Spatiotemporal self-similar fiber laser

In this Letter, we demonstrate, to the best of our knowledge, the first spatiotemporally mode-locked fiber laser with self-similar pulse evolution. The multimode fiber oscillator generates parabolic amplifier similaritons at 1030 nm with 90 mW average power, 2.3 ps duration, and 37.9 MHz repetition rate. Remarkably, we observe experimentally a near-Gaussian beam quality (M^2<1.4) at the output of the highly multimode fiber. The output pulses are compressed to 192 fs via an external grating compressor. Numerical simulations are performed to investigate the cavity dynamics which confirm experimental observations of self-similar pulse propagation. The reported results open a new direction to investigate new types of pulse besides beam shaping and nonlinear dynamics in spatiotemporal mode-locked fiber lasers.Comment: 8 pages, 5 figure

Exploring the factors affecting the motivation for learning from the perspective of public health students: A qualitative study

Objective. Despite the significant role of motivation in achieving success among public health students, students often do not demonstrate adequate motivation for learning and education. This study was performed to determine factors affecting the motivation for learning from the perspective of public health students via content analysis approach. Methods. This qualitative study was conducted at Kurdistan University of Medical Sciences in Sanandaj, Iran in 2017. 15 students were included in the study by using purposive sampling. Data were collected through personal interviews, group discussions, and field notes, and they were analyzed through conventional content analysis. Several parameters were taken into account to support the accuracy and the strength of the data: acceptability, confirmability, and transferability. Results. Five categories were derived from the data analysis, including “University Policy”, “Health Status”, “Teacher’s Role”, “Student-Related Factors” and “University Facilities”. Attention to the health status and its priority in the opinion of people, authorities, and educational system were the most important factors involved in the students’ motivation for learning. Conclusions. To increase motivation for learning, students have diverse needs that should be met. Attention to the components of motivation for learning not only enhances academic achievement but also promotes the formation of health behaviors in the society

Multimode Optical Fiber Transmission with a Deep Learning Network

Multimode fibers (MMF) are an example of a highly scattering medium which scramble the coherent light propagating within them and produce seemingly random patterns. Thus, for applications such as imaging and image projection through a MMF, careful measurements of the relationship between inputs and outputs of the fiber are required. We show, as a proof of concept, that a deep learning neural network can learn the input-output relationship in a 0.75 m long MMF. Specifically, we demonstrate that a deep convolutional neural network (CNN) can learn the non-linear relationships between the amplitude of the speckle pattern obtained at the output of the fiber and the phase or amplitude at the input of the fiber. Effectively the network performs a non-linear inversion task. We obtained image fidelity (correlation) of ~98% compared with the image obtained using the measured matrix of the system. We further show that the network can be trained for transfer learning, i.e. it can transmit images through the MMF which belongs to another class which were not used for training/testing.Comment: Published in Nature Light: Science and Applications under the same titl

Single mode output by controlling the spatiotemporal nonlinearities in mode-locked femtosecond multimode fiber lasers

The performance of fiber mode-locked lasers is limited due to the high nonlinearity induced by the spatial confinement of the single-mode fiber core. To massively increase the pulse energy of the femtosecond pulses, amplification is obtained outside the oscillator. Recently, spatiotemporal mode-locking has been proposed as a new path to fiber lasers. However, the beam quality was either highly multimode and/or with low pulse energy. Here we present an approach to reach high energy per pulse directly in the mode-locked multimode fiber oscillator with a near single-mode output beam. Our approach relies on spatial self-beam cleaning via the nonlinear Kerr effect and we demonstrate a multimode fiber oscillator with M2<1.13 beam profile, up to 24 nJ energy and sub-100 fs compressed duration. The reported approach is further power scalable with larger core sized fibers and could benefit applications that require high power ultrashort lasers with commercially available optical fibers.Comment: Manuscript 10 pages, 4 figures Supplementary 7 pages, 8 figure

All-fiber spatiotemporally mode-locked laser with multimode fiber-based filtering

We demonstrate the first multimode fiber interference-based filtering in an all-fiber spatiotemporally mode-locked laser. The oscillator generates dissipative soliton pulses at 1036 nm with 12 mW average power, 6.24 ps duration and 24.3 MHz repetition rate. The reported pulse energy (0.5 nJ) represents ~4 times improvement over the previously reported single-mode all-normal dispersion mode-locked lasers with multimode interference-based filtering. Numerical simulations are performed to reveal cavity and spatiotemporal mode-locking dynamics. The proposed oscillator presents an alternative approach to achieve spatiotemporal mode-locking with an all-fiber design that can be fabricated simply.Comment: 6 pages, 6 figure

Backpropagation-free Training of Deep Physical Neural Networks

Recent years have witnessed the outstanding success of deep learning in various fields such as vision and natural language processing. This success is largely indebted to the massive size of deep learning models that is expected to increase unceasingly. This growth of the deep learning models is accompanied by issues related to their considerable energy consumption, both during the training and inference phases, as well as their scalability. Although a number of work based on unconventional physical systems have been proposed which addresses the issue of energy efficiency in the inference phase, efficient training of deep learning models has remained unaddressed. So far, training of digital deep learning models mainly relies on backpropagation, which is not suitable for physical implementation as it requires perfect knowledge of the computation performed in the so-called forward pass of the neural network. Here, we tackle this issue by proposing a simple deep neural network architecture augmented by a biologically plausible learning algorithm, referred to as "model-free forward-forward training". The proposed architecture enables training deep physical neural networks consisting of layers of physical nonlinear systems, without requiring detailed knowledge of the nonlinear physical layers' properties. We show that our method outperforms state-of-the-art hardware-aware training methods by improving training speed, decreasing digital computations, and reducing power consumption in physical systems. We demonstrate the adaptability of the proposed method, even in systems exposed to dynamic or unpredictable external perturbations. To showcase the universality of our approach, we train diverse wave-based physical neural networks that vary in the underlying wave phenomenon and the type of non-linearity they use, to perform vowel and image classification tasks experimentally.Comment: 11 pages, 5 figure

Exploring the factors affecting the motivation for learning from the perspective of public health students: A qualitative study

Objective. Despite the significant role of motivation in achieving success among public health students, students often do not demonstrate adequate motivation for learning and education. This study was performed to determine factors affecting the motivation for learning from the perspective of public health students via content analysis approach. Methods. This qualitative study was conducted at Kurdistan University of Medical Sciences in Sanandaj, Iran in 2017. 15 students were included in the study by using purposive sampling. Data were collected through personal interviews, group discussions, and field notes, and they were analyzed through conventional content analysis. Several parameters were taken into account to support the accuracy and the strength of the data: acceptability, confirmability, and transferability. Results. Five categories were derived from the data analysis, including “University Policy”, “Health Status”, “Teacher’s Role”, “Student-Related Factors” and “University Facilities”. Attention to the health status and its priority in the opinion of people, authorities, and educational system were the most important factors involved in the students’ motivation for learning. Conclusions. To increase motivation for learning, students have diverse needs that should be met. Attention to the components of motivation for learning not only enhances academic achievement but also promotes the formation of health behaviors in the society

Methadone maintenance treatment program in prisons from the perspective of medical and non-medical prison staff: a qualitative study in Iran

Background: As one of the most important components of harm reduction strategy for high-risk groups, following the HIV epidemics, Methadone Maintenance Treatment (MMT) has been initiated in prisoners since 2003. In this paper, we aimed to assess the advantages and shortcomings of the MMT program from the perspective of people who were involved with the delivery of prison healthcare in Iran. Methods: On the basis of grounded theory and through conducting 14 Focus Group Discussions (FGDs), 7 FGDs among physicians, consultants, experts, and 7 FGDs among directors and managers of prisons (n= 140) have been performed. The respondents were asked about positive and negative elements of the MMT program in Iranian prisons. Results: This study included a total of 48 themes, of which 22 themes were related to advantages and the other 26 were about shortcomings of MMT programs in the prisons. According to participants’ views “reduction of illegal drug use and high-risk injection”, “reduction of potentially high-risk behaviors” and “making positive attitudes” were the main advantages of MMT in prisons, while issues such as “inaccurate implementation”, “lack of skilled manpower” and “poor care after release from prison” were among the main shortcomings of MMT program. Conclusions: MMT program in Iran’s prisons has achieved remarkable success in the field of harm reduction, but to obtain much more significant results, its shortcomings and weaknesses must be also taken into account by policy-makers

Characterization of the exopolysaccharides from Rhodotorula minuta IBRC-M 30135 and evaluation of their emulsifying, antioxidant and antiproliferative activities

Some microorganisms such as yeasts can produce high molecular weight and valuable polymers that known as exopolysaccharides (EPSs). Given the functional properties of yeast exopolysaccharides (EPSs) and a few numbers of studies in this field, the present study was aimed to characterize the EPSs from Rhodotorula minuta (IBRC-M 30135) and to evaluate their emulsifying, antioxidant and antiproliferative activities. R.minuta excreted 1.2 +/- 0.1 g of the EPSs per 1000 ml of fermentation medium. Glucose, mannose and rhamnose were found as main monosaccharides of the EPSs (49, 38 and 13 mol%, respectively) through gas chromatography-mass spectrometry (GC-MS) analysis. In addition, three EPS fractions were obtained with the molecular weights of 356, 500 and 220 kDa. The water retention capacity of the EPSs was 342 +/- 27%. The EPSs exhibited relatively good oil-emulsifying activity and the enhanced synergism between the R.minuta's EPSs and commercially used hydrocolloids (guar gum and sodium alginate) was observed. In vitro, antioxidant activity was investigated against DPPH, hydroxyl and superoxide free radicals. At a concentration of 10 mg/ml, the DPPH, hydroxyl and superoxide free radicals scavenging activities were 21.8 +/- 0.7%, 24.6 +/- 1.4% and 12.1 +/- 0.4%, respectively; and the scavenging activities against all were higher than hyaluronic acid. In addition, the treatment of human breast adenocarcinoma (MCF7) and Madin-Darby Canine Kidney (MDCK) cell lines with 20-1000 mu g/ml of the EPSs caused no significant differences in the cells proliferation (P>0.05). These results indicated the promising potential of the EPSs from R.minuta as non-toxic and biocompatible compounds for using in food, cosmetic and pharmaceutical fields