Characteristic noise features in light transmission across membrane protein undergoing photocycle

We demonstrate a technique based on noise measurements which can be utilized to study dynamical processes in protein assembly. Direct visualization of dynamics in membrane protein system such as bacteriorhodopsin (bR) upon photostimulation are quite challenging. bR represents a model system where the stimulus-triggered structural dynamics and biological functions are directly correlated. Our method utilizes a pump-probe near field microscopy method in the transmission mode and involves analyzing the transmittance fluctuations from a finite size of molecular assembly. Probability density distributions indicating the effects of finite size and statistical correlations appear as a characteristic frequency distribution in the noise spectra of bR whose origin can be traced to photocycle kinetics. Valuable insight into the molecular processes were obtained from the noise studies of bR and its mutant D96N as a function of external parameters such as temperature, humidity or presence of an additional pump source.Comment: 13 Pages, 3 Figures, To appear in the Journal of Chemical Physics, Vol. 134, Issue

Observation of Bessel beams from electric-field-induced patterns on polymer surfaces

We report the observation of Bessel- like beams from periodic patterns induced on viscoelastic polymer surfaces by electric field. The patterns resembling a microaxicon array originate from electrohydrodynamic instabilities in polymer films, where the feature dimensions can be easily controlled. The output beam characteristics from these patterns revealed characteristic traits of Bessel beams

Machine learning approaches for large scale classification of produce

Abstract The analysis and identification of different attributes of produce such as taxonomy, vendor, and organic nature is vital to verifying product authenticity in a distribution network. Though a variety of analysis techniques have been studied in the past, we present a novel data-centric approach to classifying produce attributes. We employed visible and near infrared (NIR) spectroscopy on over 75,000 samples across several fruit and vegetable varieties. This yielded 0.90–0.98 and 0.98–0.99 classification accuracies for taxonomy and farmer classes, respectively. The most significant factors in the visible spectrum were variations in the produce color due to chlorophyll and anthocyanins. In the infrared spectrum, we observed that the varying water and sugar content levels were critical to obtaining high classification accuracies. High quality spectral data along with an optimal tuning of hyperparameters in the support vector machine (SVM) was also key to achieving high classification accuracies. In addition to demonstrating exceptional accuracies on test data, we explored insights behind the classifications, and identified the highest performing approaches using cross validation. We presented data collection guidelines, experimental design parameters, and machine learning optimization parameters for the replication of studies involving large sample sizes

Three-dimensional microlasers based on polymer fibers fabricated by electrospinning

We report three-dimensional mirror-less lasing from non-cylindrical dye doped polystyrene fibers drawn using an electrospinning procedure where the fiber cross-sectional shape and dimension could be controlled. Signatures of three dimensional etalon like modes were observed corresponding to the transverse and axial quantization of the wave vector. Low lasing thresholds of the order of 200 nJ were achieved along with moderate Q factors

Scanning technique.

<p>(a) Small section, high resolution scanning. The user holds a monopod mounted Kinect at close range (0.5–1.5 m) from the target. (b) Large section or complete 360° scanning. The user mounts Kinect on a body supported rig and walks around the artifact (1.5–4.5 m from target) to complete the scan. Sketch by Francis Goeltner.</p

Small volume high resolution scans: Section of the left side of the mandible of FMNH PR 2081.

<p>(a) Front view, length of the segment here is about 0.9 m. (b) Side view of the left side of the mandible. (c) Lingual view of the left side of the mandible. (d) & (e) Surangular fenestra which is 2.9 cm deep and about 3.1 cm wide. Number of faces in the mesh in 2(a-c) are 284,273.</p

Insight Into Myocardial Microstructure of Athletes and Hypertrophic Cardiomyopathy Patients Using Diffusion Tensor Imaging

Background Hypertrophic cardiomyopathy (HCM) remains the commonest cause of sudden cardiac death among young athletes. Differentiating between physiologically adaptive left ventricular (LV) hypertrophy observed in athletes' hearts and pathological HCM remains challenging. By quantifying the diffusion of water molecules, diffusion tensor imaging (DTI) MRI allows voxelwise characterization of myocardial microstructure. Purpose To explore microstructural differences between healthy volunteers, athletes, and HCM patients using DTI. Study Type Prospective cohort. Population Twenty healthy volunteers, 20 athletes, and 20 HCM patients. Field Strength/Sequence 3T/DTI spin echo. Assessment In‐house MatLab software was used to derive mean diffusivity (MD) and fractional anisotropy (FA) as markers of amplitude and anisotropy of the diffusion of water molecules, and secondary eigenvector angles (E2A)—reflecting the orientations of laminar sheetlets. Statistical Tests Independent samples t‐tests were used to detect statistical significance between any two cohorts. Analysis of variance was utilized for detecting the statistical difference between the three cohorts. Statistical tests were two‐tailed. A result was considered statistically significant at P ≤ 0.05. Results DTI markers were significantly different between HCM, athletes, and volunteers. HCM patients had significantly higher global MD and E2A, and significantly lower FA than athletes and volunteers. (MDHCM = 1.52 ± 0.06 × 10−3 mm2/s, MDAthletes = 1.49 ± 0.03 × 10−3 mm2/s, MDvolunteers = 1.47 ± 0.02 × 10−3 mm2/s, P < 0.05; E2AHCM = 58.8 ± 4°, E2Aathletes = 47 ± 5°, E2Avolunteers = 38.5 ± 7°, P < 0.05; FAHCM = 0.30 ± 0.02, FAAthletes = 0.35 ± 0.02, FAvolunteers = 0.36 ± 0.03, P < 0.05). HCM patients had significantly higher E2A in their thickest segments compared to the remote (E2Athickest = 66.8 ± 7, E2Aremote = 51.2 ± 9, P < 0.05). Data Conclusion DTI depicts an increase in amplitude and isotropy of diffusion in the myocardium of HCM compared to athletes and volunteers as reflected by increased MD and decreased FA values. While significantly higher E2A values in HCM and athletes reflect steeper configurations of the myocardial sheetlets than in volunteers, HCM patients demonstrated an eccentric rise in E2A in their thickest segments, while athletes demonstrated a concentric rise. Further studies are required to determine the diagnostic capabilities of DTI. Evidence Level 1 Technical Efficacy Stage 2ISSN:1053-1807ISSN:1522-258

Insight Into Myocardial Microstructure of Athletes and Hypertrophic Cardiomyopathy Patients Using Diffusion Tensor Imaging

Background: Hypertrophic cardiomyopathy (HCM) remains the commonest cause of sudden cardiac death among young athletes. Differentiating between physiologically adaptive left ventricular (LV) hypertrophy observed in athletes' hearts and pathological HCM remains challenging. By quantifying the diffusion of water molecules, diffusion tensor imaging (DTI) MRI allows voxelwise characterization of myocardial microstructure. Purpose: To explore microstructural differences between healthy volunteers, athletes, and HCM patients using DTI. Study type: Prospective cohort. Population: Twenty healthy volunteers, 20 athletes, and 20 HCM patients. Field strength/sequence: 3T/DTI spin echo. Assessment: In-house MatLab software was used to derive mean diffusivity (MD) and fractional anisotropy (FA) as markers of amplitude and anisotropy of the diffusion of water molecules, and secondary eigenvector angles (E2A)-reflecting the orientations of laminar sheetlets. Statistical tests: Independent samples t-tests were used to detect statistical significance between any two cohorts. Analysis of variance was utilized for detecting the statistical difference between the three cohorts. Statistical tests were two-tailed. A result was considered statistically significant at P ≤ 0.05. Results: DTI markers were significantly different between HCM, athletes, and volunteers. HCM patients had significantly higher global MD and E2A, and significantly lower FA than athletes and volunteers. (MDHCM = 1.52 ± 0.06 × 10-3 mm2 /s, MDAthletes = 1.49 ± 0.03 × 10-3 mm2 /s, MDvolunteers = 1.47 ± 0.02 × 10-3 mm2 /s, P < 0.05; E2AHCM = 58.8 ± 4°, E2Aathletes = 47 ± 5°, E2Avolunteers = 38.5 ± 7°, P < 0.05; FAHCM = 0.30 ± 0.02, FAAthletes = 0.35 ± 0.02, FAvolunteers = 0.36 ± 0.03, P < 0.05). HCM patients had significantly higher E2A in their thickest segments compared to the remote (E2Athickest = 66.8 ± 7, E2Aremote = 51.2 ± 9, P < 0.05)