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BackgroundFerroptosis is a cell death mode caused by excessive accumulation of lipid peroxides caused by disturbance of intracellular metabolic pathway, which is closely related to iron and cholesterol metabolism homeostasis. Its regulation within the hypoxic metabolic tumor microenvironment (TME) has the potential to improve the effectiveness of tumor immunotherapy. The predictive role of ferroptosis in gastric cancer (GC) hypoxia TME, particularly in relation to TME immune cell infiltration, has not been fully explained.MethodsBy analyzing the mRNA expression data of ferroptosis and hypoxia-related genes, a prediction model was constructed to evaluate further the predictive value of immune cell infiltration, clinical characteristics, and immunotherapy efficacy of gastric cancer, and the essential genes were validated.ResultsTwo distinct molecular states of ferroptosis-hypoxia were identified in GC. Notably, patients with high ferroptosis-hypoxia risk scores (FHRS) displayed significant levels of hypoxia and epithelial-mesenchymal transition (EMT), which were associated with unfavorable prognosis, increased chemoresistance, and heightened immunosuppression.ConclusionsThis study demonstrates that ferroptosis under hypoxic conditions significantly affects the modulation of the tumor immune microenvironment. The FHRS can independently predict prognosis in gastric cancer. Assessing the molecular status of ferroptosis-hypoxia in individual patients will help in selecting more suitable immunotherapy regimens by providing a better understanding of TME characteristics and predicting immunotherapeutic outcomes.

Exposure to arsenic (As) induces adverse effects on human health. Vitamins B1, B6, and C, as indispensable micronutrients for humans, have been proven to influence the metabolism and toxicity of ingested As. To determine the effect of vitamins on health risks associated with soil exposure, As bioaccessibility in 14 soil samples using four in vitro methods of IVG, PBET, SBRC, and UBM was measured with the addition of vitamins B1, B6, and C. With vitamins B1 and B6 addition, the gastric As bioaccessibility in 14 soil samples was reduced by 1.14–3.52 and 1.14–5.02 fold, respectively, and instead an increase in the intestinal bioaccessibility was presented in some cases. Vitamin C supplementation yielded higher As bioaccessibility in the gastric (1.13–13.02 fold) and small intestinal (1.21–33.35 fold) phases, respectively. As evidenced by the X-ray absorption near-edge spectroscopy (XANES) and Fourier transform infrared spectroscopy (FTIR) analysis, arsenic dissolution was promoted by Fe-As and hindered by the formation of Al-As fractions. Soil As dissolution in the simulated gastrointestinal tract was strongly influenced by soil minerals and ingested vitamins, due to the chelation of arsenic with vitamins and soil minerals such as Fe (hydr)oxides, and Fe(III) reductive dissolution to enhance As release by vitamin C as an iron reducer. These findings will expand the knowledge of health risks of exposure to As-contaminated soils and nutritional interventions aiming at the mitigation of As toxicity.

To address the issues of limited one-time loading capacity, single functionality, and low automation level in existing square straw bale pickers, a large automated square straw bale pick-up-and-stack truck that integrates picking, stacking, transporting, and bundling functions has been developed, combining the technical advantages of one-time field removal and storage of bales. We innovatively designed a side-pulling traction mechanism that can realize the rapid transition between the transporting state and working state of the machine; a picking device that can complete the continuous action of forking, lifting, turning positioning, and de-forking; and a bundling device that can realize the adjustment of the attitude of square straw bales. Response surface tests were conducted on the prototype to determine the key structural and operational parameters, using the bundle completion rate and regular bale rate as evaluation indicators. Regression and significance tests were performed on the machine’s forward speed, chassis frame offset, and the ground clearance of the fork tine to determine the influence and priority of these factors on the evaluation indicators. Through multi-objective function optimization of the regression model, the optimal parameter combination was found to be a machine forward speed of 15.5 km/h, a chassis frame offset of 2126 mm, and a fork tine ground clearance of 225 mm, resulting in a bundle completion rate of 98.85% and a regular bale rate of 96.96%. Subsequent field tests with the optimized parameters showed that at a machine forward speed of 15.5 km/h, a chassis frame offset of 2126 mm, and a fork tine ground clearance of 225 mm, the bundle completion rate was 98.37% and the regular bale rate was 95.83%, meeting the relevant design requirements. This study can provide a reference for the design and development of straw collection and storage machinery.

We propose and verify a method for analyzing the randomization capacity in a 160 km quantum noise randomized cipher system with different data modulation formats. The randomization capacity is defined as the difference in mutual information between Alice and Bob while the randomization level is at 0 and at its maximum, under the condition of error-free transmission. Our experimental analysis examines the capacity of quantum noise randomized cipher systems under different optical signal-to-noise ratios for each modulation format. Additionally, we analyze the noise masking values while the randomization reaches its capacity. The experimental results indicate that the binary phase shift-keying-based quantum noise randomized cipher system achieves the highest randomization capacity and highest noise masking value.

Reclaimed asphalt pavement (RAP) serves as an eco-friendly alternative to new construction materials. Hot In-Place Recycling (HIR), which involves the complete on-site recycling of RAP, emerges as a sustainable maintenance solution with resource conservation and cost reduction benefits. Numerous laboratory studies have delved into its advantages, focusing on aspects such as the rejuvenation of binding agents and improved resistance to rutting. Despite its performance benefits, research into extending pavement service life via this technology is limited due to a lack of comprehensive maintenance history and performance inspection data, i.e., censored data. To address this, survival analysis, a method commonly used in the medical field to evaluate treatment effectiveness, was applied. Specifically, a multistate survival analysis, incorporating the non-parametric Kaplan-Meier (KM) method, semi-parametric Cox proportional hazards regression model (Cox regression model) and a parametric generalized F model, was conducted. The treatment service life (TSL) was introduced to measure the duration between the completion of one maintenance activity and the occurrence of the next. The analysis of data from the Jiangsu Provincial Maintenance Management System revealed several noteworthy insights. For instance, a 1 mm increase in the initial rutting depth (RD) raised the risk of re-maintenance for HIR-treated segments by a factor of 1.03. Additionally, delaying maintenance by one year resulted in a 27% increase in the risk of re-maintenance, and a 1,000-fold rise in Equivalent Single Axle Load (ESAL) doubled the risk of re-maintenance. The median TSL for HIR-maintained sections, as estimated through the Generalized F model, was approximately 8.87 years, closely aligned with the median TSL of 9 years obtained using the KM method and the Cox regression model. This approach adeptly addresses the crucial challenge of determining the optimal timing and choosing effective maintenance treatments for pavements, a pivotal element of sustainable maintenance management. These findings disrupt the traditional belief that HIR is predominantly cost-effective without delivering significant long-term improvements in pavement performance. Instead, they emphasize the potential of HIR as a sustainable pavement maintenance treatment, advocating for its widespread adoption and implementation in pavement maintenance.

BackgroundOsteoporosis (OP) is typically diagnosed by evaluating bone mineral density (BMD), and it frequently results in fractures. Here, we investigated the causal relationships between diet-derived circulating antioxidants and the risk of OP using Mendelian randomization (MR).MethodsPublished studies were used to identify instrumental variables related to absolute levels of circulating antioxidants like lycopene, retinol, ascorbate, and β-carotene, as well as antioxidant metabolites such as ascorbate, retinol, α-tocopherol, and γ-tocopherol. Outcome variables included BMD (in femoral neck, lumbar spine, forearm, heel, total body, total body (age over 60), total body (age 45–60), total body (age 30–45), total body (age 15–30), and total body (age 0–15)), fractures (in arm, spine, leg, heel, and osteoporotic fractures), and OP. Inverse variance weighted or Wald ratio was chosen as the main method for MR analysis based on the number of single nucleotide polymorphisms (SNPs). Furthermore, we performed sensitivity analyses to confirm the reliability of the findings.ResultsWe found a causal relationship between absolute retinol levels and heel BMD (p = 7.6E-05). The results of fixed effects IVW showed a protective effect of absolute retinol levels against heel BMD, with per 0.1 ln-transformed retinol being associated with a 28% increase in heel BMD (OR: 1.28, 95% CI: 1.13–1.44). In addition, a sex-specific effect of the absolute circulating retinol levels on the heel BMD has been observed in men. No other significant causal relationship was found.ConclusionThere is a positive causal relationship between absolute retinol levels and heel BMD. The implications of our results should be taken into account in future studies and in the creation of public health policies and OP prevention tactics.

Abstract Background Cystinuria is an autosomal recessive disorder characterized by a cystine transport deficiency in the renal tubules due to mutations in two genes: SLC3A1 and SLC7A9. Cystinuria can be classified into three forms based on the genotype: type A, due to mutations in the SLC3A1 gene; type B, due to mutations in the SLC7A9 gene; and type AB, due to mutations in both genes. Methods We report a 12-year-old boy from central China with cystine stones. He was from a non-consanguineous family that had no known history of genetic disease. A physical examination showed normal development and neurological behaviors. Whole-exome and Sanger sequencing were used to identify and verify the suspected pathogenic variants. Results The compound heterozygous variants c.898_905del (p.Arg301AlafsTer6) is located in exon5 and c.1898_1899insAT (p.Asp634LeufsTer46) is located in exon10 of SLC3A1 (NM_000341.4) were deemed responsible for type A cystinuria family. The variant c.898_905del was reported in a Japanese patient in 2000, and the variant c.1898_1899insAT is novel. Conclusion A novel pathogenic heterozygous variant pair of the SLC3A1 gene was identified in a Chinese boy with type A cystinuria, enriching the mutational spectrum of the SLC3A1 gene. We attempted to find a pattern for the association between the genotype of SLC3A1 variants and the manifestations of cystinuria in patients with different onset ages. Our findings have important implications for genetic counseling and the early clinical diagnosis of cystinuria.

The use of recycled asphalt mixtures in regions with seasonal freeze-thaw cycles is becoming more popular. However, strict requirements for low-temperature cracking resistance limit their widespread application. This study designed thirteen types of recycled asphalt mixtures to explore factors affecting low-temperature performance in seasonal freeze-thaw regions and potential optimization methods. The three-point bending test assessed the low-temperature cracking performance of mixtures with varying recycled asphalt pavement (RAP) content, asphalt-aggregate ratios, asphalt types, and gradations under both conventional and freeze-thaw conditions. Results show that destructive strain and fracture energy decrease with higher RAP content, but increase with higher asphalt-aggregate ratios and 4.75 mm sieve passing rates. Adding rubber powder significantly enhances both destructive strain and fracture energy. Furthermore, the destructive strain remains insensitive to factors under both and freeze-thaw conditions, while fracture energy effectively distinguishes differences in low-temperature crack resistance. Analysis of variance reveals that RAP content, asphalt-aggregate ratio, asphalt type, and gradation significantly affect fracture energy after freeze-thaw cycles. Optimizing gradation is recommended to improve low-temperature performance of recycled asphalt mixtures in freeze-thaw regions.

Aiming at the problems of uneven mixing and low production efficiency of domestic silage mixer, a double- helix TMR (Total Mixed Rations) preparation mixer for silage straw feed was designed to replace the traditional vertical single-helix mixer. The performance tests and parameter optimization were carried out on this preparation machine. By analyzing the mixing process and mechanism of the diets in the mixing chamber, the key factors affecting the mixing performance and the range were determined. It was found that the greater the stirring speed of the churn, the greater the angle of material lift, the more conducive to improving the material lifting capacity of the churn device. The mixing characteristics of the preparation machine and the movement of material were numerically simulated using EDEM simulation software, and the mixing effect of the preparation machine was verified. The three-factor and five-level CCD center combination orthogonal rotary test in the prototype was carried out with stirring speed of the churn, mixing time and filling coefficient as influencing factors, mixing uniformity, roughage particle size and ton material energy consumption as evaluation indexes. The test results showed that the contribution of each factor to the mixing uniformity in descending order was filling coefficient, stirring speed and mixing time, to the roughage particle size was stirring speed, mixing time and filling coefficient, and to the ton material energy consumption was filling coefficient, mixing time and stirring speed. The optimal working parameters for mixing performance by comprehensive optimization could be concluded as stirring speed of 48.59 r/min, mixing time of 14.98 min, and filling coefficient of 70%. In addition, the mixing uniformity, roughage particle size and ton material energy consumption were obtained as 91.11%, 72.13% and 2.99 kW·h/t. The relative error for all evaluation indexes between the experimental results with round parameter combination and the predicted value was verified to be less than 3%. It can be seen the double-helix TMR preparation mixer can meet the demand for efficient mixing of silage straw feed, which obviously provides data reference and technical support for the design and selection of operating parameters of TMR preparation machines.

Cracking is a prevalent issue in expressway pavements in Shanxi Province, exhibiting various types. Based on field investigations, the primary types of asphalt pavement cracks observed in Shanxi expressways can be categorized as top-down crack (TDC, surface crack) and reflection crack (bottom-top crack). These two types differ significantly in terms of cracking mechanisms, development modes, treatment methods, and impact severity. This paper aims to simulate the initiation and propagation processes of top-down cracks and reflection cracks using the finite element method, aiming to provide a basis for distinguishing between the two. In this paper, a microstructure numerical model of a three-phase asphalt concrete pavement is established. Finite element software is utilized to simulate the initiation and propagation of top-down cracks and reflection cracks on asphalt pavement, while investigating the influence of various factors on crack propagation. The findings demonstrate that top-down cracks exhibit multi-point cracking on the pavement surface, resulting in a tortuous and discontinuous development process. Conversely, reflection cracks display significant stress concentration at the crack tip, leading to propagation even under loads significantly lower than the material's tensile strength, following a single propagation path. Aggregate distribution form, preset crack length, tensile strength of ITZ, and load distribution form do not have a significant effect on the primary cracking mode. However, they do influence the crack initiation point, cracking load, and propagation path to some extent.

The content of fine aggregate and asphalt in large stone porous asphalt mixture (LSPM) is low, and the load is mainly borne by the stable skeleton structure formed by the interlocking between coarse aggregates. The stress state of coarse aggregate in LSPM is an important factor affecting the bearing capacity of LSPM. The two-dimensional discrete element model (DEM) of LSPM is established by discrete element method. In order to simulate the true profile of the aggregate surface and ensure the formation of a stable embedded extrusion model, the spherical particles of coarse aggregate with a particle size greater than 2.36 mm are replaced by irregular particles. The virtual bearing plate test was carried out on 6 LSPM rut plates with different thicknesses. The force chain network inside LSPM was quantitatively analyzed by five indexes: force chain number (FCN), force chain evaluation coefficient (FCEC), simplified value of force chain angle (SFCA), angle stability coefficient (ASC) and force chain strength (FCS). When the thickness of the DEM is greater than or equal to 7.5 cm, an integrated skeleton structure is formed inside the LSPM. The bearing capacity of asphalt treated base-25 (ATB-25), asphalt treated base-30(ATB-30) and LSPM is compared by virtual bearing plate test under this thickness. The ability of LSPM to bear heavy load is stronger than that of ATB-25 and ATB-30. The overall deformation under heavy load is about 18.4 % of ATB-25 and about 29.6 % of ATB-30. In the process of bearing load, the contribution rate of embedded force between aggregates in LSPM is large. When the aggregate particle size is greater than 9.5 cm, the average pressure of the aggregates in LSPM is greater than the average pressure of the aggregates in ATB-25 and ATB-30. In order to avoid the crushing of LSPM coarse aggregate due to excessive force, which affects the skeleton structure and bearing capacity of LSPM, 26.5 mm sieve is determined as the key sieve to improve the stress state of LSPM coarse aggregate. In the recommended gradation range of LSPM, the passing rate of 26.5 mm sieve is adjusted, which effectively improves the stress state of coarse aggregate and ensures the stability of LSPM bearing capacity. The recommended pass rate of 26.5 mm sieve of LSPM is 86 %.

Asphalt mixture is a temperature-sensitive material, and its viscoelastic properties are essential for pavement design and performance evaluation. This paper presents a method for investigating the time domain linear viscoelastic parameter response of asphalt mixture after adding different warm mix agents. The approach utilizes the generalized Sigmoidal function to construct master curves of storage modulus and loss modulus in the frequency domain, and both discrete and continuous spectrum analyses are used to analyze the viscoelastic behavior of the asphalt mixture. The effects of varying Kelvin and Maxwell element numbers on the discrete spectrum are compared to the spectral intensity and master curve obtained from the continuous spectrum. Results show that the generalized Maxwell model with 10−3 or 10−2 as the center point and the generalized Kelvin model with 103 or 104 can obtain more accurate results. When used as input for simulation software, the number of 11 elements can balance computational efficiency and accuracy. The study evaluates the impact of different warm mix agents on the relaxation modulus and creep compliance of asphalt mixture and discusses the practical implications of these findings for engineering applications. Adding Foam warm mix agent significantly lowers the asphalt mixture's relaxation modulus by approximately 44%, while Sasobit and Evotherm marginally raise it by 14% and 22%, respectively. The Foam warm mix agent also increases the equilibrium modulus of creep compliance to 0.091 MPa, 80% higher than that of HMA. The findings of this paper provide guidance for selecting the appropriate warm mix agent to improve pavement performance.

This study employed small-angle X-ray scattering (SAXS) to characterize the microstructure of asphalt and investigated the evolving patterns of microstructure during the aging process of asphalt. Furthermore, by utilizing Fourier transform infrared (FTIR) spectroscopy, a detailed explanation of the intrinsic mechanisms governing microstructural changes in asphalt during aging was provided. The study demonstrated that the unified power-law exponential equation is more suitable for analyzing the SAXS curve of asphalt compared to model-dependent analyses. This equation not only exhibits a strong fit to the SAXS curve of asphalt but also yields crucial parameters about asphalt's microstructure, including the scattering coefficient (P) of asphaltene clusters, the scattering coefficient (Ps) of micelles, and the radius of gyration (Rs) of micelles. The SAXS experiments indicate the presence of asphaltene clusters with a surface fractal structure in asphalt, by a size exceeding 100 nm. The asphaltene clusters exhibit a propensity for ''phase separation'' with the aging of asphalt. Furthermore, asphalt aging leads to an increase in the Rs of the micelles and alters the Ps of the micelles. These changes are attributed to both the aggregation of the micelles and alterations in the manner in which micelles aggregate, which are primarily caused by the excessive aging of the maltene fraction. To analyse the effect of microstructural changes on macroscopic properties during asphalt aging, the changes in high and low temperature properties of asphalt during aging were tested in this study using the multiple stress creep and recovery (MSCR) test and the bending beam rheometer (BBR) test, respectively. It was found that the changes in macro properties of asphalt during aging are not entirely due to the changes in microstructure. This study expands the application of SAXS for microstructural analysis of asphalt and contributes to a profound comprehension of the aging mechanism of asphalt from a microstructural perspective.

Rhubarb palmatum L., Polygonum multijiorum Thunb., and Polygonum cuspidatum Sieb. Et Zucc. are traditional Chinese medicines that have been used for thousands of years. They are formulated into various preparations and are widely used. Emodin is a traditional Chinese medicine monomer and the main active ingredient in Rhubarb palmatum L., Polygonum multijiorum Thunb., and Polygonum cuspidatum Sieb. Et Zucc. Modern research shows that it has a variety of pharmacological effects, including promoting lipid and glucose metabolism, osteogenesis, and anti-inflammatory and anti-autophagy effects. Research on the toxicity and pharmacokinetics of emodin can promote its clinical application. This review aims to provide a basis for further development and clinical research of emodin in the treatment of metabolic diseases. We performed a comprehensive summary of the pharmacology and molecular mechanisms of emodin in treating metabolic diseases by searching databases such as Web of Science, PubMed, ScienceDirect, and CNKI up to 2023. In addition, this review also analyzes the toxicity and pharmacokinetics of emodin. The results show that emodin mainly regulates AMPK, PPAR, and inflammation-related signaling pathways, and has a good therapeutic effect on obesity, hyperlipidemia, non-alcoholic fatty liver disease, diabetes and its complications, and osteoporosis. In addition, controlling toxic factors and improving bioavailability are of great significance for its clinical application.

This paper aims to study the long-term strength and performance evolution of cold recycled mixture with emulsified asphalt (CRME). The specimens of CRME were prepared and cured in the laboratory. The indirect tensile strength (ITS) was measured over curing time (7, 14, 40 days), considering the binder (emulsified asphalt and cement), the RAP properties and the compaction work. The asymptotic regression model was introduced to describe the strength evolution of CRME with curing time. The long-term evolution of the resistance of rutting and cracking, moisture stability and fatigue resistance were also investigated. The results indicate that the Michaelis-Menten model can effectively describes the performance evolution of CRME over time. The aged asphalt in RAP still has the bonding activity and can contribute to short-term strength formation and long-term strength growth of CRME under compaction and curing. But the aging degree of aged asphalt has a negative effect on the strength formation and growth of CRME. The emulsified asphalt provides CRME with greater strength and strength growth potential than cement. The dual effect of cement and emulsified asphalt is most pronounced in the short- and long-term strength evolution of CRME. The higher compaction power, especially in secondary compaction, is beneficial to the short- and long-term strength formation of CRME. The resistance of the mixture to rutting, cracking and fatigue also improves with increasing curing time. Nevertheless, the moisture stability is basically unchanged during the laboratory curing.

Rutting is one of the most common distresses in early damage to asphalt pavements. It can raise the risk of ride safety issues, accelerate pavement deterioration, and increase maintenance costs. To investigate the factors that affect the rutting resistance of asphalt mixtures, internal factors (such as aggregate gradation, asphalt content, and layer thickness), external factors (including temperature and traffic loading), and human factors (such as compaction degree) were tested using wheel tracking tests. The test results showed that the rutting resistance of asphalt mixtures can be improved by designing a tightly interlocked aggregate skeleton using the Bailey method's primary control sieve, using an optimal asphalt content, achieving sufficient compaction, maintaining a layer thickness of 2.5–3 times its nominal maximum aggregate size, using an asphalt softening point higher than the pavement temperature, and avoiding overloaded vehicles. In highly rutted areas, it is recommended to use a stone mastic asphalt with a stable aggregate skeleton matrix and styrene-butadiene-styrene modified asphalt with a softening point higher than the highest pavement temperature.

Driven by economic interests, adding adulterations in chili powder is a problem which threatens people’s health. Thanks to its nondestructive, rapid, and portable advantages, electronic nose has more potential to be used for adulteration detection than the traditional methods. An approach for identifying the adulterants in chili powder was proposed in this paper. Firstly, an electronic nose system with 10 gas sensors was designed, and then the response images were drawn based on the response signals of the electronic nose. Afterwards, gas features were extracted from those response images by using a histogram of oriented gradients (HOG) algorithm. Finally, an SVM-based identification model was constructed to achieve the identification of plant adulterants in chili powder. The experimental results showed that the identification accuracy of the adulterant categories (almond shell, red beetroot, and tomato peel) based on the HOG features could reach up to 98.3%, and the identification results for adulterant content were 94.2%, 93.3%, and 95%, respectively. Furthermore, in order to compare the efficiency of the proposed identification approach, the widely used model AlexNet was also investigated and discussed.

The computing power network (CPN) is expected to realize the efficient provisioning of heterogeneous computing power through the collaboration between cloud computing and edge computing. Heterogeneous computing resources consist of CPU, GPU, and other types of computing power. Different types of applications may have diverse requirements for heterogeneous computing resources, such as general applications, CPU-intensive applications, and GPU-intensive applications. Service providers are concerned about how to dynamically provide heterogeneous computing resources for different applications in a cost-effective manner, and how to deploy more applications as much as possible with limited resources. In this paper, the concept of the benefit–cost ratio (BCR) is proposed to quantify the usage efficiency of CPU and GPU in CPNs. An application-aware resource allocation (AARA) algorithm is designed for processing different types of applications. With massive simulations, we compare the performance of the AARA algorithm with a benchmark. In terms of blocking probability, resource utilization, and BCR, AARA achieves better performance than the benchmark. The simulation results indicate that more computing tasks can be accommodated by reducing 3.7% blocking probability through BCR-based resource allocation.

The rapid change of technology has driven the information industry to advance and develop, and the computer network technology has been greatly improved, which also promotes the artistic expression of visual communication to develop in the direction of diversification and enrichment, providing designers with more sufficient performance carriers in visual communication design. As an essential communication method and medium in modern art and design, multimedia technology assumes the role of information transmission and communication in the teaching process of visual communication design and is an important communication platform. At the same time, in order to meet the market demand for talents, visual communication professional teaching is also faced with the contemporary task of cultivating innovative talents. And multimedia technology is gradually being applied in the field of education and teaching, becoming one of the driving forces to promote the evolution of teaching methods and teaching modes. Multimedia technology, as a medium of visual symbolic communication with the times, can not only expand and extend the depth and breadth of visual communication professional teaching but also promote the improvement of teaching methods and modes. This paper proposes that, against the background of continuous technological innovation, it is very necessary to further integrate multimedia technology into the teaching of visual communication majors. This paper discusses and analyzes and studies the application of multimedia technology in the teaching of visual communication from the aspect of innovative development in the teaching of visual communication.

Establishing an excellent recycling mechanism for containers is of great importance for environmental protection, so many technical approaches applied during the whole recycling stage have become popular research issues. Among them, classification is considered a key step, but this work is mostly achieved manually in practical applications. Due to the influence of human subjectivity, the classification accuracy often varies significantly. In order to overcome this shortcoming, this paper proposes an identification method based on a Recursive Feature Elimination-Light Gradient Boosting Machine (RFE-LightGBM) algorithm using electronic nose. Firstly, odor features were extracted, and feature datasets were then constructed based on the response data of the electronic nose to the detected gases. Afterwards, a principal component analysis (PCA) and the RFE-LightGBM algorithm were applied to reduce the dimensionality of the feature datasets, and the differences between these two methods were analyzed, respectively. Finally, the differences in the classification accuracies on the three datasets (the original feature dataset, PCA dimensionality reduction dataset, and RFE-LightGBM dimensionality reduction dataset) were discussed. The results showed that the highest classification accuracy of 95% could be obtained by using the RFE-LightGBM algorithm in the classification stage of recyclable containers, compared to the original feature dataset (88.38%) and PCA dimensionality reduction dataset (92.02%).

Quantum key distribution (QKD) is a promising technique to resist the threat against quantum computers. However, the high loss of quantum signals over a long-distance optical fiber is an obstacle for QKD in the intercontinental domain. In this context, the quantum satellite network is preferred over the terrestrial quantum optical network. Due to the mobility of satellites, the satellite topology is dynamic in the quantum satellite network, which remains a challenge for routing. In hybrid geostationary-earth-orbit (GEO)/low-earth-orbit (LEO) quantum satellite networks, the lack of an efficient scheduling scheme for GEO/LEO satellites also limits the construction of quantum satellite networks. Therefore, this paper provides a topology abstraction-based routing scheme for secret-key provisioning, where the dynamic physical topology is translated into a quasi-static abstracted topology. This scheme contributes to saving the precious secret key resources. In order to improve the success probability of long-distance QKD requests, three novel resource-scheduling heuristic algorithms are proposed in hybrid GEO/LEO quantum satellite networks. Simulation results indicate that the proposed algorithms can improve the success probability of QKD requests by 47% compared to the benchmark.

Abstract Background Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is life-saving for severe hematological conditions. However, its outcomes need further improvement, and co-infusion of mesenchymal stem cells (MSCs) may show promise. A growing body of research on this subject exists, while the results of different trials are conflicting. A systematic review and meta-analysis is needed to appraise the real efficacy and safety of MSC co-transplantation in allo-HSCT. Methods Studies comparing MSC co-transplantation in allo-HSCT with allo-HSCT alone were searched in six medical databases from inception to June 10, 2020. The primary outcomes were engraftment and graft-versus-host disease (aGVHD and cGVHD, respectively). Other outcomes included overall survival (OS), relapse rate (RR), non-relapse mortality (NRM), and immune reconstitution. Information was independently extracted by two investigators. Methodological quality was assessed using the Cochrane Collaboration tool. Meta-analysis was performed using RevMan 5.4. Results Six randomized controlled trials (RCTs) and 13 non-randomized controlled trials (nRCTs) were included. MSC co-infusion resulted in shorter times to neutrophil engraftment (RCTs: standardized mean difference (SMD) − 1.20, p = 0.04; nRCTs: SMD − 0.54, p = 0.04) and platelet engraftment (RCTs: SMD − 0.60, p = 0.04; nRCTs: SMD − 0.70, p = 0.01), a lower risk of cGVHD (RCTs: risk ratio (RR) 0.53, p = 0.01; nRCTs: RR 0.50, p

Abstract This letter analyses the outage performance of the optimal tag selection scheme for the proposed backscatter communication system. The consumed power by the tag's circuit is considered and the harvested power is described using the non‐linear model. On the premise of the harvested power satisfying its own consumption, the tag that can maximise the received effective signal‐to‐noise ratio at the destination is selected to convey its own information. The analytical results of the outage probability for the proposed optimal tag selection scheme are derived over the independent but not necessarily identically distributed Rayleigh fading channels, and the diversity order is also obtained with the help of the derived high signal‐to‐noise ratio approximations. The numerical results verify our theoretical analysis and show that the proposed optimal tag selection scheme has the best performance compared to other counterparts under different parameter set‐ups.

Purpose The Taicang and Wuqiang cohort study (TAWS) was established to examine the association between early-life nutrition and children’s health, and to explore the potential roles of maternal health, metabolites and microbiota in children’s health in two different regions of China.Participants A total of 7041 mother–child pairs were recruited during early pregnancy (n=4035, 57.3%) or delivery phase (n=3006, 42.7%) from health centres or hospitals in Taicang and Wuqiang. Mother–child pairs were followed up three times during pregnancy, once during delivery, and 7–10 times in the 3 years after delivery. Questionnaires were used to collect data on diet, supplementary intake, physical activity, depression scale, disease occurrence, feeding practice and development quotient of children. Anthropometric measurements of mothers and their children were assessed at each visit. Pregnancy outcomes were extracted from medical records. Biospecimens were collected and stored, including venous blood, cord blood, urine, stool, breast milk, cord and placenta.Findings to date Data from the TAWS cohort showed different baseline characteristics of participants at the two sites of TAWS. Abnormal metabolism occurred among newborns whose mothers were diagnosed with gestational diabetes mellitus. Maternal serum folic acid above 14.5 ng/mL at early pregnancy was associated with a reduced risk of delivering small-for-gestational-age newborns.Future plans The association between maternal nutrition and the health of offspring will be examined at various follow-up visits. Biomarkers will be analysed to assess the associations between early-life nutrition and child development, immunity and health. Strategic recommendations for optimal infant feeding practices, obesity prevention and routine healthcare items will be developed and proposed based on the findings from the study. Children in this prospective cohort study will be followed up once a year until age 12 years to further examine the relationships between early-life nutrition and children’s long-term development and health.

Time-Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) is considered as a promising solution of next generation PON (NG-PON). The integration of Edge Computing (EC) and TWDM-PON can satisfy the QoS requirements of delay-sensitive applications by providing storage, processing and caching capabilities at the network edge. However, with limited resource capacity, edge nodes in TWDM-PON are vulnerable to network attacks, e.g., Distributed Denial of Service (DDoS) attacks. Resource exhaustion in the attacked nodes easily leads to QoS degradation and even service blocking. This paper investigates how to effectively schedule traffic to mitigate the DDoS attack in EC-enabled TWDM-PON. Based on the collaboration of edge nodes, an adaptive traffic scheduling algorithm is designed to minimize the impact of DDoS attacks on delay sensitive services. The performance of the proposed algorithm is evaluated in simulation, where direct and indirect DDoS attacks are simulated. Besides, the attack duration and the number of attacked nodes are considered in the evaluation. Simulation results show that the proposed algorithm can effectively mitigate DDoS attacks in terms of reducing the QoS degradation rate and blocking rate of delay-sensitive services.

Quantum-key-distribution (QKD) enabled optical networks can provide secure keys for different kinds of applications to ensure the high security of communication processes. As the number of wavelength channels in a single-core fiber is limited, space division multiplexing (SDM) has been considered to be a valuable technique to provide more wavelength resources, which solves the problem of insufficient channel capacity. Due to the rapid expansion of data volume, the SDM-based QKD network has been regarded as an important paradigm. At the same time, resource allocation in multi-core optical networks is a problem worthy of studying. In this work, four routing, core, and wavelength allocation (RCWA) algorithms are proposed in the multi-core optical network for quantum service requests and classical service requests, which are referred to as RCWA without perception (RCWA-WP), RCWA with crosstalk perception (RCWA-XTP), RCWA with spectrum perception (RCWA-SP), and RCWA with core perception (RCWA-CP). Simulations are carried out to evaluate the network performance in terms of blocking probability, key utilization, and average crosstalk intensity. The comparative results indicate that the RCWA-SP algorithm can improve network performance and reduce the blocking probability, while the RCWA-XTP algorithm can reduce inter-core crosstalk during transmission.

The inherent cross-sensitivity of semiconductor gas sensors makes them extremely challenging to accurately detect mixed gases. In order to solve this problem, this paper designed an electronic nose (E-nose) with seven gas sensors and proposed a rapid method for identifying CH4, CO, and their mixtures. Most reported methods for E-nose were based on analyzing the entire response process and employing complex algorithms, such as neural network, which result in long time-consuming processes for gas detection and identification. To overcome these shortcomings, this paper firstly proposes a way to shorten the gas detection time by analyzing only the start stage of the E-nose response instead of the entire response process. Subsequently, two polynomial fitting methods for extracting gas features are designed according to the characteristics of the E-nose response curves. Finally, in order to shorten the time consumption of calculation and reduce the complexity of the identification model, linear discriminant analysis (LDA) is introduced to reduce the dimensionality of the extracted feature datasets, and an XGBoost-based gas identification model is trained using the LDA optimized feature datasets. The experimental results show that the proposed method can shorten the gas detection time, obtain sufficient gas features, and achieve nearly 100% identification accuracy for CH4, CO, and their mixed gases.

As the acquisition unit of gas information, the sensor array directly determines the overall performance of the electronic nose system (E-nose). This paper proposed a new method for optimizing the sensor array. Firstly, four evaluation indicators (sensitivity, selectivity, correlation, and repeatability) were selected to evaluate the sensor array. Subsequently, different evaluation indicators were assigned different weight values according to their contributions to the overall performance of the E-nose. Finally, a comprehensive evaluation model was established based on the EWM-TOPSIS algorithm to optimize the sensor array. In order to verify the effectiveness of the as-proposed model, it was applied to the optimization of the E-nose sensor array composed of 10 gas sensors, and the influence of the sensor array optimization on the gas recognition ability of the E-nose was investigated. The experimental results showed that the optimized sensor array can identify the CO-CH4 gas mixtures with an accuracy of 96.5%, which a significant improvement compared with the accuracy of 78.3% before the sensor array optimization.

With the increasing bandwidth requirements for people and the development of urbanization, the movement of the population in the city (especially the supercity) has an increasing influence on the traffic distribution in both space and time dimensions. The imbalanced distribution results in the regional blocking of different areas in different time periods and reduces the spectrum resource utilization in elastic optical networks. To resolve this problem, this paper proposes a tidal traffic model to formulate a kind of tidal traffic phenomenon firstly. Based on the analysis for this model, the area-aware routing and spectrum allocation algorithm that focuses on the traffic adjustment in specific functional areas is proposed. And two benchmark algorithms named min-hop k-shortest path routing algorithm and occupied-slots-as-weight k-shortest path routing algorithm are introduced. The evaluation results show that, compared to the benchmark algorithms, the proposed area-aware algorithm could reduce the blocking probability efficiently from 2% to 47% with low time complexity.

Network slicing is a key enabling technology to realize the provisioning of customized services in 5G paradigm. Due to logical isolation instead of physical isolation, network slicing is facing a series of security issues. Side Channel Attack (SCA) is a typical attack for slices that share resources in the same hardware. Considering the risk of SCA among slices, this paper investigates how to effectively allocate heterogeneous resources for the slices under their different security requirements. Then, a SCA-aware Resource Allocation (SCA-RA) algorithm is proposed for Ultra-reliable and Low-latency Communications (URLLC) and Enhanced Mobile Broadband (eMBB) slices in 5G RAN. The objective is to maximize the number of slices accommodated in 5G RAN. With dynamic slice requests, simulation is conducted to evaluate the performance of the proposed algorithm in two different network scenarios. Simulation results indicate that compared with benchmark, SCA-RA algorithm can effectively reduce blocking probability of slice requests. In addition, the usage of IT and transport resources is also optimized.

As an important bearer network of the fifth generation (5G) mobile communication technology, the optical transport network (OTN) needs to have high-quality network performance and management capabilities. Proof by facts, the combination of artificial intelligence (AI) technology and software-defined networking (SDN) can improve significant optimization effects and management for optical transport networks. However, how to properly deploy AI in optical networks is still an open issue. The training process of AI models depends on a large amount of computing resources and training data, which undoubtedly increases the carrying burden and operating costs of the centralized network controller. With the continuous upgrading of functions and performance, small AI-based chips can be used in optical networks as on-board AI. The emergence of edge computing technology can effectively relieve the computation load of network controllers and provide high-quality AI-based networks optimization functions. In this paper, we describe an architecture called self-optimizing optical network (SOON) with cloud-edge collaboration, which introduces control-layer AI and on-board AI to achieve intelligent network management. In addition, this paper introduces several cloud-edge collaborative strategies and reviews some AI-based network optimization applications to improve the overall network performance.

Physical layer authentication is an important way to ensure the security of optical communication network. We hereby propose a scheme to realize it by measuring the variation of the bit error rate (BER) on both sides of communication. In this scheme, the legitimacy of the receiver is identified by analyzing the BER variation of the optical fiber loop based on the short-term correlation of the channels. We then simulate a 16 PSK optical transmission system with intensity modulation direct detection-orthogonal frequency division multiplexing (IMDD-OFDM). The authentication effect is analyzed in the case of disturbance and beam split, as well as replacement of optical fiber channels caused by eavesdropper (Eve). The results show that this scheme is sensitive to the three kinds of attacks. A high probability of detection (PD) and a low false alarm rate (FAR) can be obtained. The experimental results show that with the increase of the frequency test, PD and FAR tend to be stable, and the authentication effect is better with the accuracy rate 100%.

The fast and diversified development of Internet services leads to numerous services with differentiated delay tolerance of optical connections set-up are converging in the optical network. Consequently, the average set-up delay of optical connection is increased, which will inevitably bring pressures to optical networks. To solve this problem, a delay aware routing spectrum assignment (RSA) algorithm based on services scheduling in priority queues with dynamic virtual topology construction (QVT-RSA) is proposed. First, the QVT-RSA algorithm reasonably identifies various different services and arranges them in order according to their priority, waiting time and delay tolerance requirements. Then, software defined networks (SDN) controller with multi-threads technology is adopted to innovatively parallel serve the ordered service requests to reduce the average set-up delay of optical connections, which also offset the induced delay caused by services scheduling. The network resource is accurately shared among multi-threads using the proposed mutual exclusive resource utilization model realized by dynamic virtual topology construction. The continuously coloring and usable virtual topology linkage reconfiguration can provide topology resources for service requests and adapt the dynamic transformation among serving, waiting and new arriving service requests. The shortest-path routing and first fit spectrum assignment (SPFF-RSA) algorithm is used as the baseline algorithm. Furthermore, by combining the SPFF-RSA algorithm and partial strategy of our strategy, the QSPFF-RSA and V-RSA algorithms are proposed as baseline algorithms as described in V-B. The simulation experiment results demonstrate that the average optical connections set-up delay of QVT-RSA algorithm is reduced compared with SPFF-RSA and QSPFF-RSA algorithms, and the blocking probability of QVT-RSA algorithm is reduced compared with SPFF-RSA, QSPFF-RSA and VRSA algorithms. The optical connections set-up success probability within delay tolerance about high, medium and low priority services of QVT-RSA algorithm is higher than that of the SPFF-RSA, QSPFF-RSA and VRSA algorithms.

Quantum key distribution (QKD) has attracted much attention on secure communications across global networks. QKD over satellite networks can overcome the limitations of terrestrial optical networks, such as large attenuation over long distance fiber channel and difficulty of intercontinental domain communications. Different QKD networks (around the world) can intercommunicate through quantum satellites, leading to a global quantum network in near future. This raises a new resource allocation and management problem of QKD involving multiple satellite layers and distributed ground stations. Using existing schemes, a single satellite cannot perform QKD for ground stations for the whole day. Moreover, the research problem is more challenging due to limitations of satellite coverage: limited cover time of low earth orbit (LEO) satellite, high channel losses of geostationary earth orbit (GEO) satellite, etc. To overcome these limitations, our study proposes a double-layer quantum satellite network (QSN) implemented quantum key pool (QKP) to relay keys for ground stations. We propose a new architecture of trusted-repeater-based double-layer quantum satellite networks, comprising GEO and LEO satellites. We also address the routing and key allocation (RKA) problem for key-relay services over QSNs. We propose a novel joint GEO-LEO routing and key allocation (JGL-RKA) algorithm to solve the RKA problem. Simulative results show that the proposed scheme can increase success probability of key-relay services significantly. We also present the impact of different route selections mechanisms, number of satellite links, satellite node capability, and service granularity on network performance.

This study aims to develop a new index to evaluate the low-temperature cracking performance (LTCP) of recycled asphalt mixtures. To achieve this, the assumption that fracture energy has limitation in evaluating the LTCP of mixtures was put forward firstly. To reveal this limitation theoretically, a concept of energy absorption rate that characterized the fracture energy of the mixtures was then given. Thirdly, an equivalent fracture temperature (EFT) corresponding to the critical cracking temperature in a thermal stress restrained specimen test (TSRST) was proposed to evaluate the LTCP of mixtures based on a three-point bending beam (3PBB) test. Finally, some data derived from previous work were collected to verify the proposed assumption, and the 3PBB test and TSRST were conducted to investigate the LTCP of five recycled mixtures with different reclaimed asphalt pavement (RAP) material contents and to verify the rationality of the proposed EFT. The results confirmed that fracture energy had some limitations in predicting the LTCP of mixtures. The EFT was as accurate as the critical cracking temperature in evaluating the LTCP of mixtures. Compared to fracture energy and critical cracking temperature, EFT had bigger absolute change and relative change between different mixtures, meaning it was better to differentiate the LTCP of mixtures. Compared to failure strain, EFT was also more definite and less variable when processed by different data analysts, meaning it was more objective.

Tin oxide nanoparticles (SnO2 NPs) demonstrate potential anti-cancer functions. However, the anti-cancer mechanisms of SnO2 NPs have not been explored in detail. In the present study, we synthesized SnO2 NPs through laser ablation technique and examined their anticancer mechanisms and the probable involvement of the PI3K/AKT mediated pathways in human breast cancer cells (MCF-7) in vitro. The synthesized SnO2 NPs were characterized by transmission electron microcopy (TEM), dynamic light scattering (DLS), and Fourier-transform infrared spectroscopy (FTIR) techniques. Afterwards, the breast cancer cells were incubated with increasing concentrations of SnO2 NPs, and inhibition of cell proliferation was assessed by the viability assay. Furthermore, the quantification of reactive oxygen species (ROS) and apoptosis were examined by flow cytometry followed by superoxide dismutase (SOD) and catalase (CAT) activity as well as mitochondrial membrane potential assays. The expression levels of phosphoinositide 3-kinase (PI3K), protein kinase B (AKT), mechanistic target of rapamycin (mTOR), B-cell lymphoma 2 (Bcl-2), and Bax were also assessed by western blot and quantitative real time PCR (qRT-PCR). It was shown that SnO2 NPs, 30 nm, with potential colloidal stability selectively prevented the proliferation of MCF-7 in comparison with MCF-10A cells and triggered ROS production, apoptosis, deactivation of SOD and CAT activity, and mitigation of mitochondrial membrane potential. Moreover, SnO2 NPs stimulated mitochondrial-mediated apoptosis pathway by overexpression of Bax/Bcl-2 and downregulation of p-PI3K/p-AKT/p-mTOR signaling pathway. This data elucidates the possible mechanisms by which SnO2 NPs may stimulate their anticancer effects.

Mixed-Fixed/Flex-Grid Optical Networks (MFGONs) are a new paradigm that emerged during the brown-field migration from fixed-grid Wavelength Division Multiplexing (WDM) optical networks to flex-grid Elastic Optical Networks (EONs). Based on the flex-grid, we can accommodate IP traffic directly to the optical layer by configuration. Considering the different granularities of spectrum resources and complex constraints in MFGONs, it is difficult to apply Routing and Wavelength/Spectrum Allocation (RWA/RSA) algorithms proposed in either fixed-grid or flex-grid optical networks. This paper first proposes two concepts, i.e., Link Spectrum Compactness (LSC) and Radiancy of Nodes (RoNs), to evaluate different scenarios of candidate paths for the end-to-end requests in MFGONs. Then, based on these two concepts, a Spectrum Entropy (SE) model is proposed in MFGONs. Here, the SE is the metric that combines LSC and RoNs to judge the fragmentation of network resources, and the value of SE is treated as the cost of candidate paths during the RSA operation. Finally, an SE-minimized RSA algorithm in MFGONs is designed. Simulation results prove that the proposed algorithm can effectively reduce the Bandwidth Blocking Ratio (BBR) and increase the revenues for upgrading the nodes compared to the state-of-the-art RSA algorithm. Particularly, the performance improvement is more obvious for highly connected networks.

A high-speed centrifugal pump with a fully sealed structure has the advantages of a small size, no external leakage, and being pollution-free. The inner leakage passage of a pump with a fully sealed structure includes the tip clearance and the hub clearance. The hub clearance, the lubrication passage of the bearing, and the clearance between the stator and the rotor of the built-in motor constitute the internal flow channel. As a consequence of hub leakage, the complexity of the flow field increases and performance of the pump is affected. However, hub leakage also lubricates the bearing and cools the motor by flowing through the internal flow channel. To obtain the actual flow field distribution and external characteristics of the pump, a coupling calculation based on a conventional CFX simulation and MATLAB was carried out. The results show that hub leakage promotes an increase in tip leakage and changes the distribution of the main flow field. Moreover, hub leakage also significantly affects the efficiency of the pump. Compared with hub leakage, the internal flow has a greater impact on the performance of the pump. The numerical simulation results of the internal flow model are similar to the experimental results, with the maximum absolute error of the head at 0.3 m and the maximum absolute error of the efficiency at 1.7%, indicating that the internal flow model is effective at predicting the performance of the high-speed centrifugal pump with a fully sealed structure.

Quantum key distribution (QKD) promises to deliver secure keys, which can be applied for security demands in optical networks by using cost-efficient and scalable lightpaths. To achieve such secure communication, the QKD integrated with optical networks has become a promising scenario to provide key provisioning services in optical networks. As an inevitable problem, the occurrence of failures becomes a challenge for the resiliency of the network. In that context, this paper studies the resilient QKD-integrated optical networks against single link failure. By analyzing and quantifying the key provisioning services, we constructed the secret-key flow model (SKFM) for the failure-affected and failure-unaffected cases. Based on the SKFM, a secret-key recovery strategy (SKRS) including three algorithms (i.e., one-path recovery method (OPRM), multi-path recovery method (MPRM), and time window-based recovery method (TWRM)) is designed to recover failure-affected key provisioning services in the network. The simulation work has been conducted to evaluate the performance of OPRM, MPRM, and TWRM in terms of key-service recovery ratio, secret-key recovery ratio, wavelength consumption ratio, and secret-key consumption ratio. Numerical results show that the three algorithms can recover failure-affected key provisioning services effectively, i.e., the MPRM outperforms the OPRM and the TWRM outperforms the MPRM. Better recovery can be realized by sacrificing more wavelength and secret-key resources, which are also required for the delivery of the QKD in the network. Thus, a trade-off can be achieved between the recovery of key provisioning services and the delivery of the QKD on wavelength resources and secret-key resources.

As a concept to enhance and extend cloud-computing capabilities, edge computing aims to provide Internet-based services in the close proximity to users by placing IT infrastructures at the network edge in forms of tiny datacenters. Taking advantage of the close distance to end user and access networks, edge datacenters can provide low-latency and context-aware services and further improve users' quality of experience. As the network edge is a geographically spread concept, the edge datacenters are usually highly distributed so that they can provide nearby storage and processing capabilities to most of the end users. Furthermore, edge datacenters also co-work with centralized cloud datacenters for service orchestration. Such decentralization and collaboration are expected to introduce significant transformations to both infrastructures and applications. To provide an overview of how edge can be integrated with cloud-computing and how edge computing can benefit applications, this paper studies the infrastructure and application issues of edge computing and networking in several sub-aspects, including related concepts, infrastructures, resource management and virtualization, performance, and applications.

This paper proposes a novel key distribution system based on the measurement of the bit error rate (BER) in a fiber channel. By carrying out the loopback BER measurement at both the transmitting and the receiving end, the BER is quantified and codified to generate consistency keys. Alice and Bob respectively encrypt the signal with the help of the public key base at the transmitting end. At the receiving end the data are decrypted and then the BER is measured. The security of generated keys in the system is enhanced by the use of the encryption base and the randomness of the channel. Additionally, noise sources are added to the channel so that the random noise conceals signals and Eve cannot eavesdrop the useful information in it. Due to the randomness of the channel noise, the generated keys have good randomness. This system at a high key generation rate is compatible with the existing communication device and its measurement is simple. The 10G bit/s-200 km coherent optical communication system is used to measure the BER of the security feature information of the extracted channel. The experimental results show that the key distribution system obtains a consistency rate of 98% with the key generation rate 2 Mbps, both of which have been significantly improved.

Quantum key distribution (QKD) can protect the exchange process of confidential information between communicating parties. By using the basic principles of quantum mechanics and combined with “one-time pad” cipher encryption, information can be unconditionally secure. The BB84 protocol first describes the method of transmitting information by photon polarization state, and it expounds the transmission process of services between trusted relays. However, due to the defects of real experimental devices, there are security vulnerabilities in QKD in a real system. The birth of measurement-device-independent quantum key distribution (MDI-QKD) protocol solves the problem, providing immunity to hacker attacks at the end of the detector. It can enable both sides of the transmission service to establish a connection and generate secret keys through an untrusted relay node to ensure information security. However, the types and properties of link nodes in quantum key distribution network (QKDN) based on partially trusted relay are more complex, which can easily result in network fault. Therefore, how to prevent the impact of failure on QKDN has become an urgent problem. In this paper, we propose a protection scheme for QKDN with partially trusted relays. The method deals with trusted and untrusted relays differently and constructs the working and protection paths of the secret key for each service. It reduces resource conflict between the protection and working paths by establishing a key protection threshold, which realizes the resource trade-off between the two factors. Simulation results show that the scheme provides effective protection to the services, and it improves the stability and reliability of QKDN based on partially trusted relay.

In this data article, we present the FT-IR and PXRD data of the lanthanide complexes constructed by 4-iodo-3-methylbenzoic acid (IMBA) and 4,7-dimethyl-1,10-phenanthroline (dmp). Detailed structure analysis, luminescence and sensing properties were discussed in our previous study, “Highly Luminescent Lanthanide Complexes as Bifunctional Sensor for Et2O and Fe2+” (Zhao et al., 2018). Also, the data include the bond lengths and angles of [Ln2(IMBA)6(dmp)2] (Ln=Eu3+, 1a; Ln=Gd3+, 1b; Ln=Tb3+, 1c).

With the development of optical networks technology, broad attention has been paid to flexible grid technology in optical networks due to its ability to carry large-capacity information as well as provide flexible and fine-grained services through on-demand spectrum resource allocation. However, a one-time green-field deployment of a flexible grid network may not be practical. The transition technology called the fixed/flex-grid optical networks is more applicable and highly pragmatic. In such network, many nodes would likely be upgraded from a fixed-grid to flex-grid. In fact, dynamic service provisioning during the process of a node upgrade in fixed/flex-grid optical networks have become a challenge because the service connection can be easily interrupted, which leads to considerable data loss because of node upgrade. To overcome this challenge, we propose a brown-field migration aware routing and spectrum assignment (BMA-RSA) algorithm in fixed/flex-grid optical networks. The aim is to construct a probabilistic migration label (PML) model. The well-designed label setting of PML can balance the relationship between distance and node-upgrade probability. Dynamic service provisioning operations are undertaken based on the PML model to achieve a migration-aware dynamic connection before network migration occurs. We also evaluate the performance of different service provisioning strategies under different traffic models. The simulation results show that the BMA-RSA algorithm can achieve: (1) the tradeoff between distance and node upgrade probability during the process of service provisioning; (2) lower service interruption compared with the traditional non-migration aware K-shortest-path routing and spectrum assignment algorithm.

In the era of the interconnection of all things, the security of the Internet of Things (IoT) has become a new challenge. The theoretical basis of unconditional security can be guaranteed by using quantum keys, which can form a QKD network-based security protection system of quantum Internet of Things (Q-IoT). However, due to the low generation rate of the quantum keys, the lack of a reasonable key allocation scheme can reduce the overall service quality. Therefore, this paper proposes a dynamic on-demand key allocation scheme, named DDKA-QKDN, to better meet the requirements of lightweight in the application scenario of Q-IoT and make efficient use of quantum key resources. Taking the two processes of the quantum key pool (QKP) key allocation and the QKP key supplement into account, the scheme dynamically allocates quantum keys and supplements the QKP on demand, which quantitatively weighs the quantum key quantity and security requirements of key requests in proportion. The simulation results show that the system efficiency and the ability of QKP to provide key request services are significantly improved by this scheme.

Achievable capacity of optical fiber is approaching its physical limitation in frequency domain. Space division multiplexing (SDM) technology can scale the network capacity using multi-core fiber and multi-mode fiber. In order to provide high-speed transmission services with fine granularities, SDM enabled elastic optical networks (SDM-EONs) become a promising candidate of future optical transport networks. However, since the spectrum status in SDM-EONs becomes more complex with the introduction of spatial dimension, the issue of spectrum fragmentation will be more serious in SDM-EONs compared in simple EONs. To remedy the issue of spectrum fragmentation in SDM-EONs, we propose a crosstalk-aware spectrum defragmentation (CASD) algorithm based on a metric, i.e., spectrum compactness (SC), which we define to measure the spectrum status in the SDM-EONs. Simulation results show that the proposed CASD algorithm can achieve better performance than a benchmark algorithm in terms of blocking probability and spectrum utilization. We also compare CASD algorithm with different SC thresholds in bandwidth blocking probability and spectrum utilization. Among them, CASD algorithm with SC threshold of 50 performs the best. It can achieve low spectrum moving times as well as low defragmentation latency.