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Abstract The physics principle of pulse flight positioning is the main theoretical bottleneck that restricts the spatial resolution of the existing Raman distributed optical fiber sensing scheme. Owing to the pulse width of tens of nanoseconds, the spatial resolution of the existing Raman distributed optical fiber sensing scheme with kilometer-level sensing distance is limited to the meter level, which seriously restricts the development of the optical time-domain reflection system. In this paper, a chaos laser is proposed in the context of the physical principle of the Raman scattering effect, and a novel theory of chaos Raman distributed optical fiber sensing scheme is presented. The scheme reveals the characteristics of chaos Raman scattering light excited by a chaotic signal on the sensing fiber. Further, the chaos time-domain compression demodulation mechanism between the temperature variation information and chaos correlation peak is demonstrated. Then, the position of the temperature variation signal is precisely located using the delay time of the chaos correlation peak combined with the chaos pulse flight time. Based on this novel optical sensing mechanism, an experiment with 10 cm spatial resolution and 1.4 km sensing distance was conducted, and the spatial resolution was found to be independent of the sensing distance. Within the limit of the existing spatial resolution theory, the spatial resolution of the proposed scheme is 50 times higher than that of the traditional scheme. The scheme also provides a new research direction for optical chaos and optical fiber sensing.

Raman distributed optical fiber temperature sensors possess the unique capability of measuring spatial environmental temperatures, which can be of great interest in several fields of application. The key physics barrier to spatial resolution for most optical time-domain reflection (OTDR) systems is the positioning principle of pulse-time-flight. It obtains the spatial resolution of the existing Raman distributed optical fiber temperature sensor, with the kilometer-level sensing distance being limited to the meter-level. Here, we propose a chaotic laser Raman distributed optical fiber temperature sensing scheme that replaces the traditional OTDR positioning principle used for more than 40 years with the chaotic correlation positioning principle. The proposed scheme possesses the characteristics of the chaos Raman scattering light excited by the chaos signal along the sensing fiber. A novel measurement mechanism based on chaotic time-domain differential reconstruction and chaotic correlation demodulation is developed, and a relationship between the temperature variation information and the chaotic correlation peak is experimentally demonstrated. Importantly, the proposed optics mechanism scheme overcomes the physics limitation of the effect of a wide pulse width on sensing spatial resolution; its spatial resolution is optimized from 50 to 0.3 m under the modulation of a 500 ns pulse width. This scheme provides a new concept for chaos optics and fiber sensing research.

Garlic (Allium sativum), an asexually propagated vegetable and medicinal crop, has abundant genetic variation. Genetic diversity evaluation based on molecular markers has apparent advantages since their genomic abundance, environment insensitivity, and non-tissue specific features. However, the limited number of available DNA markers, especially SSR markers, are insufficient to conduct related genetic diversity assessment studies in garlic. In this study, 4372 EST-SSR markers were newly developed, and 12 polymorphic markers together with other 17 garlic SSR markers were used to assess the genetic diversity and population structure of 127 garlic accessions. The averaged polymorphism information content (PIC) of these 29 SSR markers was 0.36, ranging from 0.22 to 0.49. Seventy-nine polymorphic loci were detected among these accessions, with an average of 3.48 polymorphic loci per SSR. Both the clustering analyses based on either the genotype data of SSR markers or the phenotypic data of morphological traits obtained genetic distance divided the 127 garlic accessions into three clusters. Moreover, the Mantel test showed that genetic distance had no significant correlations with geographic distance, and weak correlations were found between genetic distance and the phenotypic traits. AMOVA analysis showed that the main genetic variation of this garlic germplasm collection existed in the within-population or cluster. Results of this study will be of great value for the genetic/breeding studies in garlic and enhance the utilization of these garlic germplasms.

An increased demand for iron is a hallmark of cancer cells and is thought necessary to promote high cell proliferation, tumor progression and metastasis. This makes iron metabolism an attractive therapeutic target. Unfortunately, current iron-based therapeutic strategies often lack effectiveness and can elicit off-target toxicities. We report here a dual-therapeutic prodrug, DOXjade, that allows for iron chelation chemo-photothermal cancer therapy. This prodrug takes advantage of the clinically approved iron chelator deferasirox (ExJade®) and the topoisomerase 2 inhibitor, doxorubicin (DOX). Loading DOXjade onto ultrathin 2D Ti3C2 MXene nanosheets produces a construct, Ti3C2-PVP@DOXjade, that allows the iron chelation and chemotherapeutic functions of DOXjade to be photo-activated at the tumor sites, while potentiating a robust photothermal effect with photothermal conversion efficiencies of up to 40%. Antitumor mechanistic investigations reveal that upon activation, Ti3C2-PVP@DOXjade serves to promote apoptotic cell death and downregulate the iron depletion-induced iron transferrin receptor (TfR). A tumor pH-responsive iron chelation/photothermal/chemotherapy antitumor effect was achieved both in vitro and in vivo. The results of this study highlight what may constitute a promising iron chelation-based phototherapeutic approach to cancer therapy.

Chaotic laser has attracted a large amount of attention due to its broad spectrum, noise-like characteristics, and photonic integrated chaotic semiconductor lasers have further expanded the application field of chaotic laser for their small size and stable properties. Therefore, a monolithically integrated laser with a distributed Bragg reflector (DBR) is designed. This proposed chaotic laser consists of a distributed feedback (DFB) laser section, a phase section, and a DBR section. DBR grating can provide wavelength detuning to generate mode beating, which enhances chaotic bandwidth and distributed feedback to suppress time delay signature (TDS). The transmission line laser model (TLLM) of chaotic laser is constructed and chaotic characteristics of the integrated chip are investigated. A chaotic signal with a bandwidth of 12.34 GHz and TDS less than 0.065 is obtained. In addition, a map of dynamic states in the parameter space of phase section current and DBR section current is shown, and a wide range of chaotic regions are obtained. The results show that the broadband chaotic laser with a low TDS can be obtained by controlling the parameters reasonably, which is beneficial to realize the application of chaotic laser.

Differential evolution is a popular algorithm for solving global optimization problems. When tested, it has reportedly outperformed both robotic problems and benchmarks. However, it may have issues with local optima or premature convergence. In this paper, we present a novel BODE-CS (Bidirectional Opposite Differential Evolution–Cuckoo Search) algorithm to solve the inverse kinematics problem of a six-DOF EOD (Explosive Ordnance Disposal) robot manipulator. The hybrid algorithm was based on the differential evolution algorithm and Cuckoo Search algorithm. To avoid any local optimum and accelerate the convergence of the swarm, various strategies were introduced. Firstly, a forward-kinematics model was established, and the objective function was formulated according to the structural characteristics of the robot manipulator. Secondly, a Halton sequence and an opposite search strategy were used to initialize the individuals in the swarm. Thirdly, the optimization algorithms applied to the swarm were dynamically allocated to the Differential Evolution algorithm or the Cuckoo algorithm. Fourthly, a composite differential algorithm, which consisted of a dynamically opposite differential strategy, a bidirectional search strategy, and two other typically used differential strategies were introduced to maintain the diversity of the swarm. Finally, two adaptive parameters were introduced to optimize the amplification factor F and cross-over probability Cr. To verify the performance of the BODE-CS algorithm, two different tasks were tested. The experimental results of the simulation showed that the BODE-CS algorithm had high accuracy and a fast convergence rate, which met the requirements of an inverse solution for the manipulator.

In order to protect people’s lives and property, increasing numbers of explosive disposal robots have been developed. It is necessary for an explosive ordinance disposal (EOD) robot to quickly detect all explosives, especially when the location of the explosives is unknown. To achieve this goal, we propose a bidirectional dynamic weighted-A star (BD-A*) algorithm and a learn memory-swap sequence particle swarm optimization (LM-SSPSO) algorithm. Firstly, in the BD-A* algorithm, our aim is to obtain the shortest distance path between any two goal positions, considering computation time optimization. We optimize the computation time by introducing a bidirectional search and a dynamic OpenList cost weight strategy. Secondly, the search-adjacent nodes are extended to obtain a shorter path. Thirdly, by using the LM-SSPSO algorithm, we aim to plan the shortest distance path that traverses all goal positions. The problem is similar to the symmetric traveling salesman problem (TSP). We introduce the swap sequence strategy into the traditional PSO and optimize the whole PSO process by imitating human learning and memory behaviors. Fourthly, to verify the performance of the proposed algorithm, we begin by comparing the improved A* with traditional A* over different resolutions, weight coefficients, and nodes. The hybrid PSO algorithm is also compared with other intelligent algorithms. Finally, different environment maps are also discussed to further verify the performance of the algorithm. The simulation results demonstrate that our improved A* algorithm has superior performance by finding the shortest distance with less computational time. In the simulation results for LM-SSPSO, the convergence rate significantly improves, and the improved algorithm is more likely to obtain the optimal path.

Mobile manipulator robots have become important pieces of equipment due to the high mobility of mobile subsystems and the high flexibility of manipulator subsystems. Considering the increasing degrees of freedom and the need to avoid singular locations, one of the most challenging problems is solving the inverse kinematics problem of mobile manipulator robots (IKMM). Of all the popular optimization algorithms, the differential evolution (DE) algorithm is the most effective method for quickly solving the IKMM problem with sufficient solutions. Currently, many strategies have been proposed for DE algorithms to improve the performance of solving mathematical problems; some symmetry strategies or symmetry functions have been introduced to DE algorithms. However, the effects of various DE algorithms on solving the actual IKMM lack a comprehensive explanation. Therefore, we divide various DE algorithms into three categories considering the control parameter selection and compare the specific optimization of various DE algorithms. Then, we compare the performance of various DE algorithms when solving the inverse kinematics problems of mobile manipulators with different degrees of freedom. Considering the effectiveness and the speed of the DE algorithm on the IKMM problem, we determine the best DE algorithm by comparing the error and time required to reach 100 random mission points and tracking the typical trajectories. Finally, the best-performing DE method is further improved by studying the selection of fundamental parameters in the best DE algorithm. Valuable conclusions are obtained from these experimental simulations, which can help with choosing an algorithm that is suitable for solving the inverse kinematics problem of mobile manipulator robots in practice.

Garlic (Allium sativum L.) is a compelling horticultural crop with high culinary and therapeutic values. Commercial garlic varieties are male-sterile and propagated asexually from individual cloves or bulbils. Consequently, its main breeding strategy has been confined to the time-consuming and inefficient selection approach from the existing germplasm. Polyploidy, meanwhile, plays a prominent role in conferring plants various changes in morphological, physiological, and ecological properties. Artificial polyploidy induction has gained pivotal attention to generate new genotype for further crop improvement as a mutational breeding method. In our study, efficient and reliable in vitro induction protocols of autotetraploid garlic were established by applying different antimitotic agents based on high-frequency direct shoot organogenesis initiated from inflorescence explant. The explants were cultured on solid medium containing various concentrations of colchicine or oryzalin for different duration days. Afterward, the ploidy levels of regenerated plantlets with stable and distinguished characters were confirmed by flow cytometry and chromosome counting. The colchicine concentration at 0.2% (w/v) combined with culture duration for 20 days was most efficient (the autotetraploid induction rate was 21.8%) compared to the induction rate of 4.3% using oryzalin at 60 μmol L–1 for 20 days. No polymorphic bands were detected by simple sequence repeat analysis between tetraploid and diploid plantlets. The tetraploids exhibited a stable and remarkable dwarfness effect rarely reported in artificial polyploidization among wide range of phenotypic variations. There are both morphological and cytological changes including extremely reduced plant height, thickening and broadening of leaves, disappearance of pseudostem, density reduction, and augmented width of stomatal. Furthermore, the level of phytohormones, including, indole propionic acid, gibberellin, brassinolide, zeatin, dihydrozeatin, and methyl jasmonate, was significantly lower in tetraploids than those in diploid controls, except indole acetic acid and abscisic acid, which could partly explain the dwarfness in hormonal regulation aspect. Moreover, as the typical secondary metabolites of garlic, organosulfur compounds including allicin, diallyl disulfide, and diallyl trisulfide accumulated a higher content significantly in tetraploids. The obtained dwarf genotype of autotetraploid garlic could bring new perspectives for the artificial polyploids breeding and be implemented as a new germplasm to facilitate investigation into whole-genome doubling consequences.

ABSTRACT BACKGROUND: There have been inconsistent results regarding the association between alcohol intake and susceptibility to multiple sclerosis. OBJECTIVE: To assess the potential role of alcohol intake regarding the risk of multiple sclerosis by using a meta-analytic approach. DESIGN AND SETTING: Observational meta-analysis study conducted in a hospital in China. METHODS: The electronic databases of PubMed, EMBASE and the Cochrane library were systematically searched for eligible studies from their inception up to January 2020. The summary odds ratio (OR) with 95% confidence interval (CI) was applied to assess the association between alcohol intake and multiple sclerosis, using a random-effects model. RESULTS: One prospective cohort study and eight case-control studies involving a total of 211,396 subjects and 10,407 cases of multiple sclerosis were selected for the final meta-analysis. From the pooled data, no significant association between alcohol intake and multiple sclerosis risk was found (OR: 0.94; 95% CI: 0.73-1.22; P = 0.668), and this conclusion was judged to be robust. Subgroup analysis found that intake of beer was associated with an increased risk of multiple sclerosis (OR: 1.58; 95% CI: 1.12-2.23; P = 0.010). CONCLUSION: This study found that beer intake could cause an excess risk of multiple sclerosis. Further large-scale prospective studies should be conducted to verify this conclusion.

Ideological and political (IAP) education is the soul of socialist construction. As the main position for the cultivation of the “Four Haves” in the cause of socialist construction, colleges and universities shoulder an important educational mission. However, standard, scientific, systematic, and feasible evaluation index system is lacking in the teaching of IAP theory courses. Therefore, it is fervently required to use the modern science and technology for the establishment of a complete, objective, and feasible classroom teaching evaluation system, and the optimization of the evaluation process is also an important issue that needs to be resolved urgently. This paper combines teaching evaluation theory and machine learning methods, analyzes the rationality of evaluation indicators through the acquired evaluation data, and optimizes the evaluation system. By comparing the advantages and disadvantages of traditional machine learning classification algorithms, a classifier based on weighted naive Bayes is analyzed and designed for teaching evaluation, and the specific process of evaluation model construction is introduced. The experimental results show that the classification model based on the weighted naive Bayes algorithm is reasonable and feasible for teaching evaluation. Combined with the weighted Bayesian classification incremental learning principle, the performance of the classification model can be better than the traditional classification model.

The motion control of robot manipulators is a crucial problem concerning automatically controlled robots. In this work, the model predictive control method with an integral compensation (MPC-I), which compensates for the matched uncertainties due to unmodeled dynamics, is proposed to solve the trajectory tracking problem of robot manipulators in joint and task spaces. First, this paper decouples the joint variables of the robot manipulator using a computed torque control method. The MPC-I method is, thereafter, derived to realize the motion control of the robot manipulators in joint space. To realize the motion control of the robot manipulator in task space, the task space is, thereafter, converted into the joint space, in which the MPC-I method is executed, afterward, to control the robot. Furthermore, an MPC-I variation, in which the inverse kinematics is calculated indirectly, is proposed to achieve the motion control in task space. The novelty of this paper is to propose the MPC-I method and the method of converting task space to joint space with indirect inverse kinematics calculation. The former is suitable for the dynamic control of the robot manipulators in the joint space, and the latter can extend the MPC-I method to dynamic control in task space. To evaluate the performance of the proposed control method, motion control simulations are performed in the task and joint spaces, respectively. Simulation results and comparisons verify the effectiveness of the proposed control approach for the dynamic control of the UR5 robot manipulator.

In this paper, we propose an optimized differential evolution algorithm based on kinematic limitations and structural complexity constraints to solve the trajectory tracking problem for a mobile manipulator robot. The traditional method mainly involves obtaining the speed of the control variable based on the Jacobian inverse or linearization of the robot’s kinematic model, which cannot avoid the singularity position and/or self-collision phenomena. To address these problems, we directly design an optimized differential evolution algorithm to solve the trajectory planning problem for mobile manipulator robots. First, we analyze various constraints on the actual movement and describe them specifically using various equations or inequalities, including non-holonomic constraints on the mobile platform, the physical limitations of the driving motors, self-collision avoidance restriction, and smoothly traversing the singularity position. Next, we re-define the trajectory tracking of a mobile manipulator robot as an optimization problem under multiple constraints, including the trajectory tracking task and various constraints simultaneously. Then, we propose a new differential evolution (DE) algorithm by optimizing some critical operations to solve the optimization problem, such as improving the population’s distribution, limiting the population distribution range, and adding a success index. Additionally, we design two simple trajectories and two complex trajectories to determine the performance of the optimized DE algorithm in solving the trajectory tracking problem. The results demonstrate that the optimized DE algorithm can effectively realize the high-precision trajectory tracking task of a differential wheeled mobile manipulator robot through the consideration of kinematic limitations and self-collision avoidance.

In this paper, we propose a new path planning algorithm based on the probabilistic roadmaps method (PRM), in order to effectively solve the autonomous path planning of mobile robots in complex environments with multiple narrow channels. The improved PRM algorithm mainly improves the density and distribution of sampling points in the narrow channel, through a combination of the learning process of the PRM algorithm and the APF algorithm. We also shortened the required time and path length by optimizing the query process. The first key technology to improve the PRM algorithm involves optimizing the number and distribution of free points and collision-free lines in the free workspace. To ensure full visibility of the narrow channel, we extend the obstacles through the diagonal distance of the mobile robot while ignoring the safety distance. Considering the safety distance during movement, we re-classify the all sampling points obtained by the quasi-random sampling principle into three categories: free points, obstacle points, and adjacent points. Next, we transform obstacle points into the free points of the narrow channel by combining the APF algorithm and the characteristics of the narrow channel, increasing the density of sampling points in the narrow space. Then, we include potential energy judgment into the construction process of collision-free lines shortening the required time and reduce collisions with obstacles. Optimizing the query process of the PRM algorithm is the second key technology. To reduce the required time in the query process, we adapt the bidirectional A* algorithm to query these local paths and obtain an effective path to the target point. We also combine the path pruning technology with the potential energy function to obtain a short path without collisions. Finally, the experimental results demonstrate that the new PRM path planning technology can improve the density of free points in narrow spaces and achieve an optimized, collision-free path in complex environments with multiple narrow channels.

Cucumber (Cucumis sativus L.) fruit size/shape (FS) is an important yield and quality trait that is quantitatively inherited. Many quantitative trait loci (QTLs) for fruit size/shape have been identified, but very few have been fine-mapped or cloned. In this study, through marker-assisted foreground and background selections, we developed near-isogenic lines (NILs) for a major-effect fruit size/shape QTL FS5.2 in cucumber. Morphological and microscopic characterization of NILs suggests that the allele of fs5.2 from the semi-wild Xishuangbanna (XIS) cucumber (C. s. var. xishuangbannesis) reduces fruit elongation but promotes radial growth resulting in shorter but wider fruit, which seems to be due to reduced cell length, but increased cellular layers. Consistent with this, the NIL carrying the homozygous XIS allele (fs5.2) had lower auxin/IAA contents in both the ovary and the developing fruit. Fine genetic mapping with NIL-derived segregating populations placed FS5.2 into a 95.5 kb region with 15 predicted genes, and a homolog of the Arabidopsis CRABS CLAW (CsCRC) appeared to be the most possible candidate for FS5.2. Transcriptome profiling of NIL fruits at anthesis identified differentially expressed genes enriched in the auxin biosynthesis and signaling pathways, as well as genes involved in cell cycle, division, and cell wall processes. We conclude that the major-effect QTL FS5.2 controls cucumber fruit size/shape through regulating auxin-mediated cell division and expansion for the lateral and longitudinal fruit growth, respectively. The gibberellic acid (GA) signaling pathway also plays a role in FS5.2-mediated fruit elongation.

Two new endophytic species, Colletotrichum jishouense sp. nov. and. C. tongrenense sp. nov. were isolated from Nothapodytes pittosporoides in Guizhou and Hunan provinces, China. Detailed descriptions and illustrations of these new taxa are provided and morphological comparisons with similar taxa are explored. Phylogenetic analysis with combined sequence data (ITS, GAPDH, ACT and TUB2) demonstrated that both species formed distinct clades in this genus. This is the first record of Colletotrichum species from N. pittosporoides in China.

In recent years, optic-fiber sensors have been required to simultaneously measure the structure's crack and environmental temperature in the infrastructure monitoring system. We proposed and experimentally demonstrated a distributed optic-fiber sensor based on the Raman loop configuration and fiber loss characteristic for detecting the temperature and structure's crack. Among them, the Raman loop configuration with reference fiber is proposed to detect the temperature profile along the sensing fiber. It can eliminate the influence of external physical perturbation on the temperature measurement results, and do not require pre-calibration process before measurement. The temperature experimental results show that the temperature accuracy and spatial resolution can reach up to 0.28 °C and 1.2 m with the response time of 1.04 s. In addition, the information of crack is extracted by using the loss characteristics of Stokes, which is based on optical time domain reflectometry. The experiment results indicate that the fiber loss coefficient keeps a good linear variation between the crack ranges of 1.6 mm and 5.6 mm. The studies achieve the temperature and crack measurement only by one fiber.

In this paper, an optimized kinematic modeling method to accurately describe the actual structure of a mobile manipulator robot with a manipulator similar to the universal robot (UR5) is developed, and an improved self-collision detection technology realized for improving the description accuracy of each component and reducing the time required for approximating the whole robot is introduced. As the primary foundation for trajectory tracking and automatic navigation, the kinematic modeling technology of the mobile manipulator has been the subject of much interest and research for many years. However, the kinematic model established by various methods is different from the actual physical model due to the fact that researchers have mainly focused on the relationship between driving joints and the end positions while ignoring the physical structure. To improve the accuracy of the kinematic model, we present a kinematic modeling method with the addition of key points and coordinate systems to some components that failed to model the physical structure based on the classical method. Moreover, self-collision detection is also a primary problem for successfully completing the specified task of the mobile manipulator. In traditional self-collision detection technology, the description of each approximation is determined by the spatial transformation of each corresponding component in the mobile manipulator robot. Unlike the traditional technology, each approximation in the paper is directly established by the physical structure used in the kinematic modeling method, which significantly reduces the complicated analysis and shortens the required time. The numerical simulations prove that the kinematic model with the addition of key point technology is similar to the actual structure of mobile manipulator robots, and the self-collision detection technology proposed in the article effectively improves the performance of self-collision detection. Additionally, the experimental results prove that the kinematic modeling method and self-collision detection technology outlined in this paper can optimize the inverse kinematics solution.

Allicin compositions in garlic are used widely as fungicides in modern agriculture, in which diallyl disulfide (DADS) is a major compound. Downy mildew, caused by Pseudoperonospora cubensis (P. cubensis), is one of the most destructive diseases and causes severe yield losses in cucumbers. To explore the potential mechanism of DADS-induced cucumber resistance to downy mildew, cucumber seedlings were treated with DADS and then inoculated with P. cubensis at a 10-day interval. Symptom observation showed that DADS significantly induced cucumber resistance to downy mildew. Furthermore, both lignin and H2O2 were significantly increased by DADS treatment to responding P. cubensis infection. Simultaneously, the enzyme activities of peroxidase (POD) in DADS-treated seedlings were significantly promoted. Meanwhile, both the auxin (IAA) and salicylic acid (SA) contents were increased, and their related differentially expressed genes (DEGs) were up-regulated when treated with DADS. Transcriptome profiling showed that many DEGs were involved in the biological processes of defense responses, in which DEGs on the pathways of ‘phenylpropanoid biosynthesis’, ‘phenylalanine metabolism’, ‘MAPK signaling’, and ‘plant hormone signal transduction’ were significantly up-regulated in DADS-treated cucumbers uninoculated with the pathogen. Based on the results of several physiological indices and transcriptomes, a potential molecular mechanism of DADS-induced cucumber resistance to downy mildew was proposed and discussed. The results of this study might give new insight into the exploration of the induced resistance mechanism of cucumber to downy mildew and provide useful information for the subsequent mining of resistance genes in cucumber.

In this paper, we develop a hybrid iterative learning controller (HILC) for a non-holonomic wheeled mobile platform to achieve trajectory tracking with actual complex constraints, such as physical constraints, uncertain parameters, and initial errors. Unlike the traditional iterative learning controller (ILC), the control variable selects the rotation speed of two driving wheels instead of the forward speed and the rotation speed. The hybrid controller considers the physical constraints of the robot’s motors and can effectively handle the uncertain parameters and initial errors of the system. Without the initial errors, the hybrid controller can improve the convergence speed for trajectory tracking by adding other types of error signals; otherwise, the hybrid controller achieves trajectory tracking by designing a signal compensation for the initial errors. Then, the effectiveness of the proposed hybrid controller is proven by the relationship between the input, output, and status signals. Finally, the simulations demonstrate that the proposed hybrid iterative learning controller effectively tracked various trajectories by directly controlling the two driving wheels under various constraints. Furthermore, the results show that the controller did not significantly depend on the system’s structural parameters.

Persistent infection of high-risk human papillomavirus (HR-HPV) plays a causal role in cervical cancer. Regulator of chromosome condensation 1 (RCC1) is a critical cell cycle regulator, which undergoes a few post-translational modifications including phosphorylation. Here, we showed that serine 11 (S11) of RCC1 was phosphorylated in HPV E7-expressing cells. However, S11 phosphorylation was not up-regulated by CDK1 in E7-expressing cells; instead, the PI3K/AKT/mTOR pathway promoted S11 phosphorylation. Knockdown of AKT or inhibition of the PI3K/AKT/mTOR pathway down-regulated phosphorylation of RCC1 S11. Furthermore, S11 phosphorylation occurred throughout the cell cycle, and reached its peak during the mitosis phase. Our previous data proved that RCC1 was necessary for the G1/S cell cycle progression, and in the present study we showed that the RCC1 mutant, in which S11 was mutated to alanine (S11A) to mimic non-phosphorylation status, lost the ability to facilitate G1/S transition in E7-expressing cells. Moreover, RCC1 S11 was phosphorylated by the PI3K/AKT/mTOR pathway in HPV-positive cervical cancer SiHa and HeLa cells. We conclude that S11 of RCC1 is phosphorylated by the PI3K/AKT/mTOR pathway and phosphorylation of RCC1 S11 facilitates the abrogation of G1 checkpoint in HPV E7-expressing cells. In short, our study explores a new role of RCC1 S11 phosphorylation in cell cycle regulation.

Abstract The human papillomavirus (HPV) plays a central role in cervical carcinogenesis and its oncogene E7 is essential in this process. We showed here that E7 abrogated the G1 cell cycle checkpoint under hypoxia and analyzed key cell cycle related proteins for their potential role in this process. To further explore the mechanism by which E7 bypasses hypoxia-induced G1 arrest, we applied a proteomic approach and used mass spectrometry to search for proteins that are differentially expressed in E7 expressing cells under hypoxia. Among differentially expressed proteins identified, Cdc6 is a DNA replication initiation factor and exhibits oncogenic activities when overexpressed. We have recently demonstrated that Cdc6 was required for E7-induced re-replication. Significantly, here we showed that Cdc6 played a role in E7-mediated G1 checkpoint abrogation under hypoxic condition, and the function could possibly be independent from its role in DNA replication initiation. This study uncovered a new function of Cdc6 in regulating cell cycle progression and has important implications in HPV-associated cancers.

There is an optical interference noise in the conventional Raman-based fiber-optics distributed sensing, which results in a poor temperature resolution performance. In addition, the traditional whole-fiber demodulation principle complicates the operation steps of the system. In this paper, a novel dynamic difference attenuation recognition (DDAR) principle is operated in the DDP scheme (dual demodulation principle) and the SDP scheme (self-demodulation principle) respectively. It not only helps to eliminate the optical interference noise, but also omits the whole-fiber calibration process. In this experiment, a temperature resolution of 0.30 °C (17.0 km) is achieved through using the DDP scheme based on the DDAR principle, and the measurement time can be shortened to 1.5 s. Meanwhile, a temperature resolution of 0.18 °C (17.0 km) is obtained for the SDP scheme under the DDAR principle. The SNR of DDP and DSP schemes can be optimized to 12.82 dB and 13.32 dB by the proposed DDAR technology. Furthermore, the temperature resolution performance under a large temperature measurement range (0–1000 °C) is theoretically analyzed. The results indicate that the temperature responsivity for DDP and SDP schemes are parabolic and linear type respectively, which causes the temperature resolution of the two schemes to show a different trend with the change of temperature. The proposed DDAR method also can improve the temperature resolution in such a large temperature measurement range.

Compared with conventional laser, random laser (RL) has no resonant cavity, reducing the requirement of cavity design. In recent years, the random fiber laser (RFL), a novel kind of RL, has made great progress in theories and experiments. The RFL has a simpler structure, a more flexible design, and higher reliability. It has valuable applications for earth sciences, biological life sciences, and national defense security, due to these unique properties. This paper reviews the development of RFLs in the last decade, including their configurations based on various optical fibers and their output properties, especially the method of control. Moreover, we also introduce their applications in the optical fiber sensing system, which is a very important and practical orientation to study. Finally, this paper presents the prospects of RFLs.

We present designs of wavelength-division-multiplexing (WDM) and mode-division-multiplexing (MDM) optical links using mode de/multiplexers (DE/MUXs) based on multimode interference (MMI) couplers with a tilt joint as a phase shifter. The properties of WDM-MDM links with three wavelengths and two optical modes are numerically studied by using 3-D beam propagation method. In the first design, the wavelength combiner is also an MMI coupler type. The insertion loss of the design is around 6 dB because of the inherent loss of the MMI combiner. The size of the main passive optical parts (mode DE/MUXs and wavelength combiner) of the design is only 10.4 × 114.2 μm2, making the design promising for future compact and high-capacity optical interconnection applications. In another design, arrayed waveguide gratings are used for wavelength multiplexing, leading to a lower insertion loss of the optical connections. For both designs, the mode crosstalk between the two different modes for the same wavelength are below -22 dB.

The effects of doping in the multiquantum well (MQW) active region on the properties of InP-based long wavelength deep ridge transistor lasers (TLs) are numerically studied. Doping in the MQWs is shown to lead to a decrease of the slope efficiency and a notable increase of the current gain of the TLs, which makes MQW doping a useful tool for facilitating the design of TLs. When there are nonradiative recombination centers on the exposed MQW side walls of the TLs, doping in the MQWs is found to be able to enhance the performance of the TLs by reducing the threshold current and increasing the current gain greatly. With doping in the MQWs, the carrier diffusivity is decreased, making the defects less effective in consuming the carriers. The results show that doping in the MQWs helps to obtain high-quality TLs. The reduced carrier diffusion that results from doping also helps to improve the quality of a normal diode laser in case a deep ridge structure is needed.

We present the fabrication of a low-cost multiwavelength laser array monolithically integrated with a passive optical combiner for optical line terminals (OLTs) in wavelength-division multiplexing (WDM) passive optical networks (PONs). By combining the upper separate confinement heterostructure layer selective area growth technique and the bundle integrated guide technique, both multiwavelength emission with highly uniform spacing and low-loss passive-waveguide material can be obtained in a single metal-organic chemical vapor deposition (MOCVD) growth step, which greatly simplifies the fabrication of the device. A prototype laser array, which has four distributed feedback (DFB) laser elements and a multimode interference coupler as combiner, is successfully fabricated. The shallow ridge structure of the DFB lasers and the deep ridge structure of the passive waveguides are obtained by a single dry etching step, which further eases the device fabrication. The properties of the device are measured and discussed. The results indicate that our method is promising for fabricating cost-effective OLT light sources for WDM-PONs.

The field of tunnel fire detection requires a Raman distributed temperature sensor (RDTS) with high-accuracy and visual localization. A novel temperature demodulation method to improve the temperature measurement accuracy of the RDTS systems is presented. This method is based on the optical dynamic difference compensation algorithm, which can eliminate the optical power fluctuation. In addition, the visual localization technology is presented by using the longitudinal lining model (LLM) of a three-dimensional (3D) temperature display, which enhances the engineering application of RDTS in tunnel fire detection. Experimental results indicate that the temperature measurement accuracy is optimized from 7.0 °C to 1.9 °C at the sensing distance of 18.27 km by using the presented method. We provide a solution for temperature field monitoring as well as fire visual localization of the tunnel through RDTS systems.

Evaluation of peripheral retinal vascular changes in anterior uveitis using ultra-wide-field fluorescein angiography.A prospective, observational study of a case series of patients diagnosed with anterior uveitis.Clinical observation at an academic medical center. Patient or Study Population: A total of 65 eyes of 33 patients corresponded with the research criteria of anterior uveitis in the opinion of specialists of Peking University First Hospital.Patients were diagnosed primarily through clinical examinations and conventional fluorescein angiography. Subsequently, ultra-wide-field fluorescein angiograms were obtained for each patient.The main outcome was the detection of peripheral retinal changes by ultra-wide-field fluorescein angiography, and how these changes influenced the evaluation and management of the disease.Peripheral vessel leakage was detected in 27 eyes (42%) with anterior uveitis, of which 15 eyes displayed active inflammation and 12 eyes displayed inactive inflammation. Peripheral vessel leakage was found in seven of eight eyes with cystoid macular edema. Cystoid macular edema was detected in 7 of 27 eyes (26%) with peripheral vessel leakage, whereas 1 of 38 eyes (3%) did not display peripheral vessel leakage (p