Photonic implementation of the input and reservoir layers for a reservoir computing system based on a single VCSEL with two Mach-Zehnder modulators.

Hardware implementation of reservoir computing (RC), which could reduce the power consumption of machine learning and significantly enhance data processing speed, holds the potential to develop the next generation of machine learning hardware devices and chips. Due to the existing solution only implementing reservoir layers, the information processing speed of photonics RC system are limited. In this paper, a photonic implementation of a VMM-RC system based on single Vertical Cavity Surface Emitting Laser (VCSEL) with two Mach Zehnder modulators (MZMs) has been proposed. Unlike previous work, both the input and reservoir layers are realized in the optical domain. Additionally, the impact of various mask signals, such as Two-level mask, Six-level mask, and chaos mask signal, employed in system, has been investigated. The system's performance improves with the use of more complex mask(t). The minimum Normalized mean square error (NMSE) can reach 0.0020 (0.0456) for Santa-Fe chaotic time series prediction in simulation (experiment), while the minimum Word Error Rate (WER) can 0.0677 for handwritten digits recognition numerically. The VMM-RC proposed is instrumental in advancing the development of photonic RC by overcoming the long-standing limitations of photonic RC systems in reservoir implementation. Linear matrix computing units (the input layer) and nonlinear computing units (the reservoir layer) are simultaneously implemented in the optical domain, significantly enhancing the information processing speed of photonic RC systems.

A Novel Frameshift Variant of the ELF4 Gene in a Patient with Autoinflammatory Disease: Clinical Features, Transcriptomic Profiling and Functional Studies.

We described the diagnosis and treatment of a patient with autoinflammatory disease, named "Deficiency in ELF4, X-linked (DEX)". A novel ELF4 variant was discovered and its pathogenic mechanism was elucidated. The data about clinical, laboratory and endoscopic features, treatment, and follow-up of a patient with DEX were analyzed. Whole exome sequencing and Sanger sequencing were performed to identify potential pathogenic variants. The mRNA and protein levels of ELF4 were analyzed by qPCR and Western blotting, respectively. The association of ELF4 frameshift variant with nonsense-mediated mRNA decay (NMD) in the pathogenesis DEX was examined. Moreover, RNA-seq was performed to identify the key molecular events triggered by ELF4 variant. The relationship between ELF4 and IFN-ß activity was validated using a dual-luciferase reporter assay and a ChIP-qPCR assay. An 11-year-old boy presented with a Behçet's-like phenotype. The laboratory abnormality was the most obvious in elevated inflammatory indicators. Endoscopy revealed multiple ileocecal ulcers. Intestinal histopathology showed inflammatory cell infiltrations. The patient was treated with long-term immunosuppressant and TNF-α blocker (adalimumab), which reaped an excellent response over 16 months of follow-up. Genetic analysis identified a maternal hemizygote frameshift variant (c.1022del, p.Q341Rfs*30) in ELF4 gene in the proband. The novel variant decreased the mRNA level of ELF4 via the NMD pathway. Mechanistically, insufficient expression of ELF4 disturbed the immune system, leading to immunological disorders and pathogen susceptibility, and disrupted ELF4-activating IFN-ß responses. This analysis detailed the clinical characteristics of a Chinese patient with DEX who harbored a novel ELF4 frameshift variant. For the first time, we used patient-derived cells and carried out transcriptomic analysis to delve into the mechanism of ELF4 variant in DEX.

Updating vehicle VOCs emissions characteristics under clean air actions in a tropical city of China.

In the context of clean air actions in China, vehicle emission limits have been continuously tightened, which has facilitated the reduction of volatile organic compounds (VOCs) emissions. However, the characteristics of VOC emissions from vehicles with strict emission limits are poorly understood. This study investigated the VOC emission characteristics from vehicles under the latest standards based on tunnel measurements, and identified future control strategies for vehicle emissions. The results showed that the highest percentage of VOCs from vehicle consisted of alkanes (80.9 %), followed by aromatics (15.8 %) and alkenes (3.1 %). Alkanes had the most significant ozone formation potential due to their high concentrations, in contrast to the aromatics that have been dominant in previous studies. The measured fleet-average VOC emission factor was 71.3 mg·km-1, including tailpipe emissions of 39.6 mg·km-1 and evaporative emissions of 31.7 mg·km-1. The VOC emission factors of the subgroups were obtained. The emission of evaporated VOCs accounted for 44.5 % of the total vehicle VOC emissions, which have increased substantially from previous studies. In addition, the emission characteristics of vehicles that are under the latest emission threshold values have changed significantly, and the mixing ratio of toluene/benzene (T/B) has been updated to 3:1. This study updates the VOCs emission factors of vehicles under clean air actions and highlights the future mitigation policies should focus on reducing evaporative VOC emissions.

Periodic DFT calculations for the heterogeneous formation of 2-chlorothiophenoxy radical from 2-chlorothiophenol on Cu(111) surface in fly ash.

Copper plays a crucial role in the heterogenous dissociation of chlorothiophenols (CTPs) to form chlorothiophenoxy radicals (CTPRs), which is the initial and critical step in the formation of polychlorinated thianthrenes/dibenzothiophenes (PCTA/DTs). Here, first-principles calculations were performed to investigate the activity of Cu(111) surface towards the formation of adsorbed 2-CTPR from 2-CTP. The interaction between 2-CTP and Cu(111) surface was explored to find stable adsorption configurations. Besides, the decomposition routes of 2-CTP on the Cu(111) surface were further explored. Moreover, the effects of water on the formation of absorbed 2-CTPR on the Cu(111) surface were examined. Our results demonstrate that the flat adsorption of 2-CTP on the surface with adsorption energy in the range of -33.21 kcal/mol to -28.37 kcal/mol is more stable than the vertical adsorption with adsorption energy ranging from -23.53 kcal/mol to -13.38 kcal/mol. The Cu(111) surface catalyzes the conversion of 2-CTP into the adsorbed 2-CTPR with a modest energy barrier of 9.46 kcal/mol. Furthermore, water molecules exhibit stronger catalytic activity in this process with a decreased energy barrier of 5.87 kcal/mol through "water bridge" and hydrogen bonding. Specifically, the water accepts the hydrogen atom from 2-CTP and donates another hydrogen to the surface via "water bridge". This research provides a molecular-level understanding of the heterogeneous formation of PCTA/DTs by fly ash, suggesting novel approaches for control strategy and legislation of dioxin analogues.

Regulation of cluster synchronization in multilayer networks of delay coupled semiconductor lasers with the use of disjoint layer symmetry.

In real-world complex systems, heterogeneous components often interact in complex connection patterns and could be schematized by a formalism of multilayer network. In this work, the synchronization characteristics of multilayer network composed of semiconductor lasers (SLs) are investigated systematically. It is demonstrated that the interplay between different layers plays an important role on the synchronization patterns. We elucidate that the performance of cluster synchronization could be facilitated effectively with the introduction of disjoint layer symmetry into network topology. Intertwined stability of clusters from different layers could be decoupled into independent, and the parameter spaces for stable synchronization are extended significantly. The robustness of our proposed regulation scheme on operation parameters is numerically evaluated. Furthermore, the generality of presented theoretical results is validated in networks with more complex topology and multiple layers.

The astrocyte-produced growth factor HB-EGF limits autoimmune CNS pathology.

Central nervous system (CNS)-resident cells such as microglia, oligodendrocytes and astrocytes are gaining increasing attention in respect to their contribution to CNS pathologies including multiple sclerosis (MS). Several studies have demonstrated the involvement of pro-inflammatory glial subsets in the pathogenesis and propagation of inflammatory events in MS and its animal models. However, it has only recently become clear that the underlying heterogeneity of astrocytes and microglia can not only drive inflammation, but also lead to its resolution through direct and indirect mechanisms. Failure of these tissue-protective mechanisms may potentiate disease and increase the risk of conversion to progressive stages of MS, for which currently available therapies are limited. Using proteomic analyses of cerebrospinal fluid specimens from patients with MS in combination with experimental studies, we here identify Heparin-binding EGF-like growth factor (HB-EGF) as a central mediator of tissue-protective and anti-inflammatory effects important for the recovery from acute inflammatory lesions in CNS autoimmunity. Hypoxic conditions drive the rapid upregulation of HB-EGF by astrocytes during early CNS inflammation, while pro-inflammatory conditions suppress trophic HB-EGF signaling through epigenetic modifications. Finally, we demonstrate both anti-inflammatory and tissue-protective effects of HB-EGF in a broad variety of cell types in vitro and use intranasal administration of HB-EGF in acute and post-acute stages of autoimmune neuroinflammation to attenuate disease in a preclinical mouse model of MS. Altogether, we identify astrocyte-derived HB-EGF and its epigenetic regulation as a modulator of autoimmune CNS inflammation and potential therapeutic target in MS.

Microbial community assembly and functional profiles along the soil-root continuum of salt-tolerant Suaeda glauca and Suaeda salsa.

Developing and planting salt-tolerant plants has become a promising way to utilize saline-alkali land resources and ensure food security. Root-associated microbes of salt-tolerant plants have been shown to promote plant growth and alleviate high salt stress, yet very little is known about the salt resistance mechanisms of core microbes in different niches. This study characterized the microbial community structures, assembly processes, and functional profiles in four root-related compartments of two salt-tolerant plants by amplicon and shotgun metagenomic sequencing. The results showed that both plants significantly altered the microbial community structure of saline soils, with greater microbial alpha diversity in the rhizosphere or rhizoplane compared with bulk soils. Stochastic process dominated the microbial assembly processes, and the impact was stronger in Suaeda salsa than in S. glauca, indicating that S. salsa may have stronger resistance abilities to changing soil properties. Keystone species, such as Pseudomonas in the endosphere of S. glauca and Sphingomonas in the endosphere of S. salsa, which may play key roles in helping plants alleviate salt stress, were identified by using microbial co-occurrence network analysis. Furthermore, the microbiomes in the rhizoplane soils had more abundant genes involved in promoting growth of plants and defending against salt stress than those in bulk soils, especially in salt-tolerant S. salsa. Moreover, microbes in the rhizoplane of S. salsa exhibited higher functional diversities, with notable enrichment of genes involved in carbon fixation, dissimilar nitrate reduction to ammonium, and sulfite oxidation. These findings revealed differences and similarities in the microbial community assembly, functional profiles and keystone species closely related to salt alleviation of the two salt-tolerant plants. Overall, our study provides new insights into the ecological functions and varied strategies of rhizosphere microbes in different plants under salt stress and highlights the potential use of keystone microbes for enhancing salt resistance of plants.

Noisy image segmentation based on synchronous dynamics of coupled photonic spiking neurons.

The collective dynamics in neural networks is essential for information processing and has attracted much interest on the application in artificial intelligence. Synchronization is one of the most dominant phenomenon in the collective dynamics of neural network. Here, we propose to use the spiking dynamics and collective synchronization of coupled photonic spiking neurons for noisy image segmentation. Based on the synchronization mechanism and synchronization control, the noised pattern segmentation is demonstrated numerically. This work provides insight into the possible application based on the collective dynamics of large-scale photonic networks and opens a way for ultra-high speed image processing.

Hybrid photonic deep convolutional residual spiking neural networks for text classification.

Spiking neural networks (SNNs) offer powerful computation capability due to its event-driven nature and temporal processing. However, it is still limited to shallow structure and simple tasks due to the training difficulty. In this work, we propose a deep convolutional residual spiking neural network (DCRSNN) for text classification tasks. In the DCRSNN, the feature extraction is achieved via a convolution SNN with residual connection, using the surrogate gradient direct training technique. Classification is performed by a fully-connected network. We also suggest a hybrid photonic DCRSNN, in which photonic SNNs are used for classification with a converted training method. The accuracy of hard and soft reset methods, as well as three different surrogate functions, were evaluated and compared across four different datasets. Results indicated a maximum accuracy of 76.36% for MR, 91.03% for AG News, 88.06% for IMDB and 93.99% for Yelp review polarity. Soft reset methods used in the deep convolutional SNN yielded slightly better accuracy than their hard reset counterparts. We also considered the effects of different pooling methods and observation time windows and found that the convergence accuracy achieved by convolutional SNNs was comparable to that of convolutional neural networks under the same conditions. Moreover, the hybrid photonic DCRSNN also shows comparable testing accuracy. This work provides new insights into extending the SNN applications in the field of text classification and natural language processing, which is interesting for the resources-restrained scenarios.

Biomarkers for immunotherapy in esophageal cancer.

The development of immunotherapy, especially immune-checkpoint inhibitors targeting PD-1/PD-L1, has improved the outcomes of patients with esophageal cancer. However, not all population derives benefit from the agents. Recently, kinds of biomarkers were introduced to predict the response to immunotherapy. However, the effects of these reported biomarkers are controversial and many challenges remain. In this review, we aim to summarize the current clinical evidence and provide a comprehensive understanding of the reported biomarkers. We also discuss the limits of the present biomarkers and propose our own opinions on which viewers' discretion are advised.

BP-based supervised learning algorithm for multilayer photonic spiking neural network and hardware implementation.

We introduce a supervised learning algorithm for photonic spiking neural network (SNN) based on back propagation. For the supervised learning algorithm, the information is encoded into spike trains with different strength, and the SNN is trained according to different patterns composed of different spike numbers of the output neurons. Furthermore, the classification task is performed numerically and experimentally based on the supervised learning algorithm in the SNN. The SNN is composed of photonic spiking neuron based on vertical-cavity surface-emitting laser which is functionally similar to leaky-integrate and fire neuron. The results prove the demonstration of the algorithm implementation on hardware. To seek ultra-low power consumption and ultra-low delay, it is great significance to design and implement a hardware-friendly learning algorithm of photonic neural networks and realize hardware-algorithm collaborative computing.

Analysis of technological innovation on provincial green development levels of logistics industry in China.

The transition from traditional logistics to green and low-carbon logistics is crucial and inevitable due to the pressure of climate change and sustainable development in China. Meanwhile, technological innovation is perceived as an important factor affecting the development of the logistics industry. To explore the impacts of technological innovation and other factors and to propose proper policies based on the results, this study utilizes a generalized estimating equations (GEE) regression model to analyze panel data of 30 provinces during 2001-2019. Firstly, the entropy weight method is applied to calculate the green logistics development level based on an index system considering green factors. Secondly, a GEE model which considers the correlation among different observations is used to investigate the impacts of crucial factors on the green logistics development level. Moreover, regional heterogeneity is also analyzed in this paper by comparing the regression results of the Eastern region, Central region, and Western region. Based on the above analysis, several conclusions are drawn: (1) In terms of the average green logistics development levels, the Eastern region ranks 1st, the Central region ranks 2nd, and the Western region ranks 3rd. (2) GEE regression model is proved effective in our sample. (3) For the full sample, technological innovation, trade openness, and logistics infrastructure positively affect the green logistics development level; while, government regulation and energy intensity negatively influence the green logistics development level. (4) Regional heterogeneity is confirmed in our sample. Related policy recommendations are proposed based on our regional regression results. Take the Eastern region as an example, the local governments in the Eastern region should upgrade the manufacturing industry, reduce government financial investment in the transportation sector, and enhance environmental control expenditure in the transportation sector.

Monophosphoryl lipid A ameliorates radiation-induced lung injury by promoting the polarization of macrophages to the M1 phenotype.

BACKGROUND: Radiation-induced lung injury (RILI) often occurs during clinical chest radiotherapy and acute irradiation from accidental nuclear leakage. This study explored the role of monophosphoryl lipid A (MPLA) in RILI. MATERIALS AND METHODS: The entire thoracic cavity of C57BL/6N mice was irradiated at 20 Gy with or without pre-intragastric administration of MPLA. HE staining, Masson trichrome staining, and TUNEL assay were used to assess lung tissue injury after treatment. The effect of irradiation on the proliferation of MLE-12 cells was analyzed using the Clonogenic assay. The effect of MPLA on the apoptosis of MLE-12 cells was analyzed using flow cytometry. Expression of γ-H2AX and epithelial-mesenchymal transition (EMT) markers in MLE-12 cells was detected by immunofluorescence and Western blot, respectively. RESULTS: MPLA attenuated early pneumonitis and late pulmonary fibrosis after thoracic irradiation and reversed radiation-induced EMT in C57 mice. MPLA further promoted proliferation and inhibited apoptosis of irradiated MLE-12 cells in vitro. Mechanistically, the radioprotective effect of MPLA was mediated by exosomes secreted by stimulated macrophages. Macrophage-derived exosomes modulated DNA damage in MLE-12 cells after irradiation. MPLA promoted the polarization of RAW 264.7 cells to the M1 phenotype. The exosomes secreted by M1 macrophages suppressed EMT in MLE-12 cells after irradiation. CONCLUSION: MPLA is a novel treatment strategy for RILI. Exosomes derived from macrophages are key to the radioprotective role of MPLA in RILI.

Integration of small RNAs from plasma and cerebrospinal fluid for classification of multiple sclerosis.

Multiple Sclerosis (MS) is an autoimmune, neurological disease, commonly presenting with a relapsing-remitting form, that later converts to a secondary progressive stage, referred to as RRMS and SPMS, respectively. Early treatment slows disease progression, hence, accurate and early diagnosis is crucial. Recent advances in large-scale data processing and analysis have progressed molecular biomarker development. Here, we focus on small RNA data derived from cell-free cerebrospinal fluid (CSF), cerebrospinal fluid cells, plasma and peripheral blood mononuclear cells as well as CSF cell methylome data, from people with RRMS (n = 20), clinically/radiologically isolated syndrome (CIS/RIS, n = 2) and neurological disease controls (n = 14). We applied multiple co-inertia analysis (MCIA), an unsupervised and thereby unbiased, multivariate method for simultaneous data integration and found that the top latent variable classifies RRMS status with an Area Under the Receiver Operating Characteristics (AUROC) score of 0.82. Variable selection based on Lasso regression reduced features to 44, derived from the small RNAs from plasma (20), CSF cells (8) and cell-free CSF (16), with a marginal reduction in AUROC to 0.79. Samples from SPMS patients (n = 6) were subsequently projected on the latent space and differed significantly from RRMS and controls. On contrary, we found no differences between relapse and remission or between inflammatory and non-inflammatory disease controls, suggesting that the latent variable is not prone to inflammatory signals alone, but could be MS-specific. Hence, we here showcase that integration of small RNAs from plasma and CSF can be utilized to distinguish RRMS from SPMS and neurological disease controls.

Multi-perspective comparison of the immune microenvironment of primary colorectal cancer and liver metastases.

BACKGROUND: Liver metastases are a major contributor to the poor immunotherapy response in colorectal cancer patients. However, the distinctions in the immune microenvironment between primary tumors and liver metastases are poorly characterized. The goal of this study was to compare the expression profile of multiple immune cells to further analyze the similarities and differences between the microenvironments of liver metastases and the primary tumor. METHODS: Tissues from 17 patients with colorectal cancer who underwent resection of primary and liver metastases was analyzed using multispectral immunofluorescence. The expression of multiple immune cells (CD8, Foxp3, CD68, CD163, CD20, CD11c, CD66b, CD56, PD-L1, INF-γ, Ki67 and VEGFR-2) in the tumor center (TC), tumor invasive front (< 150 µm from the tumor center, TF) and peritumoral region (≥ 150 µm from the tumor center, PT) was evaluated via comparison. The expression of CD68 and CD163 in different regions was further analyzed based on the cell colocalization method. In addition, different immune phenotypes were studied and compared according to the degree of CD8 infiltration. RESULTS: The expression trends of 12 markers in the TF and TC regions were basically the same in the primary tumor and liver metastasis lesions. However, in comparison of the TF and PT regions, the expression trends were not identical between primary and liver metastases, especially CD163, which was more highly expressed in the PT region relative to the TF region. In the contrast of different space distribution, the expression of CD163 was higher in liver metastases than in the primary foci. Further analysis of CD68 and CD163 via colocalization revealed that the distribution of macrophages in liver metastases was significantly different from that in the primary foci, with CD68-CD163+ macrophages predominating in liver metastases. In addition, among the three immunophenotypes, CD163 expression was highest in the immune rejection phenotype. CONCLUSIONS: The immune cells found in the primary tumors of colorectal cancer differed from those in liver metastases in terms of their spatial distribution. More immunosuppressive cells were present in the liver metastases, with the most pronounced differential distribution found for macrophages. CD68-CD163+ macrophages may be associated with intrahepatic immunosuppression and weak immunotherapeutic effects.

Meta-Analysis of Anesthetic Efficacy and Safety of Propofol in Craniotomy Patients.

The anesthetic effect and safety of propofol in craniotomy patients by meta-analysis is investigated. Relevant studies consistent with the anesthetic effect and safety of propofol in craniotomy patients are searched and screened from domestic and foreign literature databases such as Wanfang Medical Center, CNKI, VIP, and PubMed, and meta-analysis is performed by RevMan 5.2 software. Experimental results show that the recovery time, intracranial pressure, cerebral edema, partial cerebral oxygen pressure, glutamate, and MDA in the propofol group are better than those in the control group (P < 0.05), and the incidence of superoxide dismutase, TNF-α, and adr in the propofol group is better than that in the control group (P > 0.05). Intravenous anesthesia with propofol in patients with craniotomy has the advantage of rapid recovery, and this program can improve intracranial pressure, brain edema, and brain oxygen partial pressure and help to improve oxidative stress and inflammatory reaction.

Comparative Physiological and Transcriptomic Analyses of Two Contrasting Pepper Genotypes under Salt Stress Reveal Complex Salt Tolerance Mechanisms in Seedlings.

As a glycophyte plant, pepper (Capsicum annuum L.) is widely cultivated worldwide, but its growth is susceptible to salinity damage, especially at the seedling stage. Here, we conducted a study to determine the physiological and transcriptional differences between two genotype seedlings (P300 and 323F3) with contrasting tolerance under salt stress. The P300 seedlings were more salt-tolerant and had higher K+ contents, higher antioxidase activities, higher compatible solutes, and lower Na+ contents in both their roots and their leaves than the 323F3 seedlings. During RNA-seq analysis of the roots, more up-regulated genes and fewer down-regulated genes were identified between salt-treated P300 seedlings and the controls than between salt-treated 323F3 and the controls. Many ROS-scavenging genes and several SOS pathway genes were significantly induced by salt stress and exhibited higher expressions in the salt-treated roots of the P300 seedlings than those of 323F3 seedlings. Moreover, biosynthesis of the unsaturated fatty acids pathway and protein processing in the endoplasmic reticulum pathway were deeply involved in the responses of P300 to salt stress, and most of the differentially expressed genes involved in the two pathways, including the genes that encode mega-6 fatty acid desaturases and heat-shock proteins, were up-regulated. We also found differences in the hormone synthesis and signaling pathway genes in both the P300 and 323F3 varieties under salt stress. Overall, our results provide valuable insights into the physiological and molecular mechanisms that affect the salt tolerance of pepper seedlings, and present some candidate genes for improving salt tolerance in pepper.

Endocapillary hypercellularity levels are associated with early complete remission in children with class IV lupus nephritis as the initial presentation of SLE.

BACKGROUND: Endocapillary hypercellularity (ECHC) is commonly seen in class IV lupus nephritis (LN), the most common and severe LN in children. Factors influencing early complete remission (CR) in pediatric class IV LN have been poorly described. We investigated the relationship between ECHC levels and early CR in pediatric class IV LN. METHODS: Patients with newly, simultaneously diagnosed systemic lupus erythematosus (SLE) and class IV LN by renal biopsy from 2012 to 2021 were studied. In this retrospective study, two pathologists who were blind to clinical information reviewed all pathological data retrospectively and classified glomerular lesions according to the revised criteria of the International Society of Nephrology and the Renal Pathology Society (ISN/RPS). The demographics, baseline clinical characteristics, laboratory parameters, renal histopathological findings, treatment regimen and CR at 6 months after immunosuppressive therapy were analyzed. ECHC was categorized as: > 50% (group A), 25-50% (group B) and < 25% (group C). CR was defined as absence of clinical symptoms, 24-hour urinary protein < 0.15 g, and normal levels of serum creatinine and albumin. RESULTS: Sixty-four patients were identified: 23, 15 and 26 in groups A, B and C, respectively. Group A had significantly higher levels of D-dimer, urine protein, and SLE disease activity index (SLEDAI) than groups B and C. Group C had a markedly higher estimated glomerular filtration rate (eGFR) than groups A and B. A substantially greater proportion of patients in group A had glomerular microthrombi and basement membrane thickening than in groups B and C. At 6 months post treatment, CR was achieved in 19 (82.6%), 5 (33.3%) and 11 (42.3%) in groups A, B and C, respectively (p < 0.05, group A vs groups B and C). Multiple logistic regression analysis revealed that ECHC and urine protein levels were significantly associated with CR. CONCLUSION: ECHC and urine protein levels may be valuable biomarkers for predicting early CR in pediatric class IV LN.

The Efficacy of Remifentanil Combined with Propofol in Craniotomy for Tumor Was Evaluated by Wake Quality, Hemodynamics, and Adverse Reactions.

In order to investigate the effect of remifentanil combined with propofol on awakening of craniotomy for tumor, a retrospective analysis is conducted. 86 patients who underwent craniotomy for brain tumor in our hospital from July 2020 to December 2021 are chosen to observe the quality of awakening, hemodynamic parameters, and the occurrence of adverse reactions. All patients are divided into group A (n = 43) and group B (n = 43) according to the use of anesthesia drugs. The intraoperative awakening quality and the hemodynamic parameters during different periods of the two groups are compared. The experimental results show that the incidence of postoperative adverse reactions in group B is significantly lower than that in group A (P < 0.05). It is clearly evident that remifentanil combined with protocol has good intraoperative wake-up effect in craniotomy for tumor and maintain the hemodynamic stability of patients. Also, it can obtain high wake-up quality and effectively reduce postoperative adverse reactions.

Quantum channel measurement with local quantum Bernoulli noises.

As an important stochastic process, quantum Bernoulli noises has a very important physical background and is an important research object in the field of quantum information. In this paper, we review local quantum Bernoulli noises and local quantum mutual entropy, then introduce quantum channel measurement with local quantum Bernoulli noises. On this basis, we give the channel structure between two systems, and prove the completely positivity of this quantum channel. We also give a channel application on the local quantum mutual entropy.