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Abstract Optoelectronic stability of halide perovskite material in hostile conditions such as water is rather limited, preventing them from further industrial deployment. Here, we optimize and perform machine learning analysis on CH3NH3PbI3 materials with additives, solvents and post-treatment molecules using combined experimental and data-driven methods. A champion system consisting of a compatible tertiary molecular combination ‘calcein+PbBr2 + DMSO’ active at diverse surfaces is identified, delivering a large aqueous photoelectrochemical (PEC) photocurrent of 10-5 A/cm2 and an improved aqueous stability of 92.5%. Subsequently, machine interpretation is provided to decouple the multi-molecule contributions with the assistance of genetic programming (GP) and extra-trees (ET) machine learning models, highlighting the intricate molecular features for the target outputs. The post-hoc density functional theory (DFT) calculation suggests the presence of multiple hydrogen bond and anion··π surface interactions to stabilize the interfacial structures. The present ‘PEC + GP + ET + DFT’ approach is suggested to be an effective approach to design and comprehensively evaluate molecule-modified materials.

In order to reduce the deformation resistance, the rolling process of metastable β titanium alloys is generally carried out in the β single-phase state, which causes the problem of non-uniform grain size during the subsequent annealing process, thus affecting the alloy properties. Here we first solution-treated the as-cast Ti–15Mo–3Al-2.7Nb-0.2Si alloy at 740 °C to obtain α + β phase, then cold rolled it with a reduction of 60 %, and finally annealed it at 710–810 °C for 2–240min. Characterization of the annealed metastable β alloy revealed that α phase was involved in the rolling deformation at the same time and recrystallized on the β matrix during the subsequent annealing process, known as equiaxial dispersion, which impeded the recrystallization of the β grains, and ultimately an ultrafine crystalline microstructure of α + β phases with an average grain size of less than 2 μm was obtained.

Abstract Porcine reproductive and respiratory syndrome virus (PRRSV) is a viral pathogen with substantial economic implications for the global swine industry. The existing vaccination strategies and antiviral drugs offer limited protection. Replication of the viral RNA genome encompasses a complex series of steps, wherein a replication complex is assembled from various components derived from both viral and cellular sources, as well as from the viral genomic RNA template. In this study, we found that ZNF283, a Krüppel-associated box (KRAB) containing zinc finger protein, was upregulated in PRRSV-infected Marc-145 cells and porcine alveolar macrophages and that ZNF283 inhibited PRRSV replication and RNA synthesis. We also found that ZNF283 interacts with the viral proteins Nsp9, an RNA-dependent RNA polymerase, and Nsp10, a helicase. The main regions involved in the interaction between ZNF283 and Nsp9 were determined to be the KRAB domain of ZNF283 and amino acids 178–449 of Nsp9. The KRAB domain of ZNF283 plays a role in facilitating Nsp10 binding. In addition, ZNF283 may have an affinity for the 3' untranslated region of PRRSV. These findings suggest that ZNF283 is an antiviral factor that inhibits PRRSV infection and extend our understanding of the interactions between KRAB-containing zinc finger proteins and viruses.

High intraocular pressure causes retinal ganglion cell injury in primary and secondary glaucoma diseases, yet the molecular landscape characteristics of retinal cells under high intraocular pressure remain unknown. Rat models of acute hypertension ocular pressure were established by injection of cross-linked hyaluronic acid hydrogel (Healaflow®). Single-cell RNA sequencing was then used to describe the cellular composition and molecular profile of the retina following high intraocular pressure. Our results identified a total of 12 cell types, namely retinal pigment epithelial cells, rod-photoreceptor cells, bipolar cells, Müller cells, microglia, cone-photoreceptor cells, retinal ganglion cells, endothelial cells, retinal progenitor cells, oligodendrocytes, pericytes, and fibroblasts. The single-cell RNA sequencing analysis of the retina under acute high intraocular pressure revealed obvious changes in the proportions of various retinal cells, with ganglion cells decreased by 23%. Hematoxylin and eosin staining and TUNEL staining confirmed the damage to retinal ganglion cells under high intraocular pressure. We extracted data from retinal ganglion cells and analyzed the retinal ganglion cell cluster with the most distinct expression. We found upregulation of the B3gat2 gene, which is associated with neuronal migration and adhesion, and downregulation of the Tsc22d gene, which participates in inhibition of inflammation. This study is the first to reveal molecular changes and intercellular interactions in the retina under high intraocular pressure. These data contribute to understanding of the molecular mechanism of retinal injury induced by high intraocular pressure and will benefit the development of novel therapies.

Dielectric optical antennas have emerged as a promising nanophotonic architecture for manipulating the propagation and localization of light. However, the optically induced Mie resonances in an isolated nanoantenna are normally with broad spectra and poor Q-factors, limiting their performances in sensing, lasing, and nonlinear optics. Here, we dramatically enhance the Q-factors of Mie resonances in silicon (Si) nanoparticles across the optical band by arranging the nanoparticles in a periodic lattice. We select monocrystalline Si with negligible material losses and develop a unique method to fabricate nanoparticle arrays on a quartz substrate. By extinction dispersion measurements and electromagnetic analysis, we can identify three types of collective Mie resonances with Q-factors ∼ 500 in the same nanocylinder arrays, including surface lattice resonances, bound states in the continuum, and quasi-guided modes. Our work paves the way for fundamental research in strong light-matter interactions and the design of highly efficient light-emitting metasurfaces.

Addressing the impact of near-field effects in the Controlled Source Electromagnetic Method(CSEM) has long been a focal point in the realm of geophysical exploration. Therefore, we propose a deep learning-based near-field correction method for controlled-source electromagnetic methods. Initially, diverse datasets for a layered geologic model are generated through forward simulation. Building upon the characteristics of near-field effects, a deep learning network utilizing LSTM-CNN is meticulously constructed. Multiple experiments are executed to scrutinize the network's effectiveness in mitigating near-field effects and its resilience against noise. Following this, the proposed method is applied to actual CSEM data to validate its applicability in practice. The method is subsequently tested on measured CSEM data, confirming its practical efficacy. Results from experiments indicate that, for theoretical data, the LSTM-CNN network-trained data closely aligns with simulated data, showcasing a significant improvement. Moreover, when applied to measured data, the method eradicates false high-resistance anomalies at lower frequencies. In conclusion, this deep learning-based correction method proficiently eliminates the influence of near-field effects in the CSEM, delivering practical application benefits that more accurately reflect the authentic geologic structure.

Abstract The unique band structure of monolayer transition metal dichalcogenides (TMDC) provides an important platform for spintronic and valleytronic devices. Various approaches, such as in‐plane electric field and out‐of‐plane magnetic field, have been proposed to actively control the valley polarization. In this work, we propose a synergistic effect involving chiral near‐field interactions and hot carrier injection to actively control the valley polarization emission of WSe2 at room temperature (RT). The degree of valley polarization is enhanced from near zero (for pure WSe2) to 20% under non‐resonant optical excitation (532 nm) when monolayer WSe2 is coupled with the chiral near field of plasmonic metasurface. More importantly, the application of near‐infrared light (wavelength of 970 to 1600 nm) illumination further enhances the valley polarization from 20% to 30%, which is attributed to plasmonic‐induced hot carrier injection from the metasurface to WSe2. The synergistic effect of the chiral near field and infrared light pumping offers another strategy to manipulate the valley polarization emission in monolayer TMDs at room temperature, paving the way for future applications of opto‐valleytronic/spintronic devices based on these 2D materials.

The velocity interferometer system for any reflector (VISAR) coupled with a streaked optical pyrometer (SOP) system is used as a diagnostic tool in inertial confinement fusion (ICF) experiments involving equations of state and shock timing. To validate the process of adiabatically compressing the fuel shell through precise tuning of shocks in experimental campaigns for the double-cone ignition (DCI) scheme of ICF, a compact line-imaging VISAR with an SOP system is designed and implemented at the Shenguang-II upgrade laser facility. The temporal and spatial resolutions of the system are better than 30 ps and 7 μm, respectively. An illumination lens is used to adjust the lighting spot size matching with the target size. A polarization beam splitter and λ/4 waveplate are used to increase the transmission efficiency of our system. The VISAR and SOP work at 660 and 450 nm, respectively, to differentiate the signals from the scattered lights of the drive lasers. The VISAR can measure the shock velocity. At the same time, the SOP system can give the shock timing and relative strength. This system has been used in different DCI campaigns, where the generation and propagation processes of multi-shock are carefully diagnosed.

Double-cone ignition [Zhang et al., Phil. Trans. R. Soc. A 378, 20200015 (2020)] was proposed recently as a novel path for direct-drive inertial confinement fusion using high-power lasers. In this scheme, plasma jets with both high density and high velocity are required for collisions. Here we report preliminary experimental results obtained at the Shenguang-II upgrade laser facility, employing a CHCl shell in a gold cone irradiated with a two-ramp laser pulse. The CHCl shell was pre-compressed by the first laser ramp to a density of 3.75 g/cm3 along the isentropic path. Subsequently, the target was further compressed and accelerated by the second laser ramp in the cone. According to the simulations, the plasma jet reached a density of up to 15 g/cm3, while measurements indicated a velocity of 126.8 ± 17.1 km/s. The good agreements between experimental data and simulations are documented.

Abstract Background Cardiovascular disease was the most common disease among the elderly with high morbidity and mortality. Circ_0004104 was demonstrated to be involved in the regulation of atherosclerosis. Methods Quantitative real-time polymerase chain reaction was employed to measure the expression of circ_0004104, miR-942-5p and Rho associated coiled-coil containing protein kinase 2 (ROCK2). Cell proliferation was tested by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay. Cell apoptosis was measured by flow cytometry, and tube formation assay was used to detect the angiogenesis ability of cells. Western blot assay was performed to assess protein levels. Enzyme‑linked immunosorbent assay was used to detect the release of IL-1β and TNF-α. The relationship between miR-942-5p and circ_0004104 or ROCK2 was identified by dual-luciferase reporter assay, RNA immunoprecipitation (RIP) assay, and RNA pull-down assay. Results Oxidized low-density lipoprotein (ox-LDL) inhibited the proliferation of human umbilical vein endothelial cells (HUVECs) and promoted apoptosis in a dose-dependent manner. Circ_0004104 was increased in serum of atherosclerosis patients and ox-LDL-treated HUVECs, and silence of circ_0004104 promoted the proliferation of ox-LDL-exposed HUVECs and inhibited cell apoptosis. MiR-942-5p downregulation reversed si-circ_0004104-mediated influences in HUVECs upon ox-LDL exposure. ROCK2 was the target of miR-942-5p and circ_0004104 regulated the expression of ROCK2 through sponging miR-942-5p. ROCK2 abated the influences of miR-942-5p in ox-LDL-stimulated HUVECs. Circ_0004104 was increased in the exosomes derived from ox-LDL-exposed HUVECs, and the expression of circ_0004104 was promoted in HUVECs after stimulation with ox-LDL-treated HUVECs cells-derived exosomes. Conclusion Circ_0004104 downregulation receded ox-LDL-induced injury in HUVECs through miR-942-5p and ROCK2.

A fall k-coloring of a graph G is a proper k-coloring of G such that each vertex has at least one neighbor in each of the other color classes. A graph G which has a fall k-coloring is equivalent to having a partition of the vertex set V(G) in k independent dominating sets. In this paper, we first prove that for any fall k-colorable graph G with order n, the number of edges of G is at least (n(k−1)+r(k−r))/2, where r≡n(modk) and 0≤r≤k−1, and the bound is tight. Then, we obtain that if G is k-colorable (k≥2) and the minimum degree of G is at least k−2k−1n, then G is fall k-colorable and this condition of minimum degree is the best possible. Moreover, we give a simple proof for an NP-hard result of determining whether a graph is fall k-colorable, where k≥3. Finally, we show that there exist an infinite family of fall k-colorable planar graphs for k∈{5,6}.

Transition metal dichalcogenides (TMDCs) are interesting for nanophotonic applications due to their high refractive index and excitonic properties. Here, the authors report a scalable bottom-up fabrication method to realize arrays of TMDC metastructures showing dielectric optical modes and self-coupled exciton-polaritons.

Introduction: Enlarged perivascular spaces (EPVS) are considered early manifestations of impaired clearance mechanisms in the brain; however, it is unclear whether EPVS they are associated with the development of malignant cerebral edema (MCE) after large hemispheric infarction (LHI). Therefore, we investigated the predictive value of EPVS in predicting MCE in LHI. Methods: Patients suffering from acute LHI were consecutively enrolled. EPVS were rated after the stroke with validated rating scales from magnetic resonance imagess. Patients were divided into two groups according to the occurrence of MCE. Logistic regression was used to analyze the relationship between EPVS and MCE in the basal ganglia (BG) and centrum semiovale (CS) regions. Receiver operating characteristic (ROC) curves assessed the ability of EPVS individually and with other factors in predicting MCE. Results: We included a total of 255 patients, of whom 98 were MCE patients (58 [59.2%] males, aged 70 [range=61.75-78] years) and found that atrial fibrillation, National Institutes of Health Stroke Scale score, infarct volume, neutrophil-lymphocyte ratio, and moderate-to-severe CS-EPVS were positively associated with MCE. After adjusting for confounds, moderate-to-severe CS-EPVS remained independent risk factor of MCE (odds ratio=16.212, p＜0.001). According to the ROC analysis, MCE was highly suspected when CS-EPVS > 14 (sensitivity=0.82, specificity=0.48), and the guiding value were higher when CS-EPVS combined with other MCE predictors (area under the curve=0.90, sensitivity=0.74, specificity=0.90). Conclusion: CS-EPVS were important risk factor for MEC in patients with acute LHI and can help identify patients at risk for MCE.

Soil fungal communities play crucial roles in mediating the functional associations between above- and belowground components during forest restoration. Forest restoration shapes the alterations in plant and soil environments, which exerts a crucial effect on soil fungal assemblages. However, the changes, assembly processes, and driving factors of soil fungi communities during tropical forest restoration are still uncertain. We used Illumina high-throughput sequencing to identify the changes of soil fungal communities across a tropical secondary forest succession chronosequence (i.e., 12-, 42-, and 53-yr stages) in Xishuangbanna. During forest restoration, the dominant taxa of soil fungi communities shifted from r- to K-strategists. The relative abundance of Ascomycota (r-strategists) decreased by 10.0% and that of Basidiomycota (K-strategists) increased by 4.9% at the 53-yr restoration stage compared with the 12-yr stage. From the 12-yr to 53-yr stage, the operational taxonomic unit (OTU), abundance-based coverage estimator (ACE), Chao1, and Shannon index of fungal communities declined by 14.5–57.4%. Although the stochastic processes were relatively important in determining fungal assemblages at the late stage, the fungal community assembly was dominated by deterministic processes rather than stochastic processes. The shifts in soil properties resulting from tropical forest restoration exerted significant effects on fungal composition and diversity. The positive effects of microbial biomass carbon, readily oxidizable carbon, and soil water content explained 11.5%, 9.6%, and 9.1% of the variations in fungal community composition, respectively. In contrast, microbial biomass carbon (40.0%), readily oxidizable carbon (14.0%), and total nitrogen (13.6%) negatively contributed to the variations in fungal community diversity. Our data suggested that the changes in fungal composition and diversity during tropical forest restoration were primarily mediated by the positive or negative impacts of soil carbon and nitrogen pools.

This paper presents a novel magnetic twisting device with a coaxial double rotor based on non-contact transmission characteristics of magnetic drive technology. When the twisting device rotates one cycle, the yarn can get triple twists. This means the new device can twist three times more than what the traditional single twist does. The structure of the magnetic twisting device is designed according to the twisting principle. The influence of main structural parameters on the magnetic torque is analyzed. To optimize the maximum transmission torque and the minimum magnet volume, the multi-objective optimization design model for the twisting device is established. Main parameters such as the relative angle of active disc assembly and passive disc assembly, the thickness of magnet, and the average radius of the magnet distribution are optimized by NSGA-II algorithm. Optimization results show that the proposed structural optimization design of a twisting device based on the magnetic drive has excellent performance and is effective for industrial application.

Multi-source ecological risks have induced many ecological pollution problems that cannot be ignored and seriously threaten regional ecological security. Constructing and optimizing the landscape pattern is beneficial to improve watershed ecosystem services. In this study, an innovative method is proposed to construct and optimize the landscape pattern, which takes Luojiang-Small Creek watershed as an example. 10-meter high-precision raster elements are selected as the basic unit for landscape ecological risk evaluation, and 20 evaluation factors are selected from three dimensions of “natural environment-human society-landscape pattern” to establish the evaluation index system. The spatial principal component-redundancy analysis (SPCA-RDA) was used to comprehensively evaluate the landscape ecological risk in 2019, and the minimum cumulative resistance model (MCR) and gravity model were used to optimize the landscape pattern of the watershed. The results show (1) Human social and landscape pattern factors have a more significant influence on the integrated ecological risk, while natural factors, except for soil type and vegetation cover, have a weaker influence on the integrated ecological risk. (2) The overall landscape ecological risk is low, and the area of the mild landscape ecological risk zone is 259.89 km2, accounting for 81.68 % of the study area. According to the MCR model and gravity model, forest land with an area larger than 1 km2 and water bodies and grassland with an area larger than 0.01 km2 were identified as ecological source sites. (3) 17 potential ecological corridors were constructed, including 4 road-type corridors, 9 green belt-type corridors and 4 river-type corridors, with a total length of 68.72 km, and 22 potential ecological nodes were identified, including 8 A-type ecological nodes and 14 B-type ecological nodes. A comprehensive three-dimensional spatial ecological network of “ecological nodes-ecological corridors-ecological zones” was constructed, and the optimization effect of the landscape pattern in the study area was evaluated, and it was found that the optimized landscape pattern had significantly improved in terms of connectivity. The results of the study provide ecological protection and planning guidance for future risk prevention and control and landscape pattern optimization of the area with watershed as a unit.

Retinal degeneration causes vision loss and threatens the health of elderly individuals worldwide. Evidence indicates that the activation of the complement system is associated with retinal degeneration. However, the mechanism of complement signaling in retinal degeneration needs to be further studied. In this study, we show that the expression of C3 and C3a receptor (C3ar1) is positively associated with the inflammatory response and retinal degeneration. Genetic deletion of C3 and pharmacological inhibition of C3ar1 resulted in the alleviation of neuroinflammation, prevention of photoreceptor cell apoptosis and restoration of visual function. RNA sequencing (RNA-seq) identified a C3ar1-dependent network shown to regulate microglial activation and astrocyte gliosis formation. Mechanistically, we found that STAT3 functioned downstream of the C3-C3ar1 pathway and that the C3ar1-STAT3 pathway functionally mediated the immune response and photoreceptor cell degeneration in response to oxidative stress. These findings reveal an important role of C3ar1 in oxidative-induced retinal degeneration and suggest that intervention of the C3ar1 pathway may alleviate retinal degeneration.

Salmonella enterica serovar Gallinarum biovars Pullorum (S. Pullorum) is an infectious bacterial pathogen in the poultry industry that causes systemic pullorum disease. This disease causes great losses in terms of the clinical production and quality of chicken products in breeding farms. However, an acknowledged usable rapid detection method for its specific identification has not been reported, and it is generally difficult to distinguish from fowl typhoid caused by Salmonella enterica serovar Gallinarum biovars Gallinarum. The development of a specific and rapid detection method for this pathogen is therefore needed. In the present study, we targeted the single-nucleotide mutation position 237 of the S. Pullorum rfbS gene to develop an enzyme-activated blocked probe for its clinical rapid detection. The method displayed robust specificity and reproducibility, and it achieved minimal detection limits of 21 copies/μL of copy number and 4.53 pg/μL of genomic DNA. Compared with traditional identification and PCR methods, this method performed better for the detection of 100 clinical actual samples and without false negative results. The entire process can be accomplished in a 1-step closed-tube operation, overcomes the difficulties currently associated with S. Pullorum detection, and provides a specific and rapid method with broad application potential for SNP detection.

Salmonella infection causes huge losses in the poultry industry worldwide. With the aim to prevent infectious diseases caused by Salmonella and to achieve rapid visualized Salmonella detection in poultry production, we used cresol red as an indicator to develop a novel visualized loop-mediated isothermal amplification method that targets the Salmonella fimW gene firstly in related field. The detection limit was 7.3 × 101 CFU/mL, and the method was highly specific and showed a high clinical detection rate. The entire reaction can be completed in about 40 min and only requires a water bath at 62°C, which makes the method extremely suitable for application to poultry production.

More and more people talk about so-called Daoist ecological thought. Actually, Daoism does not have a ready-made ecological thought. However, it indeed can act as a vital theoretical resource for constructing such thought. In this article, I will argue how this is possible, and what realm Daoism can attain in the relation between human and nature. I will mainly employ such methods as original problem research, literature analysis and comparative research in the inquiry. Compared with traditional Western metaphysics, Daoist ontology can provide stronger philosophical support for the value and significance of empirical things. In addition, Dao does not dominate things like a personal god with will, but gives them the chance to grow and develop according to their own nature. Lao-Zhuang called on people to imitate this character of Dao. They believed that the primitive nature itself was worthy of respect, and urged us to set limits for ourselves and never to distort things’ natural propensities to suit us. Consequently, natural things are neither overshadowed by a noumenon, nor are they subject to humans’ conquering and abuse, so they are capable of flourishing freely. This is precisely the realm of tianfang which Daoism seeks.

Abstract Background Syndecan-1 (SDC-1) is a crucial membrane proteoglycan, which is confirmed to participate in several tumor cell biological processes. However, the biological significance of SDC-1 in colorectal carcinoma is not yet clear. An objective of this study was to investigate the role of SDC-1 in colorectal carcinoma cells. Methods Expression of SDC-1 in colorectal carcinoma tissues was evaluated by Reverse transcription-quantitative real-time PCR (RT-qPCR) and western blot. After transfection with pcDNA3.1 or pc-SDC-1, the transfection efficiency was measured. Next, SW480, SW620 and LOVO cell viability, apoptosis, migration and adhesion were assessed to explore the effects of exogenous overexpressed SDC-1 on colorectal carcinoma. In addition, the influences of aberrant expressed SDC-1 in Janus kinase 1 (JAK1)/signal transducer and activator of transcription 3 (STAT3) and rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen-activated protein kinase (MEK)/extracellular signal-regulated kinase (ERK) pathways were detected by western blot analysis. Results SDC-1 mRNA and protein levels were down-regulated in human colorectal carcinoma tissues. SDC-1 overexpression inhibited cell proliferation via suppressing CyclinD1 and c-Myc expression, meanwhile stimulated cell apoptosis via increasing the expression levels of B-cell lymphoma-2-associated x (Bax) and Cleaved-Caspase-3. Additionally, SDC-1 overexpression restrained cell migration via inhibiting the protein expression of matrix metallopeptidase 9 (MMP-9), and elicited cell adhesion through increasing intercellular cell adhesion molecule-1 (ICAM-1). Furthermore, SDC-1 overexpression suppressed JAK1/STAT3 and Ras/Raf/MEK/ERK-related protein levels. Conclusions In general, the evidence from this study suggested that SDC-1 suppressed cell growth, migration through blocking JAK1/STAT3 and Ras/Raf/MEK/ERK pathways in human colorectal carcinoma cells.

Abstract Modulation of the embryonic stem cell state is beneficial for elucidating the innate mechanisms of development and regenerative medicine. Ion flux plays important roles in modulating the transition between stemness and differentiation in mouse embryonic stem cells (mESCs). Optogenetics is a novel tool for manipulating ion flux. To investigate the impact of optical stimulation on embryonic stem cells, optogenetically engineered V6.5 mESCs were used to measure the depolarization mediated by ChR2 on the proliferation, self-renewal, and differentiation of mESCs. Blue light stimulation significantly inhibited ChR2-GFP-V6.5 ESC proliferation and disrupted the cell cycle progression, reducing the proportion of cells in the S phase. Interestingly, optical stimulation could inhibit ChR2-GFP-V6.5 ESC self-renewal and trigger differentiation by activating the extracellular regulated protein kinase (ERK) signaling pathway. Our data suggest that membrane potential changes play pivotal roles in regulating the proliferation, self-renewal and initiation of differentiation of mESCs.

Abstract Background In-stent restenosis remains an unresolved issue. Inflammation plays a pivotal role in the process of in-stent restenosis. Significant and positive associations were found between red blood cell distribution width (RDW) and inflammation. But whether there is a close relationship between higher RDW and in-stent restenosis is still not clarified. Methods This retrospective observational study investigated 214 consecutive patients with unstable angina pectoris who underwent successful percutaneous coronary interventions with drug-eluting stents. Patients were divided into three groups according to baseline RDW before percutaneous coronary interventions (low RDW group:≤12.5%; intermediate RDW group:> 12.5% and ≤ 13.5%; high RDW group:> 13.5%). The follow-up angiographies were routinely performed 9–12 months after the initial percutaneous coronary interventions. The multivariate logistic regression analysis was employed to determine the independent predictors of in-stent restenosis. Results The in-stent restenosis rate was significantly higher in group with higher baseline RDW value (12.3, 19.7, 47.7% in low, intermediate, and high RDW groups respectively, P

Implanting rotary blood pumps (RBPs) has become the principal treatment for patients suffering from severe heart failure. There are still many challenges to address for RBP control systems. These problems include meeting the patient’s physiological perfusion, eliminating postoperative complications, as well as debugging the patient’s physiological control system (automatically and indiscriminately). This paper proposes a non-invasive adaptive control system based on the Frank–Starling-like mechanism (NAC-FSL) to solve these problems. This control system uses the motor speed of the rotary blood pump as the only input variable, and the pump flow was estimated by the motor speed for achieving non-invasive detection. Simultaneously, a cardiovascular reference model was developed to provide an appropriate real-time preload for heart failure patients. The Frank–Starling-like control baseline was tracked to obtain the desired reference average pump flow by using the preload. Avoiding suction was done by adopting the control baseline (CLn), which included a flat slope under a high preload. Moreover, the NAC-FSL system could potentially unload the left ventricle and provide a higher pump flow with a smaller error during the exercise state, as compared to the CSC system. Finally, the K value indicating the preload sensitivity in the NAC-FSL controller was optimized to meet the perfusion needs according to the hemodynamic parameters.

Background: Paroxysmal atrial fibrillation can be triggered by non-pulmonary vein foci, such as the superior vena cava. Here, we report the case of a patient with a 6-year history of paroxysmal atrial fibrillation who received cryoballoon ablation in 2012 but relapsed in 2014. He then received cardiac radiofrequency ablation, which successfully isolated the left pulmonary vein and superior vena cava, but the arrhythmia recently relapsed again. The tachycardia was finally successfully terminated by ablation on the free wall without recurrence during a 2-year following up. Conclusion: Superior vena cava isolation may not require ablation isolation with a full circle way and can be accomplished by ablating several connection points between the superior vena cava and the right atrium.

S. Pullorum (Salmonella enterica serovar Gallinarum biovars Pullorum) is an infectious pathogen that causes the acute systemic disease called Pullorum disease in poultry. This disease causes huge losses to the poultry industry and seriously affects the yield and quality of the chicken product. It is not easily distinguishable with fowl typhoid caused by S. Gallinarum (Salmonella enterica serovar Gallinarum biovars Gallinarum), hence the development of a specific and rapid detection method for this pathogen is highly desired. In this study, we propose a novel single-nucleotide polymorphism (SNP) detection strategy termed loop primer probe-introduced loop-mediated isothermal amplification (LP-LAMP) for S. Pullorum detection. Based on the original primer sets, we targeted the nucleotide position 237 of the rfbS gene sequence to design a new modified loop-primer probe with a ribonucleotide insertion, where activity of the enzyme ribonuclease H2 (RNase H2) is only activated when the probe is perfectly complementary, leading to the hydrolytic release of a quencher moiety and thus an amplified signal. The method exhibits robust specificity and a low detection limit as the copy number and genomic DNA is 21 copies/μL and 4.92 pg/μL, respectively. This method showed great performance in real sample testing of 130 samples of embryos, livers, and anal swabs from chickens in poultry farms. The experimental results are mainly consistent with traditional identification methods and a PCR method reported in the past. However, the other two methods still contain some false negative results, while our method is without miss detection. The entire closed-tube reaction process can be accomplished within 40 min at a constant temperature (61°C) without the need for expensive instruments or a complicated operation. The LP-LAMP strategy established in this study not only overcomes the existing difficulties of S. Pullorum rapid detection, it also provides a novel, sensitive, and highly specific detection platform for SNPs that is suitable for clinical use.

Tinplate is widely used in food packaging and chemical packaging. Industrial production continues to reduce the thickness of tinplate steel, which puts higher requirements on the control of inclusions. In this study, compared with traditional detection methods, the Ultrasonic Detection method can analyze the distribution of nonmetallic inclusions in larger size samples, which is closer to the actual production process. The numerical simulation model is established to analyze the flow, heat transfer and solidification behavior of molten steel. The results show: There are two nonmetallic inclusion bands in the sample at the edge of the slab, one is the inner and outer arc side of the sample, and the other is the 1/8 to 1/4 slab thickness region of the inner arc side in the sample. The inclusions in the thickness direction of the slab edge within the range of 1/8 to 1/4 are captured in areas 800 mm to 1400 mm below the meniscus. The solidification of the inner and outer arcs is not symmetrical, which leads to the asymmetrical distribution of inclusions in the inner and outer arcs. This study can provide a reference for improving the tinplate production process.

Progress in cell therapy for retinal disorders has been challenging. Recognized retinal progenitors are a heterogeneous population of cells that lack surface markers for the isolation of live cells for clinical implementation. In the present application, our objective was to use the stem cell factor receptor c-Kit (CD117), a surface marker, to isolate and evaluate a distinct progenitor cell population from retinas of postnatal and adult mice. Here we report that, by combining traditional methods with fate mapping, we have identified a c-Kit-positive (c-Kit+) retinal progenitor cell (RPC) that is self-renewing and clonogenic in vitro, and capable of generating many cell types in vitro and in vivo. Based on cell lineage tracing, significant subpopulations of photoreceptors in the outer nuclear layer and bipolar, horizontal, amacrine and Müller cells in the inner nuclear layer are the progeny of c-Kit+ cells in vivo. The RPC progeny contributes to retinal neurons and glial cells, which are responsible for the conversion of light into visual signals. The ability to isolate and expand in vitro live c-Kit+ RPCs makes them a future therapeutic option for retinal diseases.

Abstract Paris is famous in China for its medicinal value and has been included in the Chinese Pharmacopoeia. Inaccurate identification of these species could confound their effective exploration, conservation, and domestication. Due to the plasticity of the morphological characteristics, correct identification among Paris species remains problematic. In this regard, we report the complete chloroplast genome of P. thibetica and P. rugosa to develop highly variable molecular markers. Comparing three chloroplast genomes, we sought out the most variable regions to develop the best cpDNA barcodes for Paris. The size of Paris chloroplast genome ranged from 162,708 to 163,200 bp. A total of 134 genes comprising 81 protein coding genes, 45 tRNA genes and 8 rRNA genes were observed in all three chloroplast genomes. Eight rapidly evolving regions were detected, as well as the difference of simple sequence repeats (SSR) and repeat sequence. Two regions of the coding gene ycf1, ycf1a and ycf1b, evolved the quickest and were proposed as core barcodes for Paris. The complete chloroplast genome sequences provide more integrated and adequate information for better understanding the phylogenetic pattern and improving efficient discrimination during species identification.

Stimulated reservoir volume (SRV) which is generated by horizontal drilling with multistage hydraulic fracturing governs the production in the shale gas reservoirs. Although microseismic data has been used to estimate the SRV, it is high-priced and sometimes overestimated. Additionally, the effect of stress sensitivity on SRV is not considered in abnormal overpressure areas. Thus, the objective of this work is to characterize subsurface fracture networks with stress sensitivity of permeability through the shale gas well production data of the early flowback stage. The flowback regions are first identified with the flowback data of two shale gas wells in South China. Then, we measured the permeability stress sensitivity of the core after fracturing, coupled to the dynamic relative permeability (DRP) calculation to obtain an accurate and simple DRP curve. After that, a comprehensive model is built considering dynamic two-phase relative permeability function and stress sensitivity. Finally, we compared the calculated results with the microseismic data. The results show that the proposed model could reasonably predict the SRV using the flowback data after fracturing. Additionally, compared with the microseismic data, the stress sensitivity should be included, especially in the abnormal overpressure block. It is believed that this mathematical model is accurate and useful. The work provides an efficient approach to estimate stimulated reservoir volume in the shale gas reservoirs.

The machine learning has been widely used in intelligent data mining. The high-computational complexity of machine learning and huge data volume present challenges to computing platforms. Graphics processor unit (GPU) provides powerful computing support for machine learning but shows different performances under different computing scales and/or different development methods. Analysing the performance of GPUs in different application scenarios helps to improve computing performance. In this study, the matrix multiplication, which is a common and time-consuming computation operation in machine learning, is performed on different data scales and different development methods to analyse the relationship between GPU computing performance with matrix scale and development methods. The experimental data shows that the performance of GPU is not much improved compared with the central processing unit in small-scale data calculation. Also, using a high-level application programming interface for GPU development is less computing-efficient than the GPU programming language computes unified device architecture C.

The on-board target tracking of unmanned aerial vehicle (UAV) relies on on-board computer to process the collected ground image information, and then use the target tracking algorithm to achieve the target tracking function, which provides the user with target position, trajectory and other information. UAVs are limited by load and power consumption. Due to the high resolution and frame rate of UAV's image collection system, traditional target tracking platforms cannot meet the requirements. As a result, the real-time nature of the tracking platform urgently needs to be resolved. This study designs and implements the airborne ground target tracking accelerator for UAV. The kernelised correlation filters (KCFs) algorithm with low computational complexity and precision is selected to achieve the airborne ground target tracking function and its performance bottleneck is analysed. In order to improve the real-time performance of the tracking task processing, the ZYNQ platform based on ARM and field programmable gate arrays is chosen to achieve the hardware acceleration of the KCF algorithm. The KCF algorithm is implemented in hardware using the high-level synthesis technology, and a high-speed data transmission link is established. Experiments show that the design can achieve a tracking rate of more than 30 FPS under 960 × 540 resolution, which meets the real-time requirements of UAV target tracking task.

Salmonella is an important cause of foodborne diseases. This study was undertaken to investigate the prevalence, serotype distribution, antimicrobial resistance, virulence genes, and genetic diversity of Salmonella isolates recovered from fresh duck meat obtained from retail markets in Southern China. In total, 365 samples of fresh duck meat were collected from retail markets in six different cities of Guangdong Province between May 2017 and April 2019. High levels of Salmonella contamination were detected in duck meat (151/365, 41.4%). Twenty-six different Salmonella serotypes were identified: S. Corvallis (n = 25, 16.6%), S. Kentucky (n = 22, 14.6%) and S. Agona (n = 20, 13.3%) were the most prevalent serotypes. All isolates were resistant to at least one antibiotic and 133 (88.1%) isolates exhibited multidrug resistance (MDR). Most (86.1%) Salmonella isolates carried seven classes of virulence-associated genes. This study showed the diversity of Salmonella serotypes and genotypes and the high prevalence of MDR isolates carrying multiple virulence-associated genes among isolates from duck meat obtained from retail markets in Southern China. Isolates from different districts had similar pulsed-field gel electrophoresis (PFGE) patterns indicating that circulating foodborne Salmonella constitutes a potential public health issue across different districts.

Dual-driving systems have been widely adopted in advanced manufacturing machine. Synchronization of the dual-servo systems is crucial for tracking reference trajectories. This article proposes a novel cross-coupled fuzzy logic sliding mode control for the synchronous control of dual-driving feed system. The dynamic model of dual-driving system has been established and the individual proportional–proportional–integral controller is built based on the dynamic model. To increase the synchronous performance, a cross-coupled sliding mode controller is provided based on dual-driving system model. In addition, a continuous saturation function is adopted to reduce chattering. Lyapunov stability criterion is used to analyze the stability of the cross-coupled sliding mode control. Moreover, a fuzzy logic saturation gain control approach is proposed to overcome the low robustness and poor dynamic synchronous performance in the normal cross-coupled control scheme. The adaptive saturation function is designed to eliminate synchronous deviation caused by the process of two axes following each other. Finally, an industrial application of dual-driving system is utilized to prove the effectiveness of the proposed scheme. The proposed cross-coupled fuzzy logic sliding mode control scheme has been effectively demonstrated to improve synchronous performance and tracking accuracy.

Salmonella enterica serovar Kentucky (S. Kentucky) sequence type 198 has emerged as a global zoonotic pathogen. We explored Salmonella enterica serovar Kentucky ST198 samples from the broiler chicken supply chain and patients between 2010 and 2016. Here, we collected 180 S. Kentucky isolates from clinical cases and the poultry supply chain. We performed XbaI pulsed-field gel electrophoresis and multilocus sequence typing. We assessed mutations in the quinolone resistance-determining regions and screened for the presence of the Salmonella genomic island 1 (SGI1). We determined that 63 (35.0%) of the 180 isolates were S. Kentucky ST198. Chinese strains of S. Kentucky ST198 have a high transmission of ciprofloxacin resistance (38/63, 60.3%) and a high risk of multidrug resistance. The quinolone resistance of the S. Kentucky ST198 strain found in China may be due to mutations in its quinolone resistance-determining region. Our study firstly revealed that ciprofloxacin-resistant S. Kentucky ST198 strains can undergo cross-host transmission, thereby causing a serious foodborne public health problem in China.

In real-time onboard hyperspectral-image(HSI) anomalous targets detection, processing speed and accuracy are equivalently desirable which is hard to satisfy at the same time. To improve detection accuracy, deep learning based HSI anomaly detectors (ADs) are widely studied. However, their large scale network results in a massive computational burden. In this paper, to improve the detection throughput without sacrificing the accuracy, a pruning−quantization−anomaly−detector (P-Q-AD) is proposed by building an underlying constraint formulation to make a trade-off between accuracy and throughput. To solve this formulation, multi-objective optimization with nondominated sorting genetic algorithm II (NSGA-II) is employed to shrink the network. As a result, the redundant neurons are removed. A mixed precision network is implemented with a delicate customized fixed-point data expression to further improve the efficiency. In the experiments, the proposed P-Q-AD is implemented on two real HSI data sets and compared with three types of detectors. The results show that the performance of the proposed approach is no worse than those comparison detectors in terms of the receiver operating characteristic curve (ROC) and area under curve (AUC) value. For the onboard mission, the proposed P-Q-AD reaches over 4.5 × speedup with less than 0.5 % AUC loss compared with the floating-based detector. The pruning and the quantization approach in this paper can be referenced for designing the anomalous targets detectors for high efficiency.

We investigate the statistical properties of maximum entropy density estimation, both for the complete data case and the incomplete data case. We show that under certain assumptions, the generalization error can be bounded in terms of the complexity of the underlying feature functions. This allows us to establish the universal consistency of maximum entropy density estimation.

Hyperspectral image (HSI) based detection has attracted considerable attention recently in agriculture, environmental protection and military applications as different wavelengths of light can be advantageously used to discriminate different types of objects. Unfortunately, estimating the background distribution and the detection of interesting local objects is not straightforward, and anomaly detectors may give false alarms. In this paper, a Deep Belief Network (DBN) based anomaly detector is proposed. The high-level features and reconstruction errors are learned through the network in a manner which is not affected by previous background distribution assumption. To reduce contamination by local anomalies, adaptive weights are constructed from reconstruction errors and statistical information. By using the code image which is generated during the inference of DBN and modified by adaptively updated weights, a local Euclidean distance between under test pixels and their neighboring pixels is used to determine the anomaly targets. Experimental results on synthetic and recorded HSI datasets show the performance of proposed method outperforms the classic global Reed-Xiaoli detector (RXD), local RX detector (LRXD) and the-state-of-the-art Collaborative Representation detector (CRD).

The characteristics of soil respiration (Rs) across different stand ages have not been well investigated. In this study, we identified temporal variation of Rs and its driving factors under three nature forest stands (e.g. 15-yr-old, 30-yr-old, and 45-yr-old) of Pinus yunnanensis in the Plateau of Mid-Yunnan, China. No consistent tendency was found on the change of Rs with the stand ages. Rs was ranked in the order of 30-yr-old > 45-yr-old >15-yr-old. Rs in 15-yr-old stand was the most sensitive to soil temperature (Ts) among the three sites. However, Ts only explained 30-40% of the seasonal dynamics of Rs at the site. Soil water content (Sw) was the major controlling factor of temporal variation at the three sites. Sw explained 88-93% of seasonal variations of Rs in the 30-yr-old stand, and 63.7-72.7% in the 15-yr-old and 79.1-79.6% in the 45-yr-old stands. In addition, we found that pH, available nitrogen (AN), C/N and total phosphorus (TP) contributed significantly to the seasonal variation of Rs. Sw was significantly related with pH, total nitrogen (TN), AN and TP, suggesting that Sw can affect Rs through improving soil acid-base property and soil texture, and increasing availability of soil nutrient. The results indicated that besides soil water, soil properties (e. g. pH, AN, C/N and TP) were also the important in controlling the temporal variations of Rs across different stand ages in the nature forestry.

As safety and reliability critical components, lithium-ion batteries always require real-time diagnosis and prognosis. This often involves a large amount of computation, which makes diagnosis and prognosis difficult to implement, especially in embedded or mobile applications. To address this issue, this paper proposes a run-time Reconfigurable Computing (RC) system on Field Programmable Gate Array (FPGA) for Relevance Vector Machine (RVM) to realize real-time Remaining Useful Life (RUL) estimation. The system leverages state-of-the-art run-time dynamic partial reconfiguration technology and customized computing circuits to balance the hardware occupation and computing efficiency. Optimal hardware resource consumption is achieved by partitioning the RVM algorithm according to a multi-objective optimization. Moreover, pipelined and parallel computation circuits for kernel function and matrix inverse are proposed on FPGA to further accelerate the computation. Experimental results with two different battery data sets show that, without sacrificing the RUL prediction performance, the embedded RC platform significantly reduces the computation time and the requirement of hardware resources. This demonstrates that complex prognostic tasks can be implemented and deployed on the proposed system, and it can be extended to the embedded computation of other machine learning algorithms.