Electrospun Polyvinyl Alcohol/Cellulose Nanocrystals Composite Nanofibrous Filter: Investigation of Fabrication and Application

Particulate matter (PM) pollution has become a global environmental issue because it poses threat to public health. To protect individuals from PM exposure, one common method is using air filters for indoor air purification. However, conventional air filters have various drawbacks, such as high air resistance, the filters are not fabricated with environmentally friendly technology, and they cannot be easily regenerated. In this dissertation, a new electrospun poly(vinyl alcohol) (PVA)/cellulose nanocrystals (CNCs) composite nanofibrous filter was successfully developed. This PVA/CNCs composite material was demonstrated as air filter for the first time. The CNCs improved the filtration performance by increasing the surface charge density of the electrospinning suspension and thereby reducing diameter of fibers. High PM2.5 removal efficiency was achieved (99.1%) with low pressure drop (91 Pa) at a relatively high airflow velocity (0.2 m s-1), under extremely polluted condition (PM2.5 mass concentration \u3e500 μg m-3). The integral effect of various electrospinning suspension properties on filtration performance was also investigated using response surface methodology. With a face-centered central composite design, the operating parameters for fabricating PVA/CNCs air filters were optimized, and the optimum conditions were a suspension concentration of 7.34% and a CNCs percentage of 20%. Additionally, the water-soluble PVA/CNCs composite was converted to be completely water-resistant when the electrospun material was heated at 140 oC for only 5 min. The mechanism of the change of water solubility of the fibers was investigated systematically. Our results revealed that increased crystallinity is the key factor for improving the aqueous stability, and CNCs provided additional nucleation sites for PVA crystallization during both electrospinning and heating process. The heated filters were effectively regenerated by water washing and the filtration performance was satisfactorily maintained. Because both PVA and CNCs are nontoxic and biodegradable, no organic solvents or crosslinking agents were used in the whole fabrication process, and the heating process is facile, the method proposed in this dissertation for fabricating electrospun PVA/CNCs nanofibrous filters is environmentally friendly and cost-effectively. This new cellulose-based air filter, which possesses high removal efficiency for PM, low pressure drop, and long lifetime, is very promising

Di-μ-methanolato-κ4 O:O-bis[tri­chlorido(dimethyl­formamide-κO)tin(IV)]

The title compound, [Sn2(CH3O)2Cl6(C3H7NO)2], contains two hexa­coordinated SnIV atoms symmetrically bridged by two deprotonated methanol ligands, with an inversion center in the middle of the planar Sn2O2 ring. The other sites of the distorted octa­hedral coordination geometry of the SnIV atom are occupied by three Cl atoms and one O atom from a dimethyl­formamide mol­ecule. The complex mol­ecules are connected by weak C—H⋯Cl hydrogen bonds into a two-dimensional supra­molecular network parallel to (10)

Optimal Distributed Controller Design for Nonlinear Coupled Dynamical Networks

This paper is concerned with the optimal distributed impulsive controller design for globally exponential synchronization of nonlinear dynamical networks with coupling delay. By the Lyapunov-Razumikhin method, a novel criterion is proposed to guarantee the global exponential synchronization of the coupled delayed network with distributed impulsive control in terms of matrix inequalities. The sum of coupling strengths of the distributed impulsive control is minimized to save the control effort. Finally, the effectiveness of the proposed method has been demonstrated by some simulations

RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Model

Inspired by the recent success of large language models (LLMs) like ChatGPT, researchers start to explore the adoption of LLMs for agile hardware design, such as generating design RTL based on natural-language instructions. However, in existing works, their target designs are all relatively simple and in a small scale, and proposed by the authors themselves, making a fair comparison among different LLM solutions challenging. In addition, many prior works only focus on the design correctness, without evaluating the design qualities of generated design RTL. In this work, we propose an open-source benchmark named RTLLM, for generating design RTL with natural language instructions. To systematically evaluate the auto-generated design RTL, we summarized three progressive goals, named syntax goal, functionality goal, and design quality goal. This benchmark can automatically provide a quantitative evaluation of any given LLM-based solution. Furthermore, we propose an easy-to-use yet surprisingly effective prompt engineering technique named self-planning, which proves to significantly boost the performance of GPT-3.5 in our proposed benchmark

High genetic abundance of Rpi-blb2/Mi-1.2/Cami gene family in Solanaceae

Relative genomic positions of genes among potato (upper), pepper (middle) and tomato (lower) along chromosome 6. (DOCX 282 kb

μ-2-Amino­terephthalato-κ2 O 1:O 4-bis­[triphenyl­tin(IV)]

The title compound, [Sn2(C6H5)6(C8H5NO4)], contains two triphenyl­tin groups bridged by a 2-amino­terephthalate ligand. The two SnIV centers have similar distorted tetra­hedral coordination geometries. Each SnIV atom is bonded to three phenyl C atoms and one O atom from a carboxyl­ate group. The other O atom of the carboxyl­ate group has a weak inter­action with the Sn atom. The amino group is disordered over two sites, with site-occupancy factors of 0.779 (11) and 0.221 (11). Intra­molecular N—H⋯O hydrogen bonds are observed

Effect of a combination of Tuina therapy and budesonide inhalation on asthma in children, and its influence on lung function and pro inflammatory f actors

Purpose: To determine the effect of a combination of Tuina therapy and budesonide inhalation on pediatric asthma, and its influence on lung function and levels of inflammatory factors. Methods: Eligible 100 asthmatic children admitted to Provincial Maternity and Child-care Hospital, Lanzhou, Gansu Province, from January 2019 to January 2021 were randomized either to a control group or study group (1:1). The patients in control group were treated with budesonide inhalation, while the study group was given Tuina therapy in combination with budesonide inhalation. Treatment effectiveness, levels of inflammatory factors, immune functions and number of infections were evaluated in the patients. Results: The study group exhibited higher effectiveness profile versus the control group (96 vs 82 %; p < 0.05). After treatment, decreases were observed in the frequency of asthmatic attacks and number of respiratory infections in the two groups, with lower results in the study group than in the control group (p < 0.05). There were marked decreases in the levels of IgG, TNF-α and IL-8 in both groups, with the study group showing higher reductions (p < 0.05). Conclusion: Combined treatment with Tuina and budesonide inhalation decreases the levels of inflammatory factors, regulates immune function, and improves lung function of asthmatic children. Further investigation in a larger population would be required to establish the mechanism and clinical value of this therapy

3D Semantic Subspace Traverser: Empowering 3D Generative Model with Shape Editing Capability

Shape generation is the practice of producing 3D shapes as various representations for 3D content creation. Previous studies on 3D shape generation have focused on shape quality and structure, without or less considering the importance of semantic information. Consequently, such generative models often fail to preserve the semantic consistency of shape structure or enable manipulation of the semantic attributes of shapes during generation. In this paper, we proposed a novel semantic generative model named 3D Semantic Subspace Traverser that utilizes semantic attributes for category-specific 3D shape generation and editing. Our method utilizes implicit functions as the 3D shape representation and combines a novel latent-space GAN with a linear subspace model to discover semantic dimensions in the local latent space of 3D shapes. Each dimension of the subspace corresponds to a particular semantic attribute, and we can edit the attributes of generated shapes by traversing the coefficients of those dimensions. Experimental results demonstrate that our method can produce plausible shapes with complex structures and enable the editing of semantic attributes. The code and trained models are available at https://github.com/TrepangCat/3D_Semantic_Subspace_TraverserComment: Published in ICCV 2023. Code: https://github.com/TrepangCat/3D_Semantic_Subspace_Traverse