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Based on the background of structural protection and Disaster Reduction Engineering, the dynamic behaviour and failure mechanism of restrained beams in portal steel frames in localised fire are investigated via experimental measurement and numerical simulation techniques. Comprehensive parametric studies are carried out to discuss the influence of end connection types, temperature, impact velocity, impact mass and span-to-depth ratio (SDR) on the dynamic response of the beams. The characteristics of deformation, internal force and energy distribution about the restrained beams and its joints are investigated. A temperature dependent criterion for evaluating the frame joint performance is proposed to measure the degree of performance degradation and impact resistance of the joint. The dynamic displacement amplification factor in different temperature environments are proposed for the different beam end constraint types and SDRs. Results of the experimental and numerical analysis show that the welded connection (WC) of three typical joint types is the strongest, and the extended endplate connection (EEC) is the weakest in terms of the impact resistance performance. With regard to the failure mode of the joint, the failure positions of the WC and the welded-bolted connection are located in the inner web of the column. Meanwhile, the EEC is located in the connection position between the beam and the endplate. Three different internal force stages and two obvious critical temperature boundaries of the restrained beams emerge with the increase in temperature, and they have significant characteristics in terms of deformation trend, internal force transfer and energy distribution. During the impact, a phenomenon known as “compression arch action” develops into “catenary action” with the increase in deflection in the frame beam mechanism.

This study examines the impact of urban management on the efficiency of regional innovation in China’s manufacturing industry, with a specific focus on modern sustainable energy. The research takes into consideration the regional diversity in innovation development across China’s three major regions and integrates common Frontier theory with the MSBM model. By employing a non-radial distance function approach, this study develops the MMSBMP model, incorporating various improved methods proposed by researchers. The Luenberger index methodology is utilized to assess the innovation efficiency of the national manufacturing industry from 2017 to 2021, enabling the identification of efficiency losses. The findings highlight significant disparities and opportunities for enhancing innovation efficiency across the three major regions, both at the common Frontier and the group Frontier. However, caution is advised due to the potential overestimation of regional Frontier efficiency values resulting from variations in technical reference datasets. Analysis of the Total Growth Rate (TGR) values reveals distinct development characteristics among the regions, with the eastern region exhibiting smaller extremes and the central and western regions displaying larger extremes. This comprehensive examination of China’s manufacturing industry emphasizes the influence of urban management. By investigating the consequences of urban management practices, this research provides insights into the relationship between urban development strategies and the performance, efficiency, and sustainable growth of the manufacturing industry. The study highlights the significance of urban management in shaping regional innovation efficiency and emphasizes the continual improvement of the industry’s innovation performance in the context of modern sustainable energy.

With the booming development of financial market, financial products are increasing, and the risk is also increasing, leading to the simple pursuit of maximizing returns can no longer meet the needs of investors, so how to choose the appropriate assets to build investment portfolios and weigh their risks and returns to achieve the optimal allocation of assets and maximize the investment returns has become the object of investors’ attention. Markowitz’s portfolio theory is sought after by investors. This paper takes Markowitz mean-variance model as the theoretical framework, on the basis of which the actual data of five stocks and SPX between May 2001 and May 2021 are used, and EXCEL is used to conduct empirical analysis to obtain the weights, minimum standard deviation, and yield curves of each stock, and ultimately the efficient frontier as well as the optimal asset allocation. The research in this paper verifies that Markowitz’s model is still instructive for investors to construct portfolio models in today’s market.

Abstract Background Axillary vein/subclavian vein (AxV/SCV) and Internal jugular vein (IJV) are commonly used for implantable venous access port (IVAP) implantation in breast cancer patients for chemotherapy. Previous research focused on comparison of complications while patient comfort was ignored. This study aims to compare patient comfort, surgery duration and complications of IVAP implantation between IJV and AxV/SCV approaches. Methods Two hundred forty-eight breast cancer patients were enrolled in this randomized controlled study from August 2020 to June 2021. Patients scheduled to undergo IVAP implantation were randomly and equally assigned to receive central venous catheters with either AxV /SCV or IJV approaches. All patients received comfort assessment using a comfort scale table at day 1, day 2 and day 7 after implantation. Patient comfort, procedure time of operation as well as early complications were compared. Results Patient comfort was significantly better in the AxV/SCV group than that of IJV group in day 1 (P

ABSTRACT: Avian pathogenic Escherichia coli (APEC) is a serious systemic infectious disease in poultry infections, causing severe economic losses to the poultry industry. Previous studies have shown that secretion of virulence proteins was required for the pathogenicity of APEC through the secretion system. Outer membrane vesicles (OMVs) are a generalized secretion system of Gram-negative bacteria that play a key role in the long-distance delivery of virulence factors, but whether they are associated with the pathogenic mechanism of APEC has not been determined. In this study, OMVs were purified and characterized from AE17 (O2 serotype) by ultracentrifugation and density gradient centrifugation and their protein cargo was identified using liquid chromatography-tandem mass spectrometry (LC-MS/MS). In addition, 89Zr was labeled after chelating AE17 OMVs by DFO and positron emission tomography PET imaging was used to track 89Zr-DFO-OMVs in chickens and to pathologically analyze the distribution sites. This study showed that AE17 OMVs were membrane vesicles ranging in size from 20 to 200 nm and proteomic analysis revealed the presence of virulence proteins, including adhesion proteins OmpA, OmpC, OmpF, OmpX, FimH, FimC and FigE, and serum resistance proteins OmpT and MliC and immune response regulator proteins (FliC). In addition, in vivo PET imaging to track the biodistribution of AE17 OMVs showed that AE17 OMVs were taken up by the lung region and the gastrointestinal and renal regions but were not detected in other areas. Pathological analysis of the tissue sites where AE17 OMVs were ingested showed inflammatory responses and damage. These findings suggested that AE17 OMVs not only contained a group of virulence proteins associated with AE17 infection but can also deliver these virulence proteins over long distances and caused tissue inflammatory damage. Our study revealed a previously unidentified causative microbial signal in the pathogenesis of APEC that could aid in the development of vaccines and antibiotics effective against APEC.

This study was conducted to evaluate the oligomeric proanthocyanidins (OPC) in alleviating the detrimental effects of intestinal health caused by dietary histamine in juvenile American eels (Anguilla rostrata). A total of 480 fish with a similar body weight of 10.84 ± 0.16 g were randomly divided into four groups, and there were the control group fed a basal diet, the HIS group fed a diet with a high level of histamine (534 mg/kg), the H + OPC I group fed the high histamine diet with 300 mg/kg OPC, and the H + OPC II group fed the high histamine diet with 600 mg/kg OPC, respectiviely. After the fish were fed the trial diets for 77 days, the intestinal samples were taken, and the related parameters of intestinal health were analyzed. Dietary 300 mg/kg or 600 mg/kg OPC could reverse the decreased activities of lipase, protease, and glutathione peroxidase and the level of total antioxidant capacity, the increased intestinal malondialdehyde and D-lactate acid levels and the activity of diamine oxidase in serum, and the decreased villus height caused by a high level of dietary histamine. There were no significant differences above all the indices between the H + OPC I group and the H + OPC II group. The higher relative abundances of potentially pathogenic bacteria were induced by the high level of dietary histamine. Dietary 300 mg/kg OPC might increase the relative abundance of the potential probiotics and inhibit the colonization of intestinal pathogenic bacteria of juvenile American eels exposed to the stress of high dietary hisatamine. The intestinal health status of the H + OPC groups was similar to that of the control group. These results suggested that dietary 300 mg/kg OPC might alleviate the detrimental effects of dietary 534 mg/kg histamine on the intestine health of juvenile American eels by increasing the activity of digestive enzymes, improving the antioxidative potential and barrier function, and beneficially modulating the intestinal microbiota. Dietary 600 mg/kg OPC could not exert further improvement in growth performance and the intestinal health of juvenile American eels.

Cancer is one of the leading causes of death worldwide, bringing a significant burden to human health and society. Accurate cancer diagnosis and biomarkers that can be used as robust therapeutic targets are of great importance as they facilitate early and effective therapies. Shared etiology among cancers suggests the existence of pan-cancer biomarkers, performance of which could benefit from the large sample size and the heterogeneity of the studied patients. In this study, we conducted a systematic RNA-seq study of 9,213 tumors and 723 para-cancerous tissue samples of 28 solid tumors from the Cancer Genome Atlas (TCGA) database, and 7,008 normal tissue samples from the Genotype-Tissue Expression (GTEx) database. By differential gene expression analysis, we identified 214 up-regulated and 186 downregulated differentially expressed genes (DEGs) in more than 80% of the studied tumors, respectively, and obtained 20 highly linked up- and downregulated hub genes from them. These markers have rarely been reported in multiple tumors simultaneously. We further constructed pan-cancer diagnostic models to classify tumors and para-cancerous tissues using 10 up-regulated hub genes with an AUC of 0.894. Survival analysis revealed that these hub genes were significantly associated with the overall survival of cancer patients. In addition, drug sensitivity predictions for these hub genes in a variety of tumors obtained several broad-spectrum anti-cancer drugs targeting pan-cancer. Furthermore, we predicted immunotherapy sensitivity for cancers based on tumor mutational burden (TMB) and the expression of immune checkpoint genes (ICGs), providing a theoretical basis for the treatment of tumors. In summary, we identified a set of biomarkers that were differentially expressed in multiple types of cancers, and these biomarkers can be potentially used for diagnosis and used as therapeutic targets.

As protection for nuclear power plants is quite necessary, the nuclear fuel is sealed in zirconium alloy thin wall cladding. During service, fuel rods might be damaged caused by wall-thickness thinning, cladding corrosion and cracking, etc. This will cause the coolant to enter into the fuel rod, which may lead to the failure of the fuel assembly. However, current diagnostic methods have limitations due to the special structure of the fuel assembly and the underwater and radioactive environment. In this paper, a novel inspection method is proposed to recognize the failure of a fuel rod. The fuel rod failure can be detected based on the presence or absence of coolant inside the fuel rod by using an ultrasonic plate wave. The inspection model and process algorithm are proposed for in-service inspection. The relationship between signal and scanning position is established and analyzed. Both ultrasound field simulation and experiment have been carried out for validation. The corresponding results illustrate that the failed nuclear fuel rod of the whole fuel assembly (including the internal rods) can be effectively detected without the influence of the near-field region by using the proposed method.

Aiming at the limitation of SOC′s pin number, and in security IC applications, on chip capless LDO and on chip decouple capacitor were preferred for suppling digital cores power. But On Chip Capless LDO′s finite bandwidth limited it responses sharp current pulses existed in digital core, huge on chip decouple capacitors of several nano farads are necessary for these situations. These on chip capacitors occupy significant chip area, so these capacitors must be mapped out in the whole chip floorplan and so did LDO designs. In conventional design flow, the on chip capacitor′s size was confirmed after P&R with power simulations at the late design procedure, which results in iterations of LDO design and whole chip floorplan distribution. A new accurate method was given based on deeply understanding digital circuit how to work in order to estimate the values of on chip capacitors at the early procedure of the flow, so the floorplan of the chip and LDO design could be started earlier, the iteration of these procedure was limited to one time. This method was succeeded applied in one SOC design, the post simulation and test results show that the estimated on chip capacitors are very accurate.

As a promising biometric technique, the finger-vein image recognition has seen a recent surge of interest. However, the collected finger-vein images are often degraded seriously because of various vein patterns, uneven illumination, and unsatisfied sensor conditions. This makes vein representations unreliable and inevitably impairs recognition accuracy. In this paper, a new model based on the pulse coupled neural network (PCNN) is proposed to enhance finger-vein image quality, and further to improve the reliability of image recognition. First, a simplified PCNN model for finger-vein image enhancement is proposed to reduce computational complexity. Then, a new parameter setting scheme is developed to automatically adjust the parameters in the present PCNN model, without involving any empirical correlations or training. Finally, extensive experiments are carried out, and the performance of the proposed PCNN model is evaluated by calculating four metrics, including the gradient in the spatial domain (GSG), the gray contrast (GC), the information capacity (IC), and the deep evaluator based on the stacked auto encoder (DESAE). The results have verified the capability and reliability of the presented PCNN model as well as the parameter setting scheme in finger-vein image enhancement. In addition, the enhanced finger-vein images by the present PCNN model have been shown to be able to improve the recognition accuracy significantly.

Space-time adaptive processing (STAP) is a fundamental topic in airborne radar applications due to its clutter suppression ability. Reduced-dimension (RD)-STAP can release the requirement of the number of training samples and reduce the computational load from traditional STAP, which attracts much attention. However, under the situation that training samples are severely deficient, RD-STAP will become poor like the traditional STAP. To enhance RD-STAP performance in such cases, this paper develops a novel RD-STAP algorithm using random matrix theory (RMT), RMT-RD-STAP. By minimizing the output clutter-plus-noise power, the estimate of the inversion of clutter plus noise covariance matrix (CNCM) can be obtained through optimally manipulating its eigenvalues, thus producing the optimal STAP weight vector. Specifically, the clutter-related eigenvalues are estimated according to the clutter-related sample eigenvalues via RMT, and the noise-related eigenvalue is optimally selected from the noise-related sample eigenvalues. It is found that RMT-RD-STAP significantly outperforms the RD-STAP algorithm when the RMB rule cannot be satisfied. Theoretical analyses and numerical results demonstrate the effectiveness and the performance advantages of the proposed RMT-RD-STAP algorithm.

The understanding of the axial tensile behavior of environmentally corroded pipelines is of great significance for the design, maintenance, and evaluation of such structures. This article presents some experimental data recorded from 210 tensile tests on pipe, which were corroded from grade of 10% to 70% by electrochemical accelerated corrosion method. The fracture modes show that, for the uncorroded pipe, the fracture frequently occurs in the middle of the specimen and then propagates perpendicular to the loading direction. However, for the corroded pipe, the crack’s position, evolution angle, and path have strong randomness. The comparative analysis based on the macroscopic stress-strain relationship shows that the rapid decrease of the yield stress, ultimate strength, and strain at the fracture for corroded pipe are correlated with the fracture patterns; i.e., the fracture patterns of pipe are changed from uniform to scattered with the continuous increase of the corrosion rate. The reduction factor based on experimental data is recommended for the consideration of the corrosion effect on the tensile strength of the steel pipe. Discussion on the tensile capacity during the service time is also presented.

The experimental part in this companion paper revealed that the macroscopic mechanical performance of corroded pipes follows a decreasing trend with the increasing corrosion rate. Inspired by the surface topology by scanning electronic microscopy (SEM) and the scattered distribution of test data, a computational procedure based on the Monte Carlo simulation method was developed in this paper to understand the randomness of the crack propagation process and the performance degradation mechanism of the corroded pipelines. A total of 2700 random samples, which contain three corrosion rates of 15%, 45%, and 70% with each corrosion rate having three variances of 0.02 mm, 0.06 mm, and 0.10 mm, were generated and then were mapped to the shell section of the FE model. In the application of the material model considering the damage, a series of “numerical” tensile experiments were carried out. The simulation analysis indicated that the corrosion rate and the standard variance of the thickness collaboratively dominated the mechanical performance of the corroded specimen. Under the same standard deviation, the wall corresponding to the higher corrosion rate is more likely to cause stress concentration in the weak position, which makes the pipe more prone to fail. Furthermore, under the same corrosion rate, the increase of the standard deviation will aggravate the unevenness of the wall thickness distribution, and then the lower tensile load will cause damage at weak locations and lead to randomness of the crack propagation path, thereby reducing the pipe’s macroscopic strength and fracture strain. The analytical methods in this paper have the potential of being a useful tool for structural reliability assessments of aged pipelines and the full life cycle design of new pipeline networks.

The principle of data power failure protection for non-volatile memory(NVM) of security chip is analyzed. Considering that the processing speed of software can not meet the performance requirements of security chip for data storage, this paper proposes a NVM data implemented in hardware for power failure protection solution. The scheme adopts a ping-pong structure and takes two Flash spaces of the same size in turn as the target area and the backup area. After each update is completed, the backup flag and the number of backups need to be updated. If the chip is powered off during the update, after comparing the backup codes and backup times of the two areas after power-on again, it can be determined which area of the data is valid. This scheme can not only ensure that the data of the security chip non-volatile memory(NVM) is not lost, but also can improve the performance of NVM data update.

In multiband/multifunction radars, the received echoes are usually multiband signals consisting of several subbands with different carrier frequencies. Digital acquisition of the in-phase and quadrature (I and Q) components of each subband is important for the extraction of radar targets. However, the existing acquisition methods are inefficient because their sampling rates are at least twice of the effective bandwidth, also known as the Landau rate. In this paper, we merge the quadrature compressive sampling into the uniform sampling technique for multiband signals, and develop a multiband quadrature compressive sampling (MQuadCS) system. The MQuadCS system first applies the random modulation to generate a compressive multiband signal, and then utilizes the uniform sampling to output the samples of the compressive multiband signal at its Landau rate. As the Landau rate of the compressive multiband signal is much less than that of the received echo, the MQuadCS achieves the sub-Landau rate sampling. With the assumption of sparse targets, the I and Q components of each subband can be independently recovered by the corresponding samples separated from the compressive multiband samples. For the independent recovery, we establish the model of MQuadCS system parameters and provide a sufficient condition to ensure the existence of the system parameters. To guarantee successful recovery of each subband, we introduce the frequency domain representation of the MQuadCS and then derive the reconstructability condition via restricted isometry property analysis. Furthermore, we design a system parameter optimization scheme to improve the recovery performance. Theoretical analyses and simulations validate the efficiency of the MQuadCS system.

Objective To study the correlation between coinfection of Epstein⁃Barr virus (EBV) and Porphyromon⁃ as gingivalis(Pg) and severity of maternal chronic periodontitis in pregnant women. Methods Saliva samples were collected from 36 pregnant women with chronic periodontitis and 36 pregnant women with healthy periodontal status. EBV was detected using nested polymerase chain reaction (PCR), Pg was detected using 16S rRNA based PCR. Clini⁃ cal periodontal indices were recorded through periodontal examination. Correlation between the coinfection and severity of maternal chronic periodontitis were analyzed. Results The results showed no significant differences in prevalence of infection of EBV or Pg between pregnant women with chronic periodontitis and with healthy periodontal status (P＞ 0.05). Contemporaneously, coinfection prevalence of EBV and Pg showed significant differences between two groups (P = 0.028). Coinfection of EBV and Pg showed significant association with bleeding on probing index (BOP) (P = 0.003). No significant associations were found between the coinfection and periodontal depth(PD) or clinical attachment loss (CAL) (P＞0.05). Conclusion Relationship between coinfection of EBV and Pg and maternal chronic periodonti⁃ tis needs further investigation.

This study employs experiments and numerical simulation to analyze the dynamic response of steel beams under huge-mass impact. Results show that lateral torsional buckling (LTB) occurs for a narrow rectangular cross-section steel beam under transverse impact. The experiments were simulated using LS-DYNA. The numerical simulation is in good agreement with experimental results, thus indicating that the LTB phenomenon is the real tendency of steel beams under impact. Meanwhile, the study shows that LS-DYNA can readily predict the LTB of steel beams. A numerical simulation on the dynamic response of H-shaped cross-section steel beams under huge-mass impact is conducted to determine the LTB behavior. The phenomenon of dynamic LTB is illustrated by displacement, strain, and deformation of H-shaped steel beams. Thereafter, a parametric study is conducted to investigate the effects of initial impact velocity and momentum on LTB. The LTB of H-shaped cross-section steel beams under transverse impact is primarily dependent on the level of impact kinetic energy, whereas impact momentum has a minor effect on LTB mode.

Dynamic compression experiments of bismuth (Bi) in a shock pressure range of 38-100 GPa were conducted using an explosive drive. The time-resolved particle velocity profiles at the Bi/LiF (lithium fluoride) interface and the impact velocities were recorded with a displacement interferometer system for any reflector (DISAR). Shock velocities of Bi were measured based on the shorted-pin technique. Sound velocities of Bi were obtained from the peak state time duration measurements with the overtake method. Uncertainties in the measured Hugoniots and sound velocities were analyzed carefully. The new Hugoniot relation, Us = (1.666 ± 0.057) km/s + (1.596 ± 0.037)Up (1.13 km/s ≤Up≤2.05 km/s), was determined by fitting the measured shock velocity and particle velocity to a line. The relation between the Grüneisen coefficient and the density, γρ=const., is found to be a good approximation to describe the sound velocities of Bi above the shock-induced melting pressure, by carefully analysis of the sound velocity data.

This paper presents an efficient sampling system for the acquisition of synthetic aperture radar (SAR) data at sub-Nyquist rate. The system adopts a quadrature compressive sampling architecture, which uses modulation, filtering, sampling and digital quadrature demodulation to produce sub-Nyquist or compressive measurements. In the sequential transmit-receive procedure of SAR, the analog echoes are modulated by random binary chipping sequences to inject randomness into the measurement projection, and the chipping sequences are independent from one observation to another. As a result, the system generates a sequence of independent structured measurement matrices, and then the resulting sensing matrix has better restricted isometry property, as proved by theoretical analysis. As a standard recovery problem in compressive sensing, image formation from the sub-Nyquist measurements has significantly improved performance, which in turn promotes low sampling/data rate. Moreover, the resulting sensing matrix has structures suitable for fast matrix-vector products, based on which we provide a first-order fast image formation algorithm. The performance of the proposed sampling system is assessed by synthetic and real data sets. Simulation results suggest that the proposed system is a valid candidate for sub-Nyquist SAR.

Radiometer systems and a Michelson interferometer, have been operated routinely to detect the elec-tron cyclotron emission (ECE) from EAST plasmas for diagnosing the local electron temperature. A common quasi-optical antenna placed inside the vacuum vessel is employed to collect and focus the plasma emission, and the line of sight is along a radial chord. All of the systems are located in a diagnostic room where the plasma emission is transmitted by overmoded corrugated waveguide. In-situ absolute intensity calibration has been carried out for both the radiometer systems and the Michelson interferometer independently, to ensure that the ECE diagnostic provides an independent electron temperature measurement. In order to diagnose the small-amplitude electron temperature fluctuation, a correlation ECE (CECE) diagnostic has been designed and commissioned recently. The CECE diagnostic employs an independent antenna system which has improved poloidal resolution. A synthetic diagnostic is realized by using the simulation code SPECE to interpret the ECE data in plasmas with non-Maxwellian distribution, and preliminary results imply that the ECE data could be still useful as a localized measurement in plasmas with non-thermal electrons, such as the LHW-heated plasmas on EAST.

The existing whip tail drive size parameter is obtained in the prototype a number of orthogonal experiments to obtain a value. In this paper, a new method is proposed. According to the resistance theory, a propulsive force calculation model is established, and then the local optimal solution is obtained through the combination of finite element method and genetic algorithm. The calculation is small and the thinking is clear. The obtained parameters are of reference to the prototype experiment.

Because the new Proton platform from Life Technologies produced markedly different data from those of the Illumina platform, the conventional Illumina data analysis pipeline could not be used directly. We developed an optimized SNP calling method using TMAP and GATK (OTG-snpcaller). This method combined our own optimized processes, Remove Duplicates According to AS Tag (RDAST) and Alignment Optimize Structure (AOS), together with TMAP and GATK, to call SNPs from Proton data. We sequenced four sets of exomes captured by Agilent SureSelect and NimbleGen SeqCap EZ Kit, using Life Technology's Ion Proton sequencer. Then we applied OTG-snpcaller and compared our results with the results from Torrent Variants Caller. The results indicated that OTG-snpcaller can reduce both false positive and false negative rates. Moreover, we compared our results with Illumina results generated by GATK best practices, and we found that the results of these two platforms were comparable. The good performance in variant calling using GATK best practices can be primarily attributed to the high quality of the Illumina sequences.

Recent longitudinal studies of glioblastoma (GBM) have demonstrated a lack of apparent selection pressure for specific DNA mutations in recurrent disease. Single-cell lineage tracing has shown that GBM cells possess a high degree of plasticity. Together this suggests that phenotype switching, as opposed to genetic evolution, may be the escape mechanism that explains the failure of precision therapies to date. We profiled 86 primary-recurrent patient-matched paired GBM specimens with single-nucleus RNA, single-cell open-chromatin, DNA and spatial transcriptomic/proteomic assays. We found that recurrent GBMs are characterized by a shift to a mesenchymal phenotype. We show that the mesenchymal state is mediated by activator protein 1. Increased T-cell abundance at recurrence was prognostic and correlated with hypermutation status. We identified tumor-supportive networks of paracrine and autocrine signals between GBM cells, nonmalignant neuroglia and immune cells. We present cell-intrinsic and cell-extrinsic targets and a single-cell multiomics atlas of GBM under therapy.