Anisotropy of Charge Transport in a Uniaxially Aligned Fused Electron-Deficient Polymer Processed by Solution Shear Coating

Precise control of the microstructure in organic semiconductors (OSCs) is essential for developing high-performance organic electronic devices. Here, a comprehensive charge transport characterization of two recently reported rigid-rod conjugated polymers that do not contain single bonds in the main chain is reported. It is demonstrated that the molecular design of the polymer makes it possible to achieve an extended linear backbone structure, which can be directly visualized by high-resolution scanning tunneling microscopy (STM). The rigid structure of the polymers allows the formation of thin films with uniaxially aligned polymer chains by using a simple one-step solution-shear/bar coating technique. These aligned films show a high optical anisotropy with a dichroic ratio of up to a factor of 6. Transport measurements performed using top-gate bottom-contact field-effect transistors exhibit a high saturation electron mobility of 0.2 cm² V⁻¹ s⁻¹ along the alignment direction, which is more than six times higher than the value reported in the previous work. This work demonstrates that this new class of polymers is able to achieve mobility values comparable to state-of-the-art n-type polymers and identifies an effective processing strategy for this class of rigid-rod polymer system to optimize their charge transport properties.     

Comparative study on the reachable workspaces of regular and irregular axially symmetric hexapod robots

Journal of Mechanical Science and Technology - Six-legged hexapod walking robots are well-known for their intrinsic stability during navigation and 6-DoF object manipulation. The robot must be...     

Impacts of electrification & automation of public bus transportation on sustainability—A case study in Singapore

Forschung im Ingenieurwesen - Electrification and automation are attracting interest from the public-transportation sector for their potential to improve energy efficiency, cost efficiency, and...     

Composite high frequency predictive scheme for efficient 2-D up-scaling performance

Multimedia Tools and Applications - This paper presents a new composite scheme to tackle the non-uniform blurring that arises because of image up-scaling. The image up-scaling results in...     

Diagnosis of breast cancer based on modern mammography using hybrid transfer learning

Breast cancer is a common cancer in women. Early detection of breast cancer in particular and cancer, in general, can considerably increase the survival rate of women, and it can be much more effective. This paper mainly focuses on the transfer learning process to detect breast cancer. Modified VGG (MVGG) is proposed and implemented on datasets of 2D and 3D images of mammograms. Experimental results showed that the proposed hybrid transfer learning model (a fusion of MVGG and ImageNet) provides an accuracy of 94.3%. On the other hand, only the proposed MVGG architecture provides an accuracy of 89.8%. So, it is precisely stated that the proposed hybrid pre-trained network outperforms other compared Convolutional Neural Networks. The proposed architecture can be considered as an effective tool for radiologists to decrease the false negative and false positive rates. Therefore, the efficiency of mammography analysis will be improved.

     

Spatial Variation of Thermokinetics and Associated Microstructural Evolution in Laser Surface Engineered IN718: Precursor to Additive Manufacturing

Metallurgical and Materials Transactions A - The spatial variation of thermokinetic parameters has a significant influence on solidification and microstructural aspects such as grain orientation,...     

Spectroscopic models for real-time monitoring of cell culture processes using spatiotemporal just-in-time Gaussian processes

Spectroscopic methods play an instrumental role in the implementation of the U.S. Food and Drug Administration outlined process analytical technology for biopharmaceutical manufacturing. Industrial spectroscopic calibration models are typically developed in an offline setting using traditional methods, such as partial least squares and principal component regression. Apart from the limiting performances of these conventional models under time-varying operating conditions, these methods require access to extensive historical data, which are seldom available in biopharmaceutical manufacturing. In this article, we propose a novel spatiotemporal just-in-time learning (ST-JITL) based spectroscopic model calibration platform for automatic training and maintenance of calibration models using routine batch data. The proposed ST-JITL framework uses Gaussian processes (GPs) for local model calibration. A GP model not only exhibits superior performance over traditional methods but also provides credibility intervals around the model predictions. The efficacy of the ST-JITL based model calibration platform is demonstrated in predicting the critical performance parameters of an industrial cell culture process.     

Hyaluronidases in Human Diseases

With the burgeoning interest in hyaluronic acid (HA) in recent years, hyaluronidases (HYALs) have come to light for their role in regulating catabolism of HA and its molecular weight (MW) distribution in various tissues. Of the six hyaluronidase-like gene sequences in the human genome, HYALs 1 and 2 are of particular significance because they are the primary hyaluronidases active in human somatic tissue. Perhaps more importantly, for the sake of this review, they cleave anti-inflammatory and anti-fibrotic high-molecular-weight HA into pro-inflammatory and pro-fibrotic oligosaccharides. With this, HYALs regulate HA degradation and thus the development and progression of various diseases. Given the dearth of literature focusing specifically on HYALs in the past decade, this review seeks to expound their role in human diseases of the skin, heart, kidneys, and more. The review will delve into the molecular mechanisms and pathways of HYALs and discuss current and potential future therapeutic benefits of HYALs as a clinical treatment.     

Mass accommodation coefficients of fresh and aged biomass-burning emissions

Most chemical transport models treat the partitioning of semi-volatile organic compounds (SVOCs) with the assumption of instantaneous thermodynamic equilibrium. However, the mass accommodation coefficients, α, of biomass-burning organic aerosol (BBOA) are largely unconstrained. During the FLAME-IV campaign, we thermally perturbed aged and fresh BBOA with a variable residence time thermodenuder and measured the resulting change in particle mass concentration to restore equilibrium. We used this equilibration profile to retrieve an effective α for components of BBOA that dictated this profile and found that the mass accommodation coefficients lie within the range 0.1 ? α ? 1. A simple plume dilution model shows a maximum of only a 7% difference between a dynamical and an instantaneous equilibrium partitioning model using our best-estimate value for α. This supports continued use of the equilibrium assumption to treat partitioning of biomass-burning emissions in chemical-transport models.

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