A Genomic Comparative Analysis of Bacillus Coagulans Unravels the Genetic Potential of MA-13 Strain for Biotechnological Applications

The production of bio-chemicals requires the use of microbial strains with efficient substrate conversion and excellent environmental robustness, such as Bacillus coagulans spp. So far the genomes of about 50 strains have been sequenced. Herein, we report a comparative genomic analysis of nine strains on the full repertoire of CAZymes, secretion systems, and resistance mechanisms to environmental challenges. Moreover, B. coagulans Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) immune system along with CRISPR-associated Cas) genes, was also analysed. Overall, this study expands our understanding of the strains genomic diversity of B. coagulans to fully exploit its potential in biotechnological applications.

Policy-based monocular vision autonomous quadrotor obstacle avoidance method

Aiming at the obstacle avoidance control problem of small quadrotor, a method of quadrotor obstacle avoidance based on reinforcement learning is proposed. The proposed method can make training converge quickly and has good environmental robustness. The proposed methods include: (1) a framework adopts perception module and decision module to improve the generalization ability of the obstacle avoidance model; (2) An Actor-Critic framework-based Proximal Policy Optimization (PPO) algorithm to provide quadrotor with policy-based decision-making capabilities; The experimental simulation results show that the strategy-based framework converges quickly and has a high success rate, the training time is much lower than that of the value-based framework. The monocular vision observation ability is limited, which leads to deviations between local observation and global state, So LSTM layer is usually added to increase model performance. Policy -based decision can have a good obstacle avoidance effect without adding the LSTM layer, and have good generalization ability after short relearning after changing.

A Multimodal Hydrogel Soft-Robotic Sensor for Multi-Functional Perception

Soft robots, with their unique and outstanding capabilities of environmental conformation, natural sealing against elements, as well as being insensitive to magnetic/electrical effects, are ideal candidates for extreme environment applications. However, sensing for soft robots in such harsh conditions would still be challenging, especially under large temperature change and complex, large deformations. Existing soft sensing approaches using liquid-metal medium compromise between large deformation and environmental robustness, limiting their real-world applicability. In this work, we propose a multimodal solid-state soft sensor using hydrogel and silicone. By exploiting the conductance and transparency of hydrogel, we could deploy both optical and resistive sensing in one sensing component. This novel combination enables us to benefit from the in-situ measurement discrepancies between the optical and electrical signal, to extract multifunctional measurements. Following this approach, prototype solid-state soft sensors were designed and fabricated, a dedicated neural network was built to extract the sensory information. Stretching and twisting were measured using the same sensor even at large deformations. In addition, exploiting the distinctive responses against temperature change, we could estimate environmental temperatures simultaneously. Results are promising for the proposed solid-state multimodal approach of soft sensors for multifunctional perception under extreme conditions.

Microwave induced in-situ formation of SiC nanowires on SiCNO ceramic aerogels with excellent electromagnetic wave absorption performance

Electromagnetic absorption (EMA) materials with light weight and harsh environmental robustness are highly desired and crucially important in the stealth of high-speed vehicles. However, meeting these two requirements is always a great challenge, which excluded the most attractive lightweight candidates, such as carbon-based materials. In this study, SiCnw-reinforced SiCNO (SiCnw/SiCNO) composite aerogels were fabricated through the in-situ growth of SiCnw in polymer-derived SiCNO ceramic aerogels by using catalyst-assisted microwave heating at ultra-low temperature and in short time. The phase composition, microstructure, and EMA property of the SiCnw/SiCNO composite aerogels were systematically investigated. The results indicated that the morphology and phase composition of SiCnw/SiCNO composite aerogels can be regulated easily by varying the microwave treatment temperature. The composite aerogels show excellent EMA property with minimum reflection loss of −23.9 [email protected] GHz, −26.5 [email protected] GHz, and −20.4 [email protected] GHz and the corresponding effective bandwidth of 5.2 GHz, 3.2 GHz, and 4.8 GHz at 2.0 mm thickness for microwave treatment at 600 °C, 800 °C, and 1000 °C, respectively, which is much better than that of SiCN ceramic aerogels. The superior EMA performance is mainly attributed to the improved impedance matching, multi-reflection, multi-interfacial polarization, and micro current caused by migration of hopping electrons.

Enabling Real-time Sign Language Translation on Mobile Platforms with On-board Depth Cameras

In this work we present SUGO, a depth video-based system for translating sign language to text using a smartphone's front camera. While exploiting depth-only videos offer benefits such as being less privacy-invasive compared to using RGB videos, it introduces new challenges which include dealing with low video resolutions and the sensors' sensitiveness towards user motion. We overcome these challenges by diversifying our sign language video dataset to be robust to various usage scenarios via data augmentation and design a set of schemes to emphasize human gestures from the input images for effective sign detection. The inference engine of SUGO is based on a 3-dimensional convolutional neural network (3DCNN) to classify a sequence of video frames as a pre-trained word. Furthermore, the overall operations are designed to be light-weight so that sign language translation takes place in real-time using only the resources available on a smartphone, with no help from cloud servers nor external sensing components. Specifically, to train and test SUGO, we collect sign language data from 20 individuals for 50 Korean Sign Language words, summing up to a dataset of ~5,000 sign gestures and collect additional in-the-wild data to evaluate the performance of SUGO in real-world usage scenarios with different lighting conditions and daily activities. Comprehensively, our extensive evaluations show that SUGO can properly classify sign words with an accuracy of up to 91% and also suggest that the system is suitable (in terms of resource usage, latency, and environmental robustness) to enable a fully mobile solution for sign language translation.

Prototyping an S-Band Conformal Line Array Antenna on a Partial Wing Surface

This paper presents the design, prototyping, and testing of an S-Band conformal array on a partial wing surface. The array elements are series fed microstrip patch antennas fabricated entirely through additive manufacturing (AM) technology using a combination of fused deposition modeling and thermal spray. A robust material set of ULTEM 9085 and copper alloy is used for a good balance of mechanical/environmental robustness and RF performance, while also offering a viable path forward for a future fielded design. The focus of this paper is on AM multi-material fabrication, fundamental print settings and material characterization, and antenna testing. AM characterization coupons are utilized to improve the accuracy of the RF antenna model, which showed excellent agreement with the prototype measurements.

Prototyping an S-Band Conformal Line Array Antenna on a Partial Wing Surface

This paper presents the design, prototyping, and testing of an S-Band conformal array on a partial wing surface. The array elements are series fed microstrip patch antennas fabricated entirely through additive manufacturing (AM) technology using a combination of fused deposition modeling and thermal spray. A robust material set of ULTEM 9085 and copper alloy is used for a good balance of mechanical/environmental robustness and RF performance, while also offering a viable path forward for a future fielded design. The focus of this paper is on AM multi-material fabrication, fundamental print settings and material characterization, and antenna testing. AM characterization coupons are utilized to improve the accuracy of the RF antenna model, which showed excellent agreement with the prototype measurements.

Recrystallization of CsPbBr3 Nanoparticles in Fluoropolymer Nonwoven Mats for Down- and Up-Conversion of Light

Inorganic halides perovskite CsPbX3 (X = Cl, Br, and I or mixed halide systems Cl/Br and Br/I) nanoparticles are efficient light-conversion objects that have attracted significant attention due to their broadband tunability over the entire visible spectral range of 410–700 nm and high quantum yield of up to 95%. Here, we demonstrate a new method of recrystallization of CsPbBr3 nanoparticles inside the electrospun fluoropolymer fibers. We have synthesized nonwoven tetrafluoroethylene mats embedding CsPbBr3 nanoparticles using inexpensive commercial precursors and syringe electrospinning equipment. The fabricated nonwoven mat samples demonstrated both down-conversion of UV light to 506 nm and up-conversion of IR femtosecond laser radiation to 513 nm green photoluminescence characterized by narrow emission line-widths of 35 nm. Nanoparticle formation inside nonwoven fibers was confirmed by TEM imaging and water stability tests controlled by fluorimetry measurements. The combination of enhanced optical properties of CsPbBr3 nanoparticles and mechanical stability and environmental robustness of highly deformable nonwoven fluoropolymer mats is appealing for flexible optoelectronic applications, while the industry-friendly fabrication method is attractive for commercial implementations.

Conditionally essential genes for survival during starvation in Enterococcus faecium E745

Background The nosocomial pathogen Enterococcus faecium can survive for prolonged periods of time on surfaces in the absence of nutrients. This trait is thought to contribute to the ability of E. faecium to spread among patients in hospitals. There is currently a lack of data on the mechanisms that are responsible for the ability of E. faecium to survive in the absence of nutrients. Results We performed a high-throughput transposon mutant library screening (Tn-seq) to identify genes that have a role in long-term survival during incubation in phosphate-buffered saline (PBS) at 20 °C. A total of 24 genes were identified by Tn-seq to contribute to survival in PBS, with functions associated with the general stress response, DNA repair, metabolism, and membrane homeostasis. The gene which was quantitatively most important for survival in PBS was usp (locus tag: EfmE745_02439), which is predicted to encode a 17.4 kDa universal stress protein. After generating a targeted deletion mutant in usp, we were able to confirm that usp significantly contributes to survival in PBS and this defect was restored by in trans complementation. The usp gene is present in 99% of a set of 1644 E. faecium genomes that collectively span the diversity of the species. Conclusions We postulate that usp is a key determinant for the remarkable environmental robustness of E. faecium. Further mechanistic studies into usp and other genes identified in this study may shed further light on the mechanisms by which E. faecium can survive in the absence of nutrients for prolonged periods of time.