duIRF4 was evenly expressed in all tissues examined, with the highest expression in the spleen, followed by the bursa of Fabricius, and lower in the skin and brain. In addition, expression of duIRF4 in the brain and spleen was significantly upregulated after being infected by duck plague virus, duck Tembusu virus, and novel duck reovirus. These data suggest that duIRF4 may be involved in innate immune response.

As a natural compound, gambogic acid (GA) emerged a shining multi-target antitumor activity in a variety of tumors. Whereas its poor solubility and non-specific effect to tumor blocked the clinical application of this drug. Herein, we reported a simple and effective strategy to construct liposome modified with nuclear targeted peptide CB5005N (VQRKRQKLMPC) via polyethylene glycol (PEG) linker to decrease the inherent limitations of GA and promote its anti-tumor activity. In this study, liposomes were prepared by thin film hydration method. The characterization of formulations contained particle size, Zeta potential, morphology and encapsulation efficiency. Further, in vitro cytotoxicity and uptake tests were investigated by 4T1 and MDA-MB-231 cells, and nuclear targeting capability was performed on MDA-MB-231 cells. In addition, the in vivo antitumor effect and biological distribution of formulations were tested in BALB/c female mice. The GA-loaded liposome modified by CB5005N showed small size, good uniformity, better targeting, higher anti-tumor efficiency, better tumor inhibition rate and lower toxicity to normal tissues than other groups. In vitro and in vivo research proved that CB5005N-GA-liposome exhibited excellent anti-tumor activity and significantly reduced toxicities. As a result, CB5005N-GA-liposome nano drug delivery system enhanced the tumor targeting and antitumor effects of GA, which provided a basis for its clinical application.

Due to the great success of Vision Transformer (ViT) in image classification tasks, many pure Transformer architectures for human action recognition have been proposed. However, very few works have attempted to use Transformer to conduct bimodal action recognition, i.e., both skeleton and RGB modalities for action recognition. As proved in many previous works, RGB modality and skeleton modality are complementary to each other in human action recognition tasks. How to use both RGB and skeleton modalities for action recognition in a Transformer-based framework is a challenge. In this paper, we propose RGBSformer, a novel two-stream pure Transformer-based framework for human action recognition using both RGB and skeleton modalities. Using only RGB videos, we can acquire skeleton data and generate corresponding skeleton heatmaps. Then, we input skeleton heatmaps and RGB frames to Transformer at different temporal and spatial resolutions. Because the skeleton heatmaps are primary features compared to the original RGB frames, we use fewer attention layers in the skeleton stream. At the same time, two ways are proposed to fuse the information of two streams. Experiments demonstrate that the proposed framework achieves the state of the art on four benchmarks: three widely used datasets, Kinetics400, NTU RGB+D 60, and NTU RGB+D 120, and the fine-grained dataset FineGym99.

Objective: To characterize predictors of patient satisfaction in outpatient radiology, we examined whether patient satisfaction differs across radiology modalities and demographic groups. Methods: A random sampling of Press-Ganey outpatient services surveys for radiology and non-radiology visits from September 2008 to September 2017 were retrospectively analyzed. Composite scores averaged across all Likert items were analyzed as both a continuous variable and a dichotomous variable of dissatisfaction (defined as ≤3 on the 5-point scale). Results: Among 9983 radiology surveys, mammography had higher composite scores than MRI, CT, radiography, US, and NM/PET (p

ABSTRACT: CD4 protein is a single chain transmembrane glycoprotein and has a broad functionality beyond cell-mediated immunity. In this study, we cloned the full-length coding sequence (CDS) of duck CD4 (duCD4) and analyzed its sequence and structure, and expression levels in several tissues. It consists of 1,449 nucleotides and encodes a 482 amino acid protein. The putative protein of duCD4 consisted of an N-terminal signal peptide, three immunoglobulins and one immunoglobulins-like domain in its central, one terminal transmembrane region, and a C-terminal domain of the CD4 T cell receptor. The duCD4 also has the typical signature “CXC” of CD4s. The multiple sequence alignment suggests duCD4 has four potential N-glycosylation sites and the phylogenetic analysis suggests duCD4 shares greater similarity with avian than other vertebrates. Quantitative real-time PCR analysis showed that duCD4 mRNA transcripts are widely distributed in the healthy Cherry Valley duck, and the highest level in the thymus. During the virus infection, the obvious change of duCD4 expression was observed in the spleen, lung and brain, which suggesting that duCD4 could be involved in the host's immune response to multiple types of viruses. Our research studied the characterization, tissue distribution, and antiviral immune responses of duCD4.

Magnesium (Mg) alloys have received increasing interest in the past two decades as biomaterials due to their excellent biological compatibility. However, the corrosion resistance of Mg alloys is relativity low which limits their usage in degradable implant applications, and controlling the corrosion resistance is the key to solving this problem. This review discusses the relative corrosion mechanisms, including pitting, filiform, high temperature, stress corrosion, etc., of Mg alloys. Various approaches like purification (Fe, Ni, Cu, etc.), micro-alloying (adding Zn, Mn, Ca, RE elements, and so on), grain refinement (severe plastic deformation, SPD, etc.), and surface modifications (various coating methods) to control corrosion and biological performance are summarized. Moreover, the in vivo implantations of Mg alloy vascular stents and the issues that have emerged based on the reports in recent years are introduced. It is recommended that corrosion mechanisms should be further investigated as there is no method that can remove all the impurities and a new purification approach needs to be developed. The concentration of micro-alloy elements should be carefully controlled to avoid superfluous compounds. Developing new continuous SPD methods to achieve fine-grained Mg alloys with a large size scale is necessary. The development of a multifunctional coating could also be considered in controlling the Mg degradation rate. Moreover, the research trends and challenges in the future of Mg biomaterials are proposed.

Wearable devices that collect data about human beings are widely used in healthcare applications. Once collected, the health data will be securely transmitted to smartphones in most scenarios. Authenticated Key Exchange (AKE) can protect wireless communications between wearables and smartphones, and a typical solution is the Bluetooth Secure Simple Pairing (SSP) protocol with numeric comparison. However, this protocol requires equivalent computation on both devices, even though their computational capabilities are significantly different. This paper proposes a lightweight numeric comparison protocol for communications in which two parties have unbalanced computational capabilities, e.g., a wearable sensor and a smartphone, named UnBalanced secure Pairing using numeric comparison (UB-Pairing for short). The security of UB-Pairing is analyzed using the modified Bellare–Rogaway model (mBR). The analysis results show that UB-Pairing achieves the security goals. We also carry out a number of experiments to evaluate the performance of UB-Pairing. The results show that UB-Pairing is friendly to wearable devices, and more efficient than standard protocols when the computation capabilities of the two communication parties are highly unbalanced.

The authenticated key exchange (AKE) protocol can ensure secure communication between a client and a server in the electricity transaction of the Energy Internet of things (EIoT). Park proposed a two-factor authentication protocol 2PAKEP, whose computational burden of authentication is evenly shared by both sides. However, the computing capability of the client device is weaker than that of the server. Therefore, based on 2PAKEP, we propose an authentication protocol that transfers computational tasks from the client to the server. The client has fewer computing tasks in this protocol than the server, and the overall latency will be greatly reduced. Furthermore, the security of the proposed protocol is analyzed by using the ROR model and GNY logic. We verify the low-latency advantage of the proposed protocol through various comparative experiments and use it for EIoT electricity transaction systems in a Metaverse scenario.

In indoor low-texture environments, the point feature-based visual SLAM system has poor robustness and low trajectory accuracy. Therefore, we propose a visual inertial SLAM algorithm based on point-line feature fusion. Firstly, in order to improve the quality of the extracted line segment, a line segment extraction algorithm with adaptive threshold value is proposed. By constructing the adjacent matrix of the line segment and judging the direction of the line segment, it can decide whether to merge or eliminate other line segments. At the same time, geometric constraint line feature matching is considered to improve the efficiency of processing line features. Compared with the traditional algorithm, the processing efficiency of our proposed method is greatly improved. Then, point, line, and inertial data are effectively fused in a sliding window to achieve high-accuracy pose estimation. Finally, experiments on the EuRoC dataset show that the proposed PLI-VINS performs better than the traditional visual inertial SLAM system using point features and point line features.

Anomaly detection is the foundation of intelligent operation and maintenance (O&M), and detection objects are evaluated by key performance indicators (KPIs). For almost all computer O&M systems, KPIs are usually the machine-level operating data. Moreover, these high-frequency KPIs show a non-Gaussian distribution and are hard to model, i.e., they are intricate KPI profiles. However, existing anomaly detection techniques are incapable of adapting to intricate KPI profiles. In order to enhance the performance under intricate KPI profiles, this study presents a seasonal adaptive KPI anomaly detection algorithm ASAD (Adaptive Seasonality Anomaly Detection). We also propose a new eBeats clustering algorithm and calendar-based correlation method to further reduce the detection time and error. Through experimental tests, our ASAD algorithm has the best overall performance compared to other KPI anomaly detection methods.

Complex urban systems, such as multi-floor rail transit stations and integrated railway transport hubs, are termed “complex urban public spaces” (CUPSs). These CUPSs facilitate people’s lives, but, at the same time, are threatened by various risks due to their multi-floor structure, dense crowds, high correlation in multi-function, complex facilities, and space openness. The risk events of CUPSs could have a negative influence on public safety and further influence sustainable development. Increasing the resilience of CUPSs is an effective way to respond to risks and guarantee public safety. Therefore, it is necessary to first assess the resilience of CUPSs. In this paper, a six-level comprehensive resilience indicator system was established based on aspects of the essence of resilience. Used in combination with the methods of resilience impact score and fuzzy analytical hierarchy process, the resilience value could be calculated. The Shenzhen North Railway Station (SZ) and the Guangzhou South Railway Station (GZ) were used to validate the proposed methodology. The established resilience indicator system was shown to be comprehensive and innovative, and, regarding practicality, the proposed assessment methodology is convenient to use. This research can help policymakers to assess the resilience of CUPSs and develop relevant policies to improve the resilience of buildings, which can further enhance urban sustainability.

The k-means problem has been paid much attention for many applications. In this paper, we define the uncertain constrained k-means problem and propose a (1+ϵ)-approximate algorithm for the problem. First, a general mathematical model of the uncertain constrained k-means problem is proposed. Second, the random sampling properties of the uncertain constrained k-means problem are studied. This paper mainly studies the gap between the center of random sampling and the real center, which should be controlled within a given range with a large probability, so as to obtain the important sampling properties to solve this kind of problem. Finally, using mathematical induction, we assume that the first j−1 cluster centers are obtained, so we only need to solve the j-th center. The algorithm has the elapsed time O((1891ekϵ2)8k/ϵnd), and outputs a collection of size O((1891ekϵ2)8k/ϵn) of candidate sets including approximation centers.

With the rapid development of high-precision road network maps, low-precision road network maps (basic data unrelated to hardware) will need to be directly produced for traditional navigation software from high-precision maps. To do so, large amounts of vector data representing road networks must be simplified and spatial directional similarity in road networks must be maintained while reducing precision. In this study, an elite strategy genetic algorithm based on the grid model is applied to spatial directional adjustment in road networks for producing road network maps for traditional navigation. Firstly, semantic features and critical vertices are extracted from the road network with high precision. Secondly, some high-precision vertices are eliminated under constraints of the digital navigation map. During this process, the local shape maintenance of the road is considered, and the destruction of the spatial topological relationships is avoided. Thirdly, a genetic algorithm for minimizing the total changes in road azimuths at nodes of road networks is developed to maintain spatial directional relationships while reducing precision. Experimental results and visualization effects on the test data of different cities show that this method is suitable for generating road network maps for traditional navigation software from high-precision ones.

AIM: To analyze the clinical value of femtosecond laser in vitrectomy combined with phacoemulsification and intraocular lens(IOL)implantation. METHODS:We selected 100 patients(102 eyes)undergoing vitrectomy combined with phacoemulsification and IOL implantation in our hospital from October 31 2013 to October 31 2015. They were divided into routine operation group, 50 cases(52 eyes), and femtosecond laser group, 50 cases(50 eyes). The parameters were compared between the two groups, including total operation time, postoperative complications(elevated intraocular pressure, uveitis, vitreous hemorrhage, and retinal detachment), postoperative intraocular pressure and postoperative half of the visual acuity(near visual acuity, visual acuity, uncorrected visual acuity, corrected visual acuity). RESULTS: The difference on total operation time of the two groups was statistically significant(PP>0.05). There were no significant differences on internal pressure, near visual acuity, far visual acuity, uncorrected visual acuity, corrected visual acuity at 6mo after surgery(P>0.05). CONCLUSION: Femtosecond laser in vitrectomy combined with phacoemulsification and IOL implantation has a high safety and efficacy with the advantages as accurate, efficient.

A prevailing neuroinflammation hypothesis is that increased production of proinflammatory cytokines contributes to progressive neuropathology, secondary to the primary damage caused by a traumatic brain injury (TBI). In support of the hypothesis, post-injury interventions that inhibit the proinflammatory cytokine surge can attenuate the progressive pathology. However, other post-injury neuroinflammatory responses are key to endogenous recovery responses. Therefore, it is critical that pharmacological attenuation of detrimental or dysregulated neuroinflammatory processes avoid pan-suppression of inflammation. MW151 is a CNS-penetrant, small molecule experimental therapeutic that restores injury- or disease-induced overproduction of proinflammatory cytokines towards homeostasis without immunosuppression. Post-injury administration of MW151 in a closed head injury model of mild TBI suppressed acute cytokine up-regulation and downstream cognitive impairment. Here, we report results from a diffuse brain injury model in mice using midline fluid percussion. Low dose (0.5-5.0 mg/kg) administration of MW151 suppresses interleukin-1 beta (IL-1β) levels in the cortex while sparing reactive microglia and astrocyte responses. To probe molecular mechanisms, we used live cell imaging of the BV-2 microglia cell line to demonstrate that MW151 does not affect proliferation, migration, or phagocytosis of the cells. Our results provide insight into the roles of glial responses to brain injury and indicate the feasibility of using appropriate dosing for selective therapeutic modulation of injurious IL-1β increases while sparing other glial responses to injury.

In apple cultivation, simulation models may be used to monitor fruit size during the growth and development process to predict production levels and to optimize fruit quality. Here, Fuji apples cultivated in spindle-type systems were used as the model crop. Apple size was measured during the growing period at an interval of about 20 days after full bloom, with three weather stations being used to collect orchard temperature and solar radiation data at different sites. Furthermore, a 2-year dataset (2011 and 2012) of apple fruit size measurements were integrated according to the weather station deployment sites, in addition to the top two most important environment factors, thermal and sunshine hours, into the model. The apple fruit diameter and length were simulated using physiological development time (PDT), an indicator that combines important environment factors, such as temperature and photoperiod, as the driving variable. Compared to the model of calendar-based development time (CDT), an indicator counting the days that elapse after full bloom, we confirmed that the PDT model improved the estimation accuracy to within 0.2 cm for fruit diameter and 0.1 cm for fruit length in independent years using a similar data collection method in 2013. The PDT model was implemented to realize a web-based management information system for a digital orchard, and the digital system had been applied in Shandong Province, China since 2013. This system may be used to compute the dynamic curve of apple fruit size based on data obtained from a nearby weather station. This system may provide an important decision support for farmers using the website and short message service to optimize crop production and, hence, economic benefit.

OBJECTIVE: Pituitary tumor transforming gene (PTTG) is an important paracrine growth factor involved in early lactotrope transformation and early onset of angiogenesis in pituitary hyperplasia. Emerging evidences have shown that PTTG expression may contribute to the etiology of pituitary adenomas; but individually published studies showed inconclusive results. This meta-analysis aimed to derive a more precise estimation of the correlations of PTTG expression with human pituitary adenomas. METHODS: A range of electronic databases were searched: MEDLINE (1966∼2013), the Cochrane Library Database (Issue 12, 2013), EMBASE (1980∼2013), CINAHL (1982∼2013), Web of Science (1945∼2013) and the Chinese Biomedical Database (CBM) (1982∼2013) without language restrictions. Meta-analysis was performed using the STATA 12.0 software. Crude odds ratio (OR) or standard mean difference (SMD) with its corresponding 95% confidence interval (95%CI) were calculated. RESULTS: Twenty-four clinical cohort studies were included with a total of 1,464 pituitary adenomas patients. The meta-analysis results revealed that patients with invasive pituitary adenomas had higher positive expression of PTTG than those of non-invasive patients (OR = 6.68, 95%CI = 3.72-11.99, P0.05). CONCLUSION: This present meta-analysis suggests that PTTG expression may be associated with tumor invasiveness and microvessel density of pituitary adenomas, while no correlations with functional status was found.

The p38 MAPK pathway plays a key role in regulating the production of proinflammatory cytokines, such as TNFα and IL-1β, in peripheral inflammatory disorders. There are four major isoforms of p38 MAPK (p38α, β, δ, γ), with p38α and p38β the targets of most p38 MAPK inhibitor drugs. Our previous studies demonstrated that the p38α MAPK isoform is an important contributor to stressor-induced proinflammatory cytokine up-regulation and neurotoxicity in the brain. However, the potential role of the p38β MAPK isoform in CNS proinflammatory cytokine overproduction and neurotoxicity is poorly understood. In the current studies, we used primary microglia from wild type (WT) and p38β knockout (KO) mice in co-culture with WT neurons, and measured proinflammatory cytokines and neuron death after LPS insult. We also measured neuroinflammatory responses in vivo in WT and p38β KO mice after administration of LPS by intraperitoneal or intracerebroventricular injection. WT and p38β KO microglia/neuron co-cultures showed similar levels of TNFα and IL-1β production in response to LPS treatment, and no differences in LPS-induced neurotoxicity. The in vitro results were confirmed in vivo, where levels of TNFα and IL-1β in the CNS were not significantly different between WT or p38β KO mice after LPS insult. Our results suggest that, similar to peripheral inflammation, p38α is critical but p38β MAPK is dispensable in the brain in regards to proinflammatory cytokine production and neurotoxicity induced by LPS inflammatory insult.

Serine-threonine protein kinases are critical to CNS function, yet there is a dearth of highly selective, CNS-active kinase inhibitors for in vivo investigations. Further, prevailing assumptions raise concerns about whether single kinase inhibitors can show in vivo efficacy for CNS pathologies, and debates over viable approaches to the development of safe and efficacious kinase inhibitors are unsettled. It is critical, therefore, that these scientific challenges be addressed in order to test hypotheses about protein kinases in neuropathology progression and the potential for in vivo modulation of their catalytic activity. Identification of molecular targets whose in vivo modulation can attenuate synaptic dysfunction would provide a foundation for future disease-modifying therapeutic development as well as insight into cellular mechanisms. Clinical and preclinical studies suggest a critical link between synaptic dysfunction in neurodegenerative disorders and the activation of p38αMAPK mediated signaling cascades. Activation in both neurons and glia also offers the unusual potential to generate enhanced responses through targeting a single kinase in two distinct cell types involved in pathology progression. However, target validation has been limited by lack of highly selective inhibitors amenable to in vivo use in the CNS. Therefore, we employed high-resolution co-crystallography and pharmacoinformatics to design and develop a novel synthetic, active site targeted, CNS-active, p38αMAPK inhibitor (MW108). Selectivity was demonstrated by large-scale kinome screens, functional GPCR agonist and antagonist analyses of off-target potential, and evaluation of cellular target engagement. In vitro and in vivo assays demonstrated that MW108 ameliorates beta-amyloid induced synaptic and cognitive dysfunction. A serendipitous discovery during co-crystallographic analyses revised prevailing models about active site targeting of inhibitors, providing insights that will facilitate future kinase inhibitor design. Overall, our studies deliver highly selective in vivo probes appropriate for CNS investigations and demonstrate that modulation of p38αMAPK activity can attenuate synaptic dysfunction.

Laser welding has been considered as a promising method to join sintered NdFeB permanent magnets thanks to its high precision and productivity. However, the influences of laser welding on the magnetic property of NdFeB are still not clear. In the present paper, the effects of laser power on the remanence (Br) were experimentally investigated in laser spot welding of a NdFeB magnet (N48H). Results show that the Br decreased with the increase of laser power. For the same welding parameters, the Br of magnets, that were magnetized before welding, were much lower than that of magnets that were magnetized after welding. The decrease in Br of magnets after laser welding resulted from the changes in microstructures and, in turn, the deterioration of magnetic properties in the nugget and the heat affected zone (HAZ) in a laser weld. It is recommended that the dimensions of nuggets and HAZ in laser welds of a NdFeB permanent magnet should be as small as possible, and the magnets should be welded before being magnetized in order to achieve a better magnetic performance in practical engineering applications.

Two dinuclear cobalt complexes based on bis-diketonate ligands (ligand 1: 3,3'-(1,3-phenylene)bis(1-phenylpropane-1,3-dione); ligand 2: 3,3'-(1,4-phenylene)bis(1-phenylpropane-1,3-dione)) were successfully synthesized. The two neutral catalysts all showed satisfactory activities in the cobalt-mediated radical polymerization (CMRP) of methyl methacrylate (MMA) with the common initiator of azodiisobutyronitrile (AIBN). The resulting polymerizations have all of the characteristics of a living polymerization and displayed linear semilogarithmic kinetic plots, a linear correlation between the number-average molecular weight and the monomer conversion, and low polydispersities. Mono- or dicomponent low polydispersity polymers could be obtained by using the two dinuclear catalysts under proper reaction conditions. All these improvements facilitate the implementation of the acrylate CMRP and open the door to the scale-up of the syntheses and applications of the multicomponent low polydispersity polymers.