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Environmental chambers are a kind of equipment to simulate various conventional and extreme environments, which are usually applied to create various environmental conditions and conduct various studies related to environmental parameters. Through our review of literature of the past 30 years, environmental chambers have been mainly used in the following four aspects: pollutants’ emission characterization, human thermal comfort research, products and materials development and transformation and the reaction and behaviour of other living bodies such as animals and plants. In this paper, the current application of environmental chambers is summarized based on the research objectives, conditions and technical means. The purpose of this paper is to provide a review of the use of environmental chambers for research and analyze the current application of environmental chambers for the future application of environmental chambers and explore the direction of its future transformation and application.

DNA has shown great biocompatibility, programmable mechanical properties, and structural addressability at the nanometer scale, making it a versatile material for building high precision nanorobotics for biomedical applications. Herein, we present design principle, synthesis, and characterization of a DNA nanorobotic hand, called the “NanoGripper”, that contains a palm and four bendable fingers as inspired by human hands, bird claws, and bacteriophages evolved in nature. Each NanoGripper finger has three phalanges connected by two flexible and rotatable joints that are bendable in response to binding to other entities. Functions of the NanoGripper have been enabled and driven by the interactions between moieties attached to the fingers and their binding partners. We showcase that the NanoGripper can be engineered to interact with and capture various objects with different dimensions, including gold nanoparticles, gold NanoUrchins, and SARS-CoV-2 virions. When carrying multiple DNA aptamer nanoswitches programmed to generate fluorescent signal enhanced on a photonic crystal platform, the NanoGripper functions as a sensitive viral biosensor that detects intact SARS-CoV-2 virions in human saliva with a limit of detection of ∼ 100 copies/mL, providing RT-PCR equivalent sensitivity. Additionally, we use confocal microscopy to visualize how the NanoGripper-aptamer complex can effectively block viral entry into the host cells, indicating the viral inhibition. In summary, we report the design, synthesis, and characterization of a complex nanomachine that can be readily tailored for specific applications. The study highlights a path toward novel, feasible, and efficient solutions for the diagnosis and therapy of other diseases such as HIV and influenza.One-sentence summaryDesign, synthesis, characterization, and functional showcase of a human-hand like designer DNA nanobot

Release from enemies can lead to rapid evolution in invasive plants, including reduced metabolic investment in defence. Conversely, reassociation with enemies leads to renewed evolution of defence, but the potential costs of this evolution are poorly documented. We report increased resistance of the invader Ambrosia artemisiifolia after reassociation with a coevolved specialist herbivore, and that this increase corresponds with reduced abiotic stress tolerance. Herbivore resistance was higher, but drought tolerance was lower in plants from populations with a longer reassociation history, and this corresponded with changes in phenylpropanoids involved in insect resistance and abiotic stress tolerance. These changes were corroborated by shifts in the expression of underlying biosynthetic genes and plant anti-oxidants. Together, our findings suggest rapid evolution of plant traits after reassociation with coevolved enemies, resulting in genetically based shifts in investment between abiotic and biotic stress responses, providing insights into co-evolution, plant invasion and biological control.

Background: Various feature (variable) screening approaches have been proposed in the past decade to mitigate the impact of ultra-high dimensionality in classification and regression problems, including filter based methods such as sure independence screening, and wrapper based methods such as random forest. However, the former type of methods rely heavily on strong modelling assumptions while the latter ones requires an adequate sample size to make the data speak for themselves. These requirements can seldom be met in biochemical studies in cases where we have only access to ultra-high dimensional data with a complex structure and a small number of observations. Objective: In this research, we want to investigate the possibility of combining both filter based screening methods and random forest based screening methods in the regression context. Method: We have combined four state-of-art filter approaches, namely, sure independence screening (SIS), robust rank correlation based screening (RRCS), high dimensional ordinary least squares projection (HOLP) and a model free sure independence screening procedure based on the distance correlation (DCSIS) from the statistical community with a random forest based Boruta screening method from the machine learning community for regression problems. Result: Among all the combined methods, RF-DCSIS performs better than the other methods in terms of screening accuracy and prediction capability on the simulated scenarios and real benchmark datasets. Conclusion: By empirical study from both extensive simulation and real data, we have shown that both filter based screening and random forest based screening have their pros and cons, while a combination of both may lead to a better feature screening result and prediction capability.

Py-GC–MS Investigation of Pyrolysis Behaviors and Decomposition Products of α- and β-2,7,11-cembratriene-4,6-diols May 1, 2022 Shen Huang, Chen Yang, Ning Ma, Lifeng Zhou, Chunxiao Jia, Tao Wei, Duobin Mao LCGC North America, May 2022, Volume 40, Issue 5 Pages: 223–228 To study the thermal stability of cembratriene, α- and β-2, 7, 11-cembratriene-4, 6-diols (α- and β-CBT) were isolated from tobacco leaves. Thermogravimetric (TG) and differential thermogravimetric (DTG) analyses were used to evaluate the cleavage differences between the two compounds. The TGA results showed the peak temperatures (Tp) were 263.3 °C and 254.1 °C with the largest weight loss rate; the significant weight losses were 90.96% and 99.45%. Pyrolysis gas chromatography–mass spectrometry (Py-GC–MS) was employed for the pyrolysis products at different temperatures (300, 600, and 900 °C) under either N2 or an O2:N2 (10%:90%) mixture. The results showed that the major pyrolysates from α- and β-CBT were simple hydrocarbons, such as toluene, 1, 4-pentadiene, and p-xylene, as well as several important flavor compounds, such as 2-methylfuran, benzaldehyde, and 4-methylbenzaldehyde. More pyrolysis products were obtained at higher temperatures, and almost all of the harmful aromatic ingredients were produced at 900 °C. Importantly, solanone, a significant flavor component, was only obtained from the pyrolysis of α-CBT under 10% O2 in N2 at both 600 and 900 °C. The number of the pyrolysates changed with the change in pyrolysis temperature and the presence of oxygen. The study of the thermal behavior and pyrolysis products of these terpenoids could possibly suggest flavor precursors that could be used to provide specific flavors.

Background and Aims Regulation of macrophage polarization is a promising strategy for treating inflammatory bowel disease [IBD]. Tollip is an important negative regulator of Toll-like receptor [TLR]-mediated innate immunity with downregulated expression in the colon tissues of patients with IBD. This study aimed to regulate the expression of Tollip to affect macrophage polarization. Methods A molecular, targeted immunotherapy method was developed by linking mannose-modified trimethyl chitosan [MTC] with Tollip-expressing plasmids via ionic cross-linking, forming MTC-Tollip nanoparticles with a targeting function. MTC-Tollip selectively targeted mouse intestinal macrophages to regulate the polarization of macrophages for mucosal repair. Results Orally administered MTC-Tollip significantly elevated Tollip expression in intestinal tissue. Compared with MTC-negative control [NC]-treated mice in which colitis was induced with dextran sodium sulphate [DSS], the MTC-Tollip nanoparticle-treated mice exhibited decreased body weight loss and colon shortening, lower proinflammatory cytokine expression in colon tissues, and greater mucosal barrier integrity. MTC-Tollip treatment decreased TNF-α and iNOS expression but increased CD206 and Arg-1 expression in colon tissue. Tollip overexpression in mouse peritoneal macrophages inhibited lipopolysaccharide [LPS]-induced proinflammatory cytokine production and promoted IL-4-induced M2 expression. The progression of peritoneal macrophages extracted from Tollip−/− mice confirmed the effect of Tollip on macrophage polarization. Western blots showed that Tollip overexpression attenuated the upregulation of TLR pathway-associated targets in M1 macrophages. Conclusions MTC nanoparticles can be ‘intelligent’ carriers in immunotherapy. The modulation of Tollip expression in macrophages may be a novel treatment approach for IBD.

The traditional dynamic models of linear ultrasonic motor (LUSM) do not consider the influences of the preload force and the roughness of the contact surface of stator/slider on the performance of the motor, which unable to effectively describe the dynamic behavior of the motor. In this paper, a dynamic model is established for a V-shaped LUSM considering the influence of the preload force and the roughness of the contact surface of stator/slider on the dynamic behavior of the motor. The contact mechanism of the stator/slider and the influence of preload force on the stator parameters are studied and analyzed. The effectiveness of the developed model is verified by comparing with the analytical model that ignored the effect of the preload force on the stator parameters. The experimental results shown that the developed model can accurately reflect the dynamic characteristics of the motor, and the model will be helpful for the function prediction and precise control of the motor.

Due to defects of low-voltage and high-current output in new energy power generation system, it is necessary to raise the output voltage and realize further power conversion in the subsequent stage. In this paper, an innovative interleaved high step-up DC-DC converter is proposed. Considering the problems of non-common ground and limited gain in the previously proposed active network DC-DC boost converters, the active network structure is replaced by an interleaved parallel structure, in which charge pump units are employed, and a switched-capacitor unit is added to further improve the voltage gain. Finally, the experimental results of the 150W prototype show that the converter has higher gain, lower voltage stress in switch devices and higher efficiency. When the input voltage and output current are 16V and 1.25A respectively, the efficiency of the entire system can reach about 94.2%.

In this letter, we consider a distributed submodular maximization problem for multi-robot systems when attacked by adversaries. One of the major challenges for multi-robot systems is to increase resilience against failures or attacks. This is particularly important for distributed systems under attack as there is no central point of command that can detect, mitigate, and recover from attacks. Instead, a distributed multi-robot system must coordinate effectively to overcome adversarial attacks. In this work, our distributed submodular action selection problem models a broad set of scenarios where each robot in a multi-robot system has multiple action selections that may fulfill a global objective, such as exploration or target tracking. To increase resilience in this context, we propose a fully distributed algorithm to guide each robot's action selection when the system is attacked. The proposed algorithm guarantees performance in a worst-case scenario where up to a portion of the robots malfunction due to attacks. Importantly, the proposed algorithm is also consistent, as it is shown to converge to the same solution as a centralized method. Finally, a distributed resilient multi-robot exploration problem is presented to confirm the performance of the proposed algorithm.

We present a net-shaped DNA nanostructure (called "DNA Net" herein) design strategy for selective recognition and high-affinity capture of intact SARS-CoV-2 virions through spatial pattern-matching and multivalent interactions between the aptamers (targeting wild-type spike-RBD) positioned on the DNA Net and the trimeric spike glycoproteins displayed on the viral outer surface. Carrying a designer nanoswitch, the DNA Net-aptamers release fluorescence signals upon virus binding that are easily read with a handheld fluorimeter for a rapid (in 10 min), simple (mix-and-read), sensitive (PCR equivalent), room temperature compatible, and inexpensive (∼$1.26/test) COVID-19 test assay. The DNA Net-aptamers also impede authentic wild-type SARS-CoV-2 infection in cell culture with a near 1 × 10

This paper provides a general framework for modeling bonded-type piezoelectric linear motors considering the stress transferred by adhesive layer. A three-dimensional static model of stator is first developed by the principle of minimum potential energy and finite element. The stress transferred by adhesive layer could be simulated and analyzed for arbitrary bonding conditions. Basing on the static stress-transfer analysis, a quasi-static stress acted to substrate by piezoelectric elements is assumed and integrated into the substrate dynamic model. A pure mechanical dynamic model is developed for the electromechanical coupling system of stator. Furthermore, the whole-machine dynamic model of motor is presented by incorporating the frictional contact force into the dynamic model of the stator and an analytical model of the mover. Finally, a bonded-type piezoelectric linear motor with V-shaped stator is investigated as an example for simulations and experiments. The methodology presented here for simulating the transferred load of adhesive layer in bonded-type piezoelectric motor as well as for estimating the vibration characteristics of stator and output performances of motor. It is believed that the proposed method would be helpful to design and manufacture the prototypes due to the wider applicability of allowing for irregular geometry and any bonding conditions.

We introduce and study the problem of planning a trajectory for an agent to carry out a scouting mission while avoiding being detected by an adversarial opponent. This introduces a multi-objective version of classical visibility-based target search and pursuit-evasion problem. In our formulation, the agent receives a positive reward for increasing its visibility (by exploring new regions) and a negative penalty every time it is detected by the opponent. The objective is to find a finite-horizon path for the agent that balances the trade off between maximizing visibility and minimizing detectability. We model this problem as a discrete, sequential, two-player, zero-sum game. We use two types of game tree search algorithms to solve this problem: minimax search tree and Monte-Carlo search tree. Both search trees can yield the optimal policy but may require possibly exponential computational time and space. We first propose three pruning techniques to reduce the computational time while preserving optimality guarantees. When the agent and the opponent are located far from each other initially, we present a variable resolution technique with longer planning horizon to further reduce computational time. Simulation results show the effectiveness of the proposed strategies in terms of computational time.

DNA origami is typically used to fold a long single-stranded DNA scaffold into nanostructures with complex geometries using many short DNA staple strands. Integration of RNA into nucleic acid nanostructures is also possible, but has been less studied. In this research, we designed and characterized a hybrid RNA-scaffolded origami nanostructure with dimensions of ∼12 nm. We used 12 DNA staple strands to fold a 401 nt RNA scaffold into a ten-helix bundle with a honeycomb cross section. We verified the construction of the nanostructure using gel electrophoresis and atomic force microscopy. The DNA–RNA hybrid origami showed higher resistance to ribonuclease compared to a DNA–RNA duplex control. Our work shows potential use in folding long RNA, such as messenger RNA, into origami nanostructures that can be delivered into targeted cells as medicine or a vaccine., A mini DNA–RNA hybrid origami nanobrick with overall size close to 12 nanometer showed high resistance to nuclease digestion.

We present a net-shaped DNA nanostructure (called “DNA Net” herein) design strategy for selective recognition and high-affinity capture of the intact SARS-CoV-2 virions through spatial pattern-matching and multivalent interactions between the aptamers (targeting wild type spike-RBD) positioned on the DNA Net and the trimeric spike glycoproteins displayed on the viral outer surface. Carrying a designer nanoswitch, the DNA Net-aptamers releases fluorescent signal upon virus binding that is easily read by a hand-held fluorimeter for a rapid (in 10 mins), simple (mix- and-read), sensitive (PCR equivalent), room temperature compatible, and inexpensive (∼ $1.26/test) COVID-19 test assay. The DNA Net-aptamers also impede authentic wild-type SARS-CoV-2 infection in cell culture with a near 1×103-fold enhancement of the monomeric aptamer. Furthermore, our DNA Net design principle and strategy can be customized to tackle other life-threatening and economically influential viruses like influenza and HIV, whose surfaces carry class-I viral envelope glycoproteins like the SARS-CoV-2 spikes in trimeric forms.

The pinewood nematode, Bursaphelenchus xylophilus, is one of the most destructive invasive species worldwide, causing the wilting and eventual death of pine trees. Despite the recognition of their economic and environmental significance, it has thus far been impossible to study the detailed gene functions of plant-parasitic nematodes (PPNs) using conventional forward genetics and transgenic methods. However, as a reverse genetics technology, RNA interference (RNAi) facilitates the study of the functional genes of nematodes, including B. xylophilus. This paper outlines a new protocol for RNAi of the ppm-1 gene in B. xylophilus, which has been reported to play crucial roles in the development and reproduction of other pathogenic nematodes. For RNAi, the T7 promoter was linked to the 5'-terminal of the target fragment by polymerase chain reaction (PCR), and double-stranded RNA (dsRNA) was synthesized by in vitro transcription. Subsequently, dsRNA delivery was accomplished by soaking the nematodes in a dsRNA solution mixed with synthetic neurostimulants. Synchronized juveniles of B. xylophilus (approximately 20,000 individuals) were washed and soaked in dsRNA (0.8 µg/mL) in the soaking buffer for 24 h in the dark at 25 °C. The same quantity of nematodes was placed in a soaking buffer without dsRNA as a control. Meanwhile, another identical quantity of nematodes was placed in a soaking buffer with green fluorescent protein (gfp) gene dsRNA as a control. After soaking, the expression level of the target transcripts was determined using real-time quantitative PCR. The effects of RNAi were then confirmed using microscopic observation of the phenotypes and a comparison of the body size of the adults among the groups. The current protocol can help advance research to better understand the functions of the genes of B. xylophilus and other parasitic nematodes toward developing control strategies through genetic engineering.