Dropout Ratio Research Articles

Effects of social-interactive engagement on the dropout ratio in online learning: insights from MOOC

ABSTRACTIn online learning, the high dropout ratio is a serious problem and reflects a poor level of motivation in e-learning programmes. Social-interactive engagement may greatly affect users’ attitudes and choices in many fields; among these, online learning is inevitably impacted by factors such as social connections. To study the impact of social-interactive engagement on the dropout ratio and learning progress, iMOOC was employed as the study object using data from 619 courses and 2,071,147 learners, as well as 19,451,428 learning records. As engagement is a process of collecting experiences, the learner’s experience plays a significant role in reducing the dropout ratio. Social-interactive engagement helps to reduce the dropout ratio; thus, learners should be encouraged to engage in online activities, such as discussions, note sharing, commenting and Q&A, to alleviate the feelings of being disconnected and isolated. Through an empirical study, we also find that the longer a learner's registered time is, the lower the dropout ratio. From the perspective of the courses themselves, the dropout ratios of shorter or more difficult courses are lower than those of longer or less-difficult courses. This paper provides theoretical and practical recommendations for reducing the dropout ratio in online learning and improving learning efficiency.

Effect of baseline CD(4)(+) T cell count on drop-out of antiretroviral therapy in HIV infected persons in Guangxi Zhuang Autonomous Region, 2008-2015

Objective: To investigate the effect of baseline CD(4)(+) T cell count (CD(4)) on drop-out of antiretroviral therapy (ART) in HIV infected persons. Methods: Retrospective cohort was conducted in this study. HIV infected persons aged≥18 years and receiving free ART for the first time in Guangxi Zhuang Autonomous Region (Guangxi) from 2008 to 2015 were selected from the antiretroviral treatment database of National Comprehensive HIV/AIDS Information System, with follow-up conducted till May 30, 2016. Cause-specific Cox proportional hazard models were used to evaluate effect of different CD(4) on the drop-out of ART in the HIV infected persons. Results: A total of 58 502 eligible study participants were included in this retrospective cohort study. The average drop-out ratio was 4.8/100 person-years. After controlling the following baseline covariates: age, sex, marital status, route of HIV infection, WHO clinical stage before ART, initial/current ART regiment, ART regiment adjustment, and year of initiating ART for potential confounding, the adjusted HR of drop-out for HIV infected persons with 200- cells/μl, 351-cells/μl and ≥500 cells/μl were 1.110 (95%CI: 1.053-1.171, P<0.001), 1.391 (95%CI: 1.278-1.514, P<0.001) and 1.695 (95%CI: 1.497-1.918, P<0.001), respectively, in risk for drop-out compared with those with baseline CD(4)<200 cells/μl. Among the HIV infected persons, 56.0% (1 601/2 861) of drug withdrawal was due to poor compliance with medication. Conclusions: With the increase of baseline CD(4) when initiating ART, the risk for the drop-out in HIV infected persons increased significantly. To further reduce the drop-out of ART, it is important to take CD(4) into account in initiating ART and to strengthen the health education on treatment compliancy and training for healthcare providers.

Safety, compliance, and efficacy of newly developed videogame based exercises using wearable sensors for aged people

Videogame based exercise, namely exergame, is an innovative approach to enhance physical activity in the elderly. This study was done to evaluate the safety, compliance, adherence and efficacy of exergames using wearable sensors. Sixty aged people (77.5 ± 6.4 years) played 3 exergames including abdominal bracing, Q-setting and balance training games for 12 weeks. Wearable pressure sensors were applied on the abdominal and quadriceps muscles and magnetic sensors under the soles to monitor accuracy and intensity of targeted activities. Safety and compliance were assessed by dropout ratio and personal interviews. Adherence to progression of sessions was measured by calculating total exertional index, the duration of exertional pressure or step-on status, and compared between the earlier and later weeks. A simplified frailty screening battery was devised to measure skeletal muscle mass, grip strength, walking speed, unipedal stance test and short geriatric depression scale before and after the exercise program. Fifty-four participants completed. Dropout reaseons were lack of time (4), ankle fracture by unrelated activity (1) and fear of aggravating pre-existing sciatica (1). 14.8% and 5.6% of participants complained of leg pain and difficulty in exercising, respectively. The total exertional indices were significantly increased in the later phase of sessions, showing 35.9 ± 23.9 kPa·min vs 41.6 ± 28.0 kPa·min ( P = 0.013), 129.5 ± 76.5 kPa·min vs 147.4 ± 81.2 kPa·min ( P = 0.040), and 12.1 ± 3.0 vs 13.1 ± 2.6 steps ( P = 0.018) for abdominal bracing, Q-setting and balance training games, respectively. There were statistically significant improvements in skeletal muscle index (33.7 ± 3.7% vs 34.4 ± 4.1%, P = 0.004), grip strength (20.0 ± 5.6 kgf vs 21.5 ± 5.5 kgf, P = 0.000), walking speed (0.89 ± 0.19 m/s vs 1.26 ± 0.19 m/s, P = 0.000), and balance ability (10.8 ± 7.6 s vs 15.4 ± 9.8 s, P = 0.000) after the exercises. This study demonstrates that three exergames developed in this study can be safely done with high compliance for 12 weeks, improving skeletal muscle mass, muscle strength, function and balance.

Europe 2020 Implementation as Driver of Economic Performance and Competitiveness. Panel Analysis of CEE Countries

The Europe 2020 strategy is the EU strategy for sustainable and inclusive growth, for fighting the structural weaknesses of the European economies, and for improving their competitiveness. In this paper, we determined the most important ratios of the Europe 2020 Strategy impacting on economic performance expressed as the growth of the GDP per capita, and on economic competitiveness expressed as the share of the countries’ exports in total world exports for some selected Central and Eastern European (CEE) countries (Poland, Slovakia, Bulgaria, Hungary, the Czech Republic, and Romania) using co-integration tests and OLS panel estimations with a dataset between 2004 (after four of these selected countries acceded to EU) and 2015 (the latest available data for all the ratios we used in our analysis). Our findings show that the tertiary level of education is the most important factor, positively correlated with both endogenous variables mentioned above. Other important factors for achieving the economic performance and competitiveness goals are the school dropout ratio, the share of renewable energy in final energy consumption, and the employment rate.

Forecasting students' success in an open university

In recent years, students' performance prediction has been identified as one of the most essential and challenging research topics for educational institutions. The necessity for exploitation and analysis of data originating from several educational contexts has led to a widespread implementation of familiar machine learning methods trying to effectively analyse students' academic behaviour and predict their performance. The early detection of low performers is of major importance for open universities seeking to decrease dropout ratios, improve educational outcomes and provide high quality education. This paper introduces an ensemble of classification and regression algorithms for predicting students' performance in a distance web-based course. Several state-of-the-art machine learning methods have also been applied to compare the efficiency of our method. A plethora of experiments have been conducted for this purpose, using data provided by the Hellenic Open University. The proposed ensemble combines classification and regression rules and is as accurate as the powerful ensembles, while the produced model remains comprehensive. In addition, a prototype software support tool has been designed and it simulates the presented ensemble.

Sanitation and water supply in schools and girls' educational progression in Zambia

Abstract There is much anecdotal evidence related to the importance of Water, Sanitation and Hygiene (WASH) in schools for girls' educational progression, yet a lack of comprehensive quantitative studies on linkages between WASH and educational indicators disaggregated by gender and grade. This paper aims to fill that gap by testing the hypothesis that the presence of water and sanitation facilities in schools can increase female-to-male enrolment ratios and reduce repetition and drop-out-ratios for girls, especially at ages when they menstruate. Quantitative analyses were undertaken of Education Management Information System (EMIS) data collected from over 10,000 schools in Zambia, to explore relationships between WASH facility provision in schools and enrolment, repetition and drop-out ratios disaggregated by gender and grade. Results indicated that improved sanitation provision in schools was correlated with high female-to-male enrolment ratios, and reduced repetition and drop-out ratios, especially for girls. A t-test revealed significant gender differences in grades 5–8 when many girls start to experience their menstrual cycle. Improved water supply in schools, however, did not reveal the same relationship. The findings confirm possible linkages between adequate toilets in schools and educational progression of girls.

PROBLEMS OF RURAL GIRL STUDENTS IN HIGHEREDUCATIONAL INSTITUTION

Higher Education means Tertiary Education, which is under taken in colleges (or) universities, and it may be delivered virtually (or) at a distance. There are a large number of problems that girl student’s face for developing their career potential. Some of the serious problems are as Follows: -Problems related to Home, Educational Institutions, Society, Economic problems, Educational problems. Rural girls belong to disable as per the data, Girl dropout ratio has increase with the enhanced pattern of gender inequality in access to education, which seems to be attainment and from urban to rural and to disadvantaged group in the society.Gender equality and the empowerment of women are gaining ground worldwide. There are more women Heads of state (or) Government then ever and the highest proportion of women serving as government ministers women are excursing ever-greater influence in business. More girls are going to school, and are growing up healthier and better equipped to realize their potential. Girl student’s suffer in many case, both form discrimination and from inequality treatment. It is easy to imagine that the difficulties encountered by rural girl students in obtaining higher education. Providing access to local relevant high-qualities education and training opportunities in critical to retaining rural girl students in Higher Educational Institutions.

Efficacy of sequential three-step empirical therapy for chronic cough.

Background:Empirical three-step therapy has been proved in just one hospital. This study aimed to demonstrate applicability of the sequential empirical three-step therapy for chronic cough in different clinical settings.Methods:Sequential empirical three-step therapy was given to patients with chronic cough in one tertiary and three secondary care respiratory clinics. Recruiters were initially treated with methoxyphenamine compound as the first-step therapy, followed by corticosteroids as the second-step therapy and the combination of a proton-pump inhibitor and a prokinetic agent as the third-step therapy. The efficacy of the therapy was verified according to the changes in cough symptom score between pre- and post-treatment, and compared among the different clinics.Results:In total 155 patients in one tertiary clinic and 193 patients in secondary care clinics were recruited. The total dropout ratio is significantly higher in the secondary care clinics than that in the tertiary clinic (9.3% versus 3.2%, p = 0.023). The therapeutic success rate for cough was 38.7% at first-step therapy, 32.3% at second-step therapy and 20.0% at third-step therapy in the tertiary clinic, and comparable to corresponding 49.7%, 31.1% and 4.1% in secondary care clinics. Furthermore, the overall cough resolution rate was not significantly different (91.0% versus 85.0%, p = 0.091). However, the efficacy of the third-step therapy is much higher (20.0% versus 4.1%, p = 0.001) in the tertiary clinic than in the secondary care clinics.Conclusions:Sequential empirical three-step therapy is universally efficacious and useful for management of chronic cough in different clinical settings.

PD11-08 COMPUTER-AIDED DIAGNOSIS OF PROSTATE CANCER USING A DEEP NEURAL NETWORKS ALGORITHM IN PRE-BIOPSY MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING

You have accessJournal of UrologyImaging/Radiology: Uroradiology II1 Apr 2017PD11-08 COMPUTER-AIDED DIAGNOSIS OF PROSTATE CANCER USING A DEEP NEURAL NETWORKS ALGORITHM IN PRE-BIOPSY MULTIPARAMETRIC MAGNETIC RESONANCE IMAGING Junichiro Ishioka, Yoh Matsuoka, Masaya Itoh, Masaharu Inoue, Toshiki Kijima, Soichiro Yoshida, Minato Yokoyama, Kazutaka Saito, Kazunori Kihara, Yasuhisa Fujii, Hiroshi Tanaka, and Tomo Kimura Junichiro IshiokaJunichiro Ishioka More articles by this author , Yoh MatsuokaYoh Matsuoka More articles by this author , Masaya ItohMasaya Itoh More articles by this author , Masaharu InoueMasaharu Inoue More articles by this author , Toshiki KijimaToshiki Kijima More articles by this author , Soichiro YoshidaSoichiro Yoshida More articles by this author , Minato YokoyamaMinato Yokoyama More articles by this author , Kazutaka SaitoKazutaka Saito More articles by this author , Kazunori KiharaKazunori Kihara More articles by this author , Yasuhisa FujiiYasuhisa Fujii More articles by this author , Hiroshi TanakaHiroshi Tanaka More articles by this author , and Tomo KimuraTomo Kimura More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2017.02.584AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Magnetic resonance imaging (MRI) provides a noninvasive assessment of the prostate that improves the detection of prostate cancer and can reduce unnecessary biopsies. The excessive variation in the performance and interpretation of MRI is, however, a major barrier to its widespread acceptance and use. In this study, we employed computer-aided diagnosis with a deep neural networks algorithm for prostate cancer detection using multiparametric MRI (mpMRI). METHODS Between 2010 and 2015, 354 patients underwent extended systematic prostate biopsy with MRI-targeted biopsy (MTB), and 209 patients with negative mpMRI underwent systematic prostate biopsy (SB). All patients with PSA levels of less than 20 ng/ml and negative findings of digital rectal examination were included as subjects. mpMRI was interpreted by an experienced radiologist. For the supervised training using deep neural network architecture, we selected 163 mpMRI-positive patients who were diagnosed with prostate cancer by MTB and 135 mpMRI-negative patients who were not diagnosed with prostate cancer by SB. We chose representative T2-weighted and diffusion-weighted (DW) MRI images from both mpMRI-positive and mpMRI-negative patients. The 298 pairs of T2-weighted and DW images labeled as ″cancer″ or ″no cancer″ were randomly divided into 248 training and 50 test datasets, and the measure of diagnostic accuracy was calculated. The structure of the deep neural network model we used contains an input layer, three fully connected hidden layers, and an output layer (figure 1). The layers in the networks have ReLu non-linear activation units, and their learning rate was 0.01 for 10 epochs with a dropout ratio of 0.5. RESULTS In the 50 hold-out validation test datasets, the mean area under the curve and the accuracy were 0.84 (0.72-0.99) and 0.81 (0.72-0.96). The mean positive predictive value, negative predictive value, sensitivity, and specificity of the algorithm were 0.89 (0.74-1.00), 0.75 (0.50-1.00), 0.76 (0.50-1.00), and 0.88 (0.18-1.00), respectively. CONCLUSIONS Computer-aided diagnosis with a deep neural networks algorithm for prostate cancer with mpMRI can provide reproducible interpretation and a greater level of standardization and consistency. © 2017FiguresReferencesRelatedDetails Volume 197Issue 4SApril 2017Page: e209 Advertisement Copyright & Permissions© 2017MetricsAuthor Information Junichiro Ishioka More articles by this author Yoh Matsuoka More articles by this author Masaya Itoh More articles by this author Masaharu Inoue More articles by this author Toshiki Kijima More articles by this author Soichiro Yoshida More articles by this author Minato Yokoyama More articles by this author Kazutaka Saito More articles by this author Kazunori Kihara More articles by this author Yasuhisa Fujii More articles by this author Hiroshi Tanaka More articles by this author Tomo Kimura More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...

Atypical antipsychotics as add-on treatment in late-life depression.

BackgroundSecond-generation antipsychotics (SGAs) have been used in the augmentation of treatment-resistant depression. However, little is known about their effectiveness, tolerability, and adverse events in the treatment of late-life depression, which were the aim of this study.MethodsThe retrospective data of patients aged >65 years who had a major depressive episode with inadequate response to antidepressant treatment and had adjuvant SGA treatment were analyzed. The outcome measures were the number of the patients who continued to use SGAs in the fourth and twelfth weeks, adverse events, and changes in symptoms of depression.ResultsThirty-five patients were screened: 21 (60%) had quetiapine, twelve (34.28%) had aripiprazole, and two (5.71%) had olanzapine adjuvant treatment. The mean age was 72.17±5.02 years, and 65.7% of the patients were women. The mean daily dose was 85.71±47.80 mg for quetiapine, 3.33±1.23 mg for aripiprazole, and 3.75±1.76 mg for olanzapine. The Geriatric Depression Scale scores of all patients were significantly decreased in the fourth week and were significant in the aripiprazole group (P=0.02). Of the 35 patients, 23 (65.7%) patients discontinued the study within 12 weeks. The frequency of adverse events was similar in all SGAs, and the most common were sedation, dizziness, constipation, and orthostatic hypotension with quetiapine, and akathisia and headache because of aripiprazole.ConclusionThis study indicates that dropout ratio of patients with SGAs is high, and a subgroup of patients with late-life depression may benefit from SGAs. Effectiveness is significant in aripiprazole, and adverse events of SGAs were not serious but common in elderly patients.

Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network.

We present a pipeline for the visual localization and classification of agricultural pest insects by computing a saliency map and applying deep convolutional neural network (DCNN) learning. First, we used a global contrast region-based approach to compute a saliency map for localizing pest insect objects. Bounding squares containing targets were then extracted, resized to a fixed size, and used to construct a large standard database called Pest ID. This database was then utilized for self-learning of local image features which were, in turn, used for classification by DCNN. DCNN learning optimized the critical parameters, including size, number and convolutional stride of local receptive fields, dropout ratio and the final loss function. To demonstrate the practical utility of using DCNN, we explored different architectures by shrinking depth and width, and found effective sizes that can act as alternatives for practical applications. On the test set of paddy field images, our architectures achieved a mean Accuracy Precision (mAP) of 0.951, a significant improvement over previous methods.

Cognitive abilities of health and art college students a pilot study.

[Purpose] The selection of a college major is a struggle that high school students undergo every year; however, there is a dearth of studies examining the role of cognitive ability tests as a tool for determining the aptitude of prospective students. Hence, the purpose of this study was to assess cognitive ability differences among students. [Subjects and Methods] A convenience sample of 60 college students (30 health science and 30 art students) with a mean age of 19 ± 1.6 years, voluntarily participated in this study. Cognitive ability was assessed using the self-administered Cognitive Assessment of Minnesota (CAM) scale under the supervision of a researcher. [Results] The findings indicated that there was a significant cognitive ability difference between health science and art students, especially in the cognitive components of knowledge, calculation, and thinking. However, the difference in the social cognitive component of both the health science and art students was not significant. [Conclusion] The results indicate that the health science students’ cognitive abilities were better than those of the art students. This finding implies that it is important for high school graduates to undertake a cognitive ability assessment prior to choosing a subject major. Hence, it is recommended that cognitive scales should be included as an aptitude assessment tool for the decision-makers and prospective students to determine an appropriate career, since it might reduce the percentage of university drop-out ratio.

Prevalence of Depression and Associated Factors among Addis Ababa University Students, Addis Abeba, Ethiopia

Depression could affect the student’s academic success and his future such as withdrawal from study. Dropout ratio was found two-times higher in first-year students compared to second or third year students. It also causes people all across the world to have feelings of sadness, helplessness, worthlessness, and guilt. One of the important reasons in the current study is lack of data on the extent of mental disorders especially in higher learning institutions.

Medium-based noninvasive preimplantation genetic diagnosis for human α-thalassemias-SEA.

To develop a noninvasive medium-based preimplantation genetic diagnosis (PGD) test for α-thalassemias-SEA.The embryos of α-thalassemia-SEA carriers undergoing in vitro fertilization (IVF) were cultured. Single cells were biopsied from blastomeres and subjected to fluorescent gap polymerase chain reaction (PCR) analysis; the spent culture media that contained embryo genomic DNA and corresponding blastocysts as verification were subjected to quantitative-PCR (Q-PCR) detection of α-thalassemia-SEA. The diagnosis efficiency and allele dropout (ADO) ratio were calculated, and the cell-free DNA concentration was quantitatively assessed in the culture medium.The diagnosis efficiency of medium-based α-thalassemias–SEA detection significantly increased compared with that of biopsy-based fluorescent gap PCR analysis (88.6% vs 82.1%, P < 0.05). There is no significant difference regarding ADO ratio between them. The optimal time for medium-based α-thalassemias–SEA detection is Day 5 (D5) following IVF.Medium-based α-thalassemias–SEA detection could represent a novel, quick, and noninvasive approach for carriers to undergo IVF and PGD.

P-49 * CHARACTERIZING DROP-OUT AMONG PATIENTS AT METHADONE MAINTENANCE (MMT) CLINICS IN VIETNAM

Introduction. By 2013, approximately 15,000 MMT patients were being treated in Vietnam. The national goal is to have 80,000 patients on MMT by 2015. While increasing the number of patients, retaining patients on MMT is equally important. Methods. The Drop-out ratio was calculated and reasons for drop out identified based on program monitoring during 2011-2013. The cumulative number of patients included in this analysis was 6213 at 17 clinics in 6 provinces. Results. The rate of patient drop-out was less than 4% monthly in all clinics, but cumulatively up to 24% of patients enrolled in treatment dropped out the 3 year period. Reasons for drop included patients arrested by police (25%), moved to other clinics (4%), returned to rehabilitation (3%), and voluntarily stopping treatment (3%). The reason was unknown for a high proportion of loss to follow-up (55%). Conclusions. Drop-out is serious threat to the success of the MMT program in Vietnam. MMT clinic staff should provide education and counseling for patients to avoid illegal activities, arrest and interruption of MMT. Research should be conducted to understand the characteristics of drop-out patients and develop more effective interventions for improving retention.

Paradise lost or paradise regained? Changes in admission system affect academic performance and drop-out rates of medical students

Background: The Austrian State medical universities had to change their admission system in 2005. Until this year admission to medical studies was unrestricted. Innsbruck Medical University chose the Eignungstest für das Medizinstudium in der Schweiz (EMS) aptitude test for admission testing.Aims and objectives: Did the implementation of a selection process affect the academic performance and drop-out rates of students according to gender?Methods: Two groups of students were compared: ‘open admission’ (2002–2004), and ‘selected’ (2006–2009). Academic performance was tested according to results in the final exams after year 1 (SIP 1; SIP, summative integrierte Prüfung) and after year 3 (SIP 3). Drop-out rates were recorded using the registration system of the university.Results: Both, male and female ‘selected’ students had a higher passing rate regarding SIP 1 and they passed SIP 1 in shorter time and using fewer attempts than the open admission group. The percentage in passing SIP 3 did not change due to change in admission. The drop-out rates were significantly reduced for male and female students. ‘Unselected’ female students had a significantly higher drop-out ratio than ‘unselected’ male counterparts. After EMS testing, the drop-out ratios of female and male students were not significantly different.Conclusion: Selected applicants were more able and better motivated to study medicine.

Time-dependent changes in DNA stability in decomposing teeth over 18 months

Objective. The objective was to use a dual quantitative and qualitative approach to analyze the dental DNA degradation produced by the passage of time since tooth death under controlled environmental conditions. Materials and methods. Sixty human teeth were stored at room temperature for 0, 1, 3, 6, 12 or 18 months post-extraction. DNA quantification was determined by real-time quantitative PCR using a QuantifilerTM kit. DNA quality was assessed by the allelic dropout ratio between the smallest and largest loci obtained after STR genotyping and using an AmpFlSTR® Identifiler™ PCR kit. We also evaluated differences of DNA concentration related to gender and tooth position. Results. DNA concentration significantly reduced in 1 month post-extraction, stabilized between 1–12 months post-extraction, but decreased again at 18 months post-extraction. Interestingly, a significant reduction of the allelic dropout ratio (DNA quality) was only detected at 18 months post-extraction. Conclusions. Stability of dental DNA decreased over time, differently affecting the amount and quality of the DNA in a time-dependent process over the first 18 months post-extraction. These results have a potential use in post-mortem intervals in human teeth in controlled environmental conditions.

Study of Short‐ and Long‐Term Storage of Teeth and Its Influence on DNA

DNA degradation can interfere with the resolution of forensic cases. Allelic dropout often reduces the opportunity for adequate comparisons between degraded and reference samples. This study analyzed DNA degradation in 24 extracted teeth after storage at room temperature for 0, 2, 5, and 10 years. DNA concentration, quantified by dot-blot hybridization, declined significantly for the first 2 years, but there was no significant further degradation from the second to the tenth year of storage. COfiler analysis was used and the allelic dropout ratio for the amelogenin locus relative to CSF1PO locus was also estimated. Statistically significant differences were found between fresh teeth and teeth from the 2- and 5-year groups but not from the 10-year group. Under our storage conditions most of the DNA degradation occurred during the first 2 years. Further research is needed to control for individual and external factors that could affect DNA.

Statistical measures of the power dropout ratio in semiconductor lasers subject to optical feedback

The influence of the optical feedback ratio and bias current on the mean and the standard deviation of the power dropout ratio of low-frequency fluctuations in external-cavity semiconductor lasers has been studied experimentally. The power dropout ratio was found to increase with increasing optical feedback ratio and to decrease with increasing bias current.

10-GHz, 13-ps erbium fiber laser employing soliton pulse shortening

An actively mode-locked single-polarization erbium fiber laser modulated at 10 GHz utilizes intracavity soliton formation to produce 1.3-ps pulses, well below the Kuizenga-Siegman limit, without passive mode locking. The observed degree of pulse shortening agrees with the predictions of recently developed soliton laser models. The pulse dropout ratio was measured to be less than 10(-12), and the rms amplitude and phase jitter are less than 1.1% and 0.16 ps, respectively.