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We propose a cascaded neural network (NN) to simultaneously identify the modulation formats and monitor the optical-signal-to-noise ratio (OSNR). In the second-level network, it is a single deep NN (DNN) rather than multiple sub-networks, which makes the architecture more compact and can save the resource for real implementation. However, since the data set is constituted from all modulation formats, the universality can be guaranteed but not for the accuracy and the complexity. To accelerate the estimation process and improve the accuracy, we introduce the transfer learning (TL) and reconstruct the data set with a part from all of the modulation formats for universality and another part from a specific modulation format for TL to pursue higher accuracy. In the experiment, we compare the proposed cascaded single neural network (CSNN) with or without TL, cascaded multiple neural networks (CMNN) and adaptive multi-task learning (MTL) for MFI and OSNR monitoring. In the first-level NN, all of the three schemes can achieve the accuracy of MFI as 100%. In the second-level NN, the CSNN with TL (TL-CSNN) can significantly improve the training speed and decline the RMSE of 0.19 dB compared with CSNN without TL. The TL-CSNN also has faster convergence speed and is more stable compared with CMNN and adaptive MTL.

High-throughput RNA sequencing unveiled the complexity of transcriptome and significantly increased the records of long noncoding RNAs (lncRNAs), which were reported to participate in a variety of biological processes. Identification of lncRNAs is a key step in lncRNA analysis, and a bunch of bioinformatics tools have been developed for this purpose in recent years. While these tools allow us to identify lncRNA more efficiently and accurately, they may produce inconsistent results, making selection a confusing issue. We compared the performance of 41 analysis models based on 14 software packages and different data sets, including high-quality data and low-quality data from 33 species. In addition, computational efficiency, robustness, and joint prediction of the models were explored. As a practical guidance, key points for lncRNA identification under different situations were summarized. In this investigation, no one of these models could be superior to others under all test conditions. The performance of a model relied to a great extent on the source of transcripts and the quality of assemblies. As general references, FEELnc_all_cl, CPC, and CPAT_mouse work well in most species while COME, CNCI, and lncScore are good choices for model organisms. Since these tools are sensitive to different factors such as the species involved and the quality of assembly, researchers must carefully select the appropriate tool based on the actual data. Alternatively, our test suggests that joint prediction could behave better than any single model if proper models were chosen. All scripts/data used in this research can be accessed at http://bioinfo.ihb.ac.cn/elit.

In this paper, we consider the problem of anomaly detection when a small number of anomaly types are observed. Previous research primarily focused on supervised learning, when all samples are labeled. And unsupervised learning is used, when all samples are unlabeled. However, many settings do not satisfy the above two situations. Recently, there are some studies on the situations that anomalies are partially observed (e.g., Anomaly Detection with partially Observed Anomalies). It is generally believed that the anomalies are classifiable in these studies. And it is common that the types of observed anomalies cannot include all types of anomalies in the case of partially observed anomalies. We refer to this problem as anomaly detection with partially observed anomaly types and propose a two-stage anomaly detection algorithm in this condition. The proposed method in this paper is based on Anomaly Detection with partially Observed Anomalies and is available in the new setting. Experimental results demonstrate the effectiveness of the proposed method both in the case of insufficient types of observed anomalies and in the case of sufficient types of observed anomalies. Besides, anomaly detection with partially observed anomaly types avoids the use of hyper-parameter and has high generality in different datasets.

Repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, has been considered as a potentially effective treatment for the cognitive impairment in patients with mild cognitive impairment (MCI) and Alzheimer’s Disease (AD). However, the effectiveness of this therapy is still under debate due to the variety of rTMS parameters and individual differences including distinctive stages of AD in the previous studies. The current meta-analysis is aiming to assess the cognitive enhancement of rTMS treatment on patients of MCI and early AD. Three datasets (PubMed, Web of Science and CKNI) were searched with relative terms and finally twelve studies with 438 participants (231 in the rTMS group and 207 in the control group) in thirteen randomized, double-blind and controlled trials were included. Random effects analysis revealed that rTMS stimulation significantly introduced cognitive benefits in patients of MCI and early AD compared with the control group (mean effect size, 1.17; 95% CI, 0.76 - 1.57). Most settings of rTMS parameters (frequency, session number, stimulation site number) significantly enhanced global cognitive function, and the results revealed that protocols with 10 Hz repetition frequency and DLPFC as the stimulation site for 20 sessions can already be able to produce cognitive improvement. The cognitive enhancement of rTMS could last for one month after the end of treatment and patients with MCI were likely to benefit more from the rTMS stimulation. Our meta-analysis added important evidence to the cognitive enhancement of rTMS in patients with MCI and early AD and discussed potential underlying mechanisms about the effect induced by rTMS.

Purpose The purpose of this paper is to study where to place industrial solid waste treatment centers among the 16 prefecture-level cities under its jurisdiction. Design/methodology/approach This paper adopts the cross-efficiency data envelopment analysis (DEA) model, with the industrial land price and average annual salary per capita as inputs, while coverage, total transportation distance, number of industrial enterprises and total amount of industrial solid waste are used as outputs. Findings Based on the spatial efficiency scores calculated by using the new presented models, the authors find that the most efficient construction site are Chizhou, Chuzhou, Suzhou and Bengbu. That is quite different from the results obtained by using traditional approach. Originality/value This paper evaluates the spatial efficiency by using combinations of the four locations as the decision-making units of the DEA model, which could be used as an objective way to allocate limited resource. In addition to the resource allocation of the industrial solid waste treatment center, the method in this paper can also be applied to other spatial aspects of resource allocation.

Purpose Some recent studies have suggested a relationship between cardiac dose and mortality in non-small cell lung cancer (NSCLC), but others have reported conflicting data. The goal of this study was to conduct a systematic review and meta-analysis to provide an evidence-based estimate of the relationship between cardiac dose and mortality in these patients. Methods and Materials A systematic review of MEDLINE (PubMed) and Embase databases (inception to January 2018) was performed according to PRISMA guidelines. Studies that evaluated cardiac dosimetric factors in patients with NSCLC and included outcomes of cardiac events, cardiac mortality, and/or overall survival were identified. Results From 5614 patients across 22 studies, a total of 214 cardiac dosimetric parameters (94 unique) were assessed as possible predictors of cardiac toxicity or death. Assessed predictors included general (eg, mean heart dose [MHD]), threshold-based (eg, heart V5), and anatomic-based (eg, atria, ventricles) dosimetric factors. The most commonly analyzed parameters were MHD, heart V5, and V30. Most studies did not make corrections for multiplicity of testing. For overall survival, V5 was found to be significant on multivariable analysis (MVA) in 1 of 11 studies and V30 in 2 of 12 studies; MHD was not significant in any of 8 studies. For cardiac events, V5 was found to be significant on multivariable analysis in 1 of 2 studies, V30 in 1 of 3 studies, and MHD in 2 of 4 studies. A meta-analysis of the data could not be performed because most negative studies did not report effect estimates. Conclusions Consistent heart dose-volume parameters associated with overall survival of patients with NSCLC were not identified. Multiplicity of testing is a major issue and likely inflates the overall risk of type I errors in the literature. Future studies should specify predictors a priori, correct for multiplicity of testing, and report effect estimates for nonsignificant variables.

Big data technology is a new digital technology, which is as famous as the Internet of things and artificial intelligence in the past 20 years. It is an important technology that will profoundly change the way of human production and life. For economic researchers, the popularization and development of big data will bring subversive changes to the acquisition, collation and timeliness of data in economic research, and will play a positive role in promoting the development of economic research methods. In terms of the availability of data sources, the combination of big data technology and computer technology can make researchers easily obtain the required data, no matter the structured data we usually use or the unstructured data we don’t often use. In terms of the timeliness of data acquisition, big data technology makes the timeliness of economic data possible and effectively solves the lag in economic research Post problem: in terms of the value of data acquisition, although massive data reduces the value density of data, the quality of data captured by big data technology is far higher than that of ordinary data acquisition methods.

BackgroundObservational studies have shown an inverse association between circulating linoleic acid (LA) and risk of ischemic stroke (IS).ObjectiveThe aim of this study was to explore whether genetic variants predicting levels of circulating LA are associated with IS and its subtypes using a two-sample Mendelian randomization (MR) analysis.MethodsLA-related single-nucleotide polymorphisms (SNPs) were selected from a genome-wide association study of 8,631 participants, and summary statistics of IS and IS subtypes were obtained from the MEGASTROKE consortium. MR analysis was performed using the inverse-variance weighted (IVW) method complemented with other approaches, including weighted-median, weighted-mode, MR Pleiotropy RESidual Sum and Outlier test and MR-Egger regression, to test for the robustness of the association. Moreover, we conducted bidirectional MR analysis to assess the impact of IS-associated SNPs on circulating LA levels. Odds ratios (ORs) with 95% confidence intervals (95% CIs) were calculated.ResultsWe found that genetically predicted circulating LA levels were inversely associated with the risk of IS by the IVW method (OR = 0.98, 95% CI: 0.97–0.99, and P = 0.003). Subgroup analyses showed a statistically significant association between LA and risk of large artery stroke (LAS; OR = 0.95, 95% CI: 0.92–0.98, and P = 0.004), but not for other IS subtypes. The results were stable in sensitivity analyses, and no evidence of reverse association between LA and risk of IS, or LAS was observed.ConclusionOur study supports a potential inverse association of genetically predicted circulating LA levels with risk of IS, particularly LAS.

Objective Calcification serves as a surrogate for atherosclerosis-associated vascular diseases, and coronary artery calcification is mediated by multiple pathogenic factors. Estrogen is a known factor that protects the arterial wall against atherosclerosis, but its role in the coronary artery calcification development remains largely unclear. This study tested the hypothesis that estrogen inhibits coronary artery calcification via the hypoxia-induced factor-1α pathway. Methods Eight-week-old healthy female Sprague–Dawley rats were castrated, and vitamin D3 was administered orally to establish. Hypoxia-induced factor-1 inhibitor was administered to test its effect on vascular calcification and expression of bone morphogenetic protein 2 and runt-related transcription factor-2. Vascular smooth muscle cell calcification was induced with CaCl2 in rat aortic smooth muscle cells in the presence or absence of E2(17β-estradiol) and bone morphogenetic protein 2 siRNA intervention. Results The estrogen levels in ovariectomized rats were significantly decreased, as determined by ELISA. Expression of hypoxia-induced factor-1α mRNA and protein was significantly increased in vascular cells with calcification as compared to those without calcification ( p 2 ( p < 0.01). Finally, bone morphogenetic protein 2 siRNA treatment decreased the levels of p-Smad1/5/8 in A7r5 calcification cells ( p < 0.01). Conclusion Estrogen deficiency enhances vascular calcification. Treatment with estrogen reduces the expression of hypoxia-induced factor-1α as well as vascular calcification in rats. The estrogen effects occur in a fashion dependent on hypoxia-induced factor-1α regulation of bone morphogenetic protein-2 and downstream Smad1/5/8.

We propose a low complexity transfer-learning assisted neural-network nonlinear compensation (TL-NN- NLC) scheme. The experimental results show 1.3-dB quality factor (Q-factor) improvement for 128 Gb/s polarization multiplexed (PM) 16-QAM coherent optical transmission over 800-km SSMF. © 2020 The Author(s)

We propose a novel cascaded neural network with abnormality monitoring to simultaneously identify the modulation format and monitor the OSNR. The experimental results show 97.5 % MFI accuracy and 0.167dB average MAE for OSNR monitoring.

Objective. To assess the association between the expression level of miR-16 and prognosis of solid cancer patients by meta-analysis and bioinformatic analysis. Methods. PubMed, Web of Science, and Embase databases were searched until October 31, 2019, to identify eligible studies reporting the association of the miR-16 status with the prognosis of solid cancer patients. Hazard ratios (HRs) with 95% confidence intervals (CIs) were pooled, and a heterogeneity test was conducted. Sensitivity analysis and a publication bias test were also carried out. Furthermore, the miRpower database was used to validate the association. Results. Thirteen articles with 2303 solid cancer patients were included in the meta-analysis. Solid cancer patients with low expression level of miR-16 had shorter survival time (I2=84.0%, HR=1.47, 95% CI: 1.13-1.91, P=0.004). In the subgroup analyses of cancer sites, low miR-16 expression level was associated with poor prognosis in the reproductive system cancers (I2=33.3%, HR=1.24, 95% CI: 1.06-1.45, P=0.008). Sensitivity analysis suggested that the pooled HR was stable and omitting a single study did not change the significance of the pooled HR. Begg’s test and Egger’s test revealed no publication bias in the meta-analysis. In bioinformatic analysis, the significant association between miR-16 level and prognosis of patients with reproductive system cancers was further confirmed (HR=1.21, 95% CI: 1.03-1.42, P=0.017). Conclusion. Low expression level of miR-16 is an indicator for poor prognosis of solid cancer patients, particularly in reproductive system cancers.

With the expanding of marine and freshwater aquaculture, the outbreaks of aquatic animal diseases have increasingly become the major threats to the healthy development of aquaculture industries. Notably, viral infections lead to massive fish deaths and result in great economic loss every year across the world. Hence, it is meaningful to clarify the biodiversity, geographical distribution and host specificity of fish-associated viruses. In this study, viral sequences detected in fish samples were manually collected from public resources, along with the related metadata, such as sampling time, location, specimen type and fish species. Moreover, the information regarding the host fish, including aliases, diet type and geographic distribution were also integrated into a database (FVD). To date, FVD covers the information of 4860 fish-associated viruses belonging to 15 viral families, which were detected from 306 fish species in 57 countries. Meanwhile, sequence alignment, live data statistics and download function are available. Through the user-friendly interface, FVD provides a practical platform that would not only benefit virologists who want to disclose the spread of fish-associated viruses, but also zoologists who focus on the health of domestic and wild animals. Furthermore, it may facilitate the surveillance and prevention of fish viral diseases. Database URL: http://bioinfo.ihb.ac.cn/fvd.

AI-based network function virtualization (NFV) is an emerging technique that separates network control functionality from dedicated hardware middleboxes and is virtualized to reduce capital and operational costs. With the advances of NFV and AI-based software-defined networks, dynamic network service demands can be flexibly and effectively accomplished by connecting multiple virtual network functions (VNFs) running on virtual machines. However, such promising technology also introduces several new research challenges. Due to resource constraints, service providers may have to deploy different service function chains (SFCs) to share the same physical resources. Such sharing inevitably forces the scheduling of the SFCs and resources, which consumes computational time and introduces problems associated with reducing the response delay. In this paper, we address this challenge by developing two dynamic priority methods for queuing AI-based VNFs/services to improve the user experience. We account for both transmission and processing delays in our proposed algorithms and achieve a new processing order (scheduler) for VNFs to minimize the overall scheduling delay. The simulation results indicate that the proposed scheme can promote the performance of AI-based VNFs/services to meet strict latency requirements.

Solar-assisted steam generation is considered as an environmental-friendly and feasible technology to effectively harvest solar energy, which has been widely in water purification, seawater desalination and steam sterilization. In this work, we demonstrated flexible and scalable double-layered photothermal material (named as ppy-RF) based on phenolic aldehyde foam and polypyrrole coating as a light adsorption layer for solar steam generation. The resulting ppy-RF foam possessed interpenetrated and macroporous network with high porosity (>86%), superhydrophilicity, low thermal conductivity (0.0396 W m-1 K-1) and almost 100% absorbance (500-2500 nm). These characteristics make ppy-RF foam rapid water transportation and steam generation with an energy conversion efficiency of 90% under solar illumination of 1 kW h-1. Furthermore, the ppy-RF foam exhibits outstanding salt-resistant performance and long-term stability for desalination even in high salinity brine (20 wt%). By combination of its porous, flexible and monolithic configuration obtained by a simple and scalable fabrication method with efficient solar-thermal conversion ability and salt-resistance, the ppy-RF foam shows great potential in the application of clean water production and brine desalination.

In the context of "Internet Plus", the application of new media technology in Higher Vocational Education keeps maturing. At present, it is the key point of the ideological work in colleges and universities to customize the individualized strategy of publicity in a way that is popular with students. Giving the current problems of publicity in student affairs management, such as not very down to earth, poor timeliness, weak pertinence and small influence, this paper tries to introduce the O2O (online to offline) models on the student affairs management in Higher Vocational Colleges. This paper designs the practice scheme for "four modules" and the implementation method of "six modules" to open up a new realm of student affairs management in Higher Vocational Colleges. Among them, the practice scheme for "four modules" includes the establishment of the calendar of publicity, the insight of the object of publicity, selecting the content of the publicity and analyzing the effect of publicity. The implementation methods of "six modules" include triggering events, subdivision of people, selection of schemes, channel model fit, evaluation results, and process optimization.

Objective To evaluate the telomere length (TL) in patients with RA relative to that in controls and to test whether TL is causally associated with risk of RA. Methods Systematic review and meta-analysis of relevant literature was conducted to evaluate the association between TL and RA. Standardized mean differences with 95% CIs of TL in RA patients relative to controls were pooled using fixed or random-effects models. TL-related single-nucleotide polymorphisms were selected from a genome-wide association study of 37 684 individuals, and summary statistics of RA were obtained from a genome-wide association study meta-analysis including 14 361 RA patients and 43 923 controls. Mendelian randomization was performed using the inverse-variance weighted, weighted-median and likelihood-based methods. Sensitivity analyses were performed to test the robustness of the association. Results In the meta-analysis of 911 RA patients and 2498 controls, we found that patients with RA had a significantly shorter TL compared with controls (standardized mean differences = −0.50; 95% CI −0.88, −0.11; P = 0.012). In the Mendelian randomization analysis, we found that genetically predicted longer TL was associated with a reduced risk of RA [odds ratio = 0.68; 95% CI 0.54, 0.86; P = 0.002 using the inverse-variance weighted method]. Sensitivity analyses using alternative Mendelian randomization approaches yielded similar findings, suggesting the robustness of the causal association. Conclusion Our study provides evidence for a negative causal association of TL with risk of RA. Further studies are warranted to elucidate the underlying mechanism for the role of telomeres in the development of RA.

Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging problems in VC. Although, dynamic scheduling problem with deadline constraint has been extensively studied in prior studies in the heterogeneous system, such as cloud computing and clusters, these algorithms can&rsquo, t be fully applied to VC. This is because volunteer nodes can get offline whenever they want without taking any responsibility, which is different from other distributed computing. For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. To make full use of resources and maximize the number of completed tasks before the deadline constraint, on the basis of the DPDS algorithm, improved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we conducted experiments, and the results show that the proposed algorithms can effectively solve the dynamic task assignment problem with deadline constraint in VC.

BACKGROUND The physical and mental health of college students tends to continuously decline worldwide. Thus, improving their health is necessary. Jazz dance may be one of the effective exercises to improve one's health. However, the effect of jazz dance exercise on different physical fitness level and whether the intensity of jazz dance exercises can improve physical and mental health simultaneously and efficiently need to be investigated. In this study, we systematically assessed the effect of jazz dance on physical and mental health of college students by a rigorous randomized, parallel-controlled design. METHODS An experimental study including 90 Chinese female college students (junior and senior) was performed. They completed an 8-week jazz dance class (two times/week for 70 min per session). Data on psychological status were obtained using the Subjective Exercise Experiences Scale after every class. Based on the Japanese national physical fitness test method, we identified the body weight and Body Mass Index and the students performed 30-s sit ups, standing long jump, 20s repeated across the body, and seated forward flexion to determine their physical fitness at baseline and after 8 weeks. Repeated measures analyses of variance and paired samples t-tests were used to compare the means of the participants' data. RESULTS Differences in the mean of mental health scores over time were significant and showed an increasing trend (P

This paper discusses a study of the influence of different positions and modes of smartphone navigation devices on driving behavior based on real vehicle driving. Twenty professional drivers participated in the experiment in free-flowing traffic and good weather conditions. The eye movement and vehicle control data obtained in the experiment were used as indicators for evaluation. Comparison of the mean, variance, and significance analysis shows that a smartphone navigation device placed on the right side of the car dashboard (position 1) has less impact on driving behavior than when placed above the air conditioning vent (position 2). A smaller angle of view can increase the fixation frequency and the length of time that the driver spends looking out the windshield and reduce the range and time spent in glancing at the navigation device. Using only sound navigation (the audio group in this paper) has the least influence on driving behavior because the driver’s visual attention is not transferred inside the vehicle rather than on the road ahead, and the vehicle is operated in the most stable state. These findings have practical significance for reducing the negative influence of smartphone navigation.

Background In recent years, the opportunistic fungus C.albicans has been linked to ECC.It is important to investigate the relationship between the distribution of C.albicans and early childhood caries (ECC) in 3–5-year-old Uygur and Han children in Kashgar, and the role of C.albicans of distinct genotypes in caries. Methods Two hundred fifty-six Uygur and 141 Han children were enrolled in the study. The identified C.albicans isolates were genotyped based on 25S rDNA Polymerase Chain Reaction(PCR) amplification, and their acidogenicity, aciduricity, and adhesiveness were examined. Moreover, secreted aspartic protease (Sap) activity and SAP1–5 transcriptional levels were compared in the ECC and caries-free (CF) groups of Uygur children. Results C.albicans detection rate was significantly higher in Uygur children than in Han children (44. 5% vs. 31. 2%; χ2= 6.739, P = 0.009);the A genotype was dominant in Uygur and Han children with ECC, the C genotype was dominant in Uygur CF children(P = 0.022). C.albicans acidogenicity and growth were more pronounced in the Uygur ECC group than in CF group, especially at pH 4.0 and 4. 5(pH 4.0, P = 0.012; pH 4. 5, P = 0.029); the average ratios of glass-wall adhesion and the Sap activity was higher in ECC group than in CF group(P

Previous observational studiíes provided conflicting findings on the relationship between linoleic acid (LA) and the risk for stroke. The aim of this study was to evaluate the association of LA levels in blood or adipose tissue samples with risk for stroke.PubMed, Web of Science, and Embase databases were searched until February 29, 2020 to identify eligible observational studies, including cohort studies, nested case-control studies, case-cohort studies, and case-control studies, reporting the association of LA with the risk for stroke and its subtypes. We pooled hazard ratio (HR) estimates with 95% confidence intervals (CIs) and conducted heterogeneity test. Sensitivity analysis and publication bias test were also carried out.Twelve studies from 11 observational articles involving 47 836 individuals were included in the meta-analysis. We observed an inverse association between biomarkers of dietary LA and risk for total stroke (HR, 0.88; 95% CI, 0.83-0.94; P0.001). Meta-regression analysis suggested that ethnicity (P = 0.029) and study design (P = 0.049) contributed to between-study heterogeneity. Subgroup analysis showed that the association was statistically significant among studies conducted in white (P0.001) and Asian (P = 0.032) populations, and those with cohort (P = 0.001) and case-cohort design (P = 0.007). Moreover, we found that higher LA levels were associated with a reduced risk for ischemic stroke (HR, 0.87; 95% CI, 0.80-0.95; P = 0.001), although no statistically significant association was found between LA levels and the risk for hemorrhagic stroke.The present study supported an inverse association of LA levels with the risk for stroke, particularly ischemic stroke. Racial disparity exists in the association between LA and the risk for stroke, which deserves further studies.

The grass carp is an important farmed fish, accounting for similar to 16% of global freshwater aquaculture, and has a vegetarian diet. Here we report a 0.9-Gb draft genome of a gynogenetic female adult and a 1.07-Gb genome of a wild male adult. Genome annotation identified 27,263 protein-coding gene models in the female genome. A total of 114 scaffolds consisting of 573 Mb are anchored on 24 linkage groups. Divergence between grass carp and zebrafish is estimated to have occurred 49-54 million years ago. We identify a chromosome fusion in grass carp relative to zebrafish and report frequent crossovers between the grass carp X and Y chromosomes. We find that transcriptional activation of the mevalonate pathway and steroid biosynthesis in liver is associated with the grass carp's adaptation from a carnivorous to an herbivorous diet. We believe that the grass carp genome could serve as an initial platform for breeding better-quality fish using a genomic approach.

A novel broadband light source based on supercontinuum (SC) generation seeded by random distributed feedback fiber laser (RFL) is proposed and demonstrated for the first time. A half-opened fiber cavity formed by FBG and TrueWave fiber is used to generate random lasing and SC simultaneously. Experimental results indicate that RFL can be used as an effective pump for generation of SC. SC with 20-dB bandwidth of >250 nm was obtained. Such a broadband SC light source seeded by RFL may pave a way to generate high power broadband RFLs for use in optical sensing and measurement.

In recent years, elderly people are suffering an increasingly severe problem in their home due to the falls. Falling down is the most common cause of death among the elderly. This paper proposed a falling detection algorithm based on a humanoid robot to monitor and detect the motion of the elderly who live alone. A stream of the videos obtained from the robot cameras are transmitted to the personal computer via Wi-Fi, and then the image data will be analyzed by the MATLAB procedure algorithm, including extracting foreground, eliminating noise from foreground, evaluating Motion History and determining ellipse statistical properties to determine whether a falling has happened. If a fall occurs, the robot will raise an alarm to call for help through microphone. This algorithm will help the elderly receive timely medical treatment in order to minimize the falling risk and the company of NAO will enhance the elderly's sense of security.

Broadly-tunable pulse generation in cavity-free graphene random lasers is reported, with tunable pulsewidths across two orders-of-magnitude to less-than 900 ps, tunable repetition over three orders-of-magnitude up to 3 MHz, and 41-dB singly-polarized extinction ratio.

The tremendous potential application in emerging two-dimensional layered materials such as black phosphorus (BP) has attracted great attention as nanoscale devices. In this paper, the effect of anisotropic negative differential resistance (NDR) in monolayer black phosphorus field-effect transistors (FETs) is reported by the first-principles computational study based on the non-equilibrium Green's function approach combined with density functional theory. The transport properties including current-voltage (I-V) relation and transmission spectrum of monolayer BP are investigated at different gate voltages (Vg). Further studies indicate that NDR occurs at a specific gate voltage in the armchair direction rather than in the zigzag direction. The decrease of current in I-V characteristics can be understood from the generation of non-conducting states region moving towards the Fermi level resulting in a reduction of the integration within corresponding energy range in the transmission spectrum. Our results offer useful guidance for designing FETs and other potential applications in nanoelectronic devices based on BP.