Broad spectral sliced multiwavelength source with a mode locked fiber laser

A simple multi-wavelength source is demonstrated based on spectral slicing of supercontinuum (SC) light using a Sagnac loop mirror. A mode locked fiber laser with pulse width of 800 fs is employed to generate the SC in photonic crystal fiber (PCF). The SC light extending from 1200 nm up to the wavelength region above 1750 nm is obtained at the amplified pulse pump power of 30 dBm. By slicing the SC with a loop mirror, a multiwavelength comb spectrum is obtained with different channel spacing for different operating wavelength region. Spacings of 1.5, 2.3, and 2.9 nm are shown at wavelength regions of 1220, 1450, and 1730 nm, respectively. It is also observed that the signal to noise ratio (SNR) increases from 15 to 20 dB as the operating wavelength increases from 1220 to 1730 nm region.     

Stable double spacing multiwavelength Brillouin-Erbium doped fiber laser based on highly nonlinear fiber

A double frequency spaced multiwavelength Brillouin-Erbium doped fiber laser (BEDFL) with figure-of-eight cavity have been successfully developed and tested. Double frequency spacing is achieved by using a piece of 2 km of highly nonlinear fiber (HNLF) as a gain medium. Figure-of-eight configuration removes the odd order Stokes signals via a four-port circulator. Fifteen Stokes channels are simultaneously generated with a spacing of 0.154 nm that is around 20 GHz, when the Brillouin pump and 980 nm pump powers are fixed at the optimized values of 6 dBm and 40 mW, respectively. Fourteen anti stoke channels are also obtained, which are generated through four wave mixing (FWM) process in the laser cavity. The output is smooth triangular comb. The BEFL can also be tuned from 1526.5 to 1567.5 nm.     

Dual-cavity dual-output multi-wavelength fiber laser based on nonlinear polarization rotation effect

We demonstrate a multi-wavelength fiber laser based on nonlinear polarization rotation (NPR) in dual-cavity configuration with two output ports. The laser employs a piece of erbium doped fiber (EDF) and semiconductor optical amplifier (SOA) as the gain medium in a separate cavity. By incorporating PCF in the dual cavity the non-linear polarization rotation (NPR) effect is enhanced and thus higher output and more oscillating lasing can be achieved. The laser produces three strong lines with a spacing of 2.40 nm and side mode suppression ratio (SMSR) of more than 10 dB at 1535 nm region. Another output produces 8 lines of optical comb with a spacing of 0.54 at 1570 nm region.     

Objective Supervised Machine Learning-Based Classification and Inference of Biological Neuronal Networks

The classification of biological neuron types and networks poses challenges to the full understanding of the human brain’s organisation and functioning. In this paper, we develop a novel objective classification model of biological neuronal morphology and electrical types and their networks, based on the attributes of neuronal communication using supervised machine learning solutions. This presents advantages compared to the existing approaches in neuroinformatics since the data related to mutual information or delay between neurons obtained from spike trains are more abundant than conventional morphological data. We constructed two open-access computational platforms of various neuronal circuits from the Blue Brain Project realistic models, named Neurpy and Neurgen. Then, we investigated how we could perform network tomography with cortical neuronal circuits for the morphological, topological and electrical classification of neurons. We extracted the simulated data of 10,000 network topology combinations with five layers, 25 morphological type (m-type) cells, and 14 electrical type (e-type) cells. We applied the data to several different classifiers (including Support Vector Machine (SVM), Decision Trees, Random Forest, and Artificial Neural Networks). We achieved accuracies of up to 70%, and the inference of biological network structures using network tomography reached up to 65% of accuracy. Objective classification of biological networks can be achieved with cascaded machine learning methods using neuron communication data. SVM methods seem to perform better amongst used techniques. Our research not only contributes to existing classification efforts but sets the road-map for future usage of brain–machine interfaces towards an in vivo objective classification of neurons as a sensing mechanism of the brain’s structure.     

Multifunctional Derivatives of Spiropyrrolidine Tethered Indeno-Quinoxaline Heterocyclic Hybrids as Potent Antimicrobial,Antioxidant and Antidiabetic Agents: Design,Synthesis, In Vitro and In Silico Approaches

To combat emerging antimicrobial-resistant microbes, there is an urgent need to develop new antimicrobials with better therapeutic profiles. For this, a series of 13 new spiropyrrolidine derivatives were designed, synthesized, characterized and evaluated for their in vitro antimicrobial, antioxidant and antidiabetic potential. Antimicrobial results revealed that the designed compounds displayed good activity against clinical isolated strains, with 5d being the most potent (MIC 3.95 mM against Staphylococcus aureus ATCC 25923) compared to tetracycline (MIC 576.01 mM). The antioxidant activity was assessed by trapping DPPH, ABTS and FRAP assays. The results suggest remarkable antioxidant potential of all synthesized compounds, particularly 5c, exhibiting the strongest activity with IC₅₀ of 3.26 ± 0.32 mM (DPPH), 7.03 ± 0.07 mM (ABTS) and 3.69 ± 0.72 mM (FRAP). Tested for their α-amylase inhibitory effect, the examined analogues display a variable degree of α-amylase activity with IC₅₀ ranging between 0.55 ± 0.38 mM and 2.19 ± 0.23 mM compared to acarbose (IC₅₀ 1.19 ± 0.02 mM), with the most active compounds being 5d, followed by 5c and 5j, affording IC₅₀ of 0.55 ± 0.38 mM, 0.92 ± 0.10 mM, and 0.95 ± 0.14 mM, respectively. Preliminary structure–activity relationships revealed the importance of such substituents in enhancing the activity. Furthermore, the ADME screening test was applied to optimize the physicochemical properties and determine their drug-like characteristics. Binding interactions and stability between ligands and active residues of the investigated enzymes were confirmed through molecular docking and dynamic simulation study. These findings provided guidance for further developing leading new spiropyrrolidine scaffolds with improved dual antimicrobial and antidiabetic activities.