Many important aspects of nanosilver behavior are influenced by the ionic activity associated with the particle suspension, including antibacterial potency, eukaryotic toxicity, environmental ...release, and particle persistence.The present study synthesizes pure, ion-free, citrate-stabilized nanosilver (nAg) colloids as model systems, and measures their time-dependent release of dissolved silver using centrifugal ultrafiltration and atomic absorption spectroscopy. Ion release is shown to be a cooperative oxidation process requiring both dissolved dioxygen and protons. It produces peroxide intermediates, and proceeds to complete reactive dissolution under some conditions. Ion release rates increase with temperature in the range 0-37 °C, and decrease with increasing pH or addition of humic or fulvic acids. Sea salts have only a minor effect on dissolved silver release. Silver nanoparticle surfaces can adsorb Ag(+), so even simple colloids contain three forms of silver: Ag(0) solids, free Ag(+) or its complexes, and surface-adsorbed Ag(+). Both thermodynamic analysis and kinetic measurements indicate that Ag(0) nanoparticles will not be persistent in realistic environmental compartments containing dissolved oxygen. An empirical kinetic law is proposed that reproduces the observed effects of dissolution time, pH, humic/fulvic acid content, and temperature observed here in the low range of nanosilver concentration most relevant for the environment.
Motor imagery (MI) electroencephalography (EEG) decoding plays an important role in brain-computer interface (BCI), which enables motor-disabled patients to communicate with the outside world via ...external devices. Recent deep learning methods, which fail to fully explore both deep-temporal characterizations in EEGs itself and multi-spectral information in different rhythms, generally ignore the temporal or spectral dependencies in MI-EEG. Also, the lack of effective feature fusion probably leads to redundant or irrelative information and thus fails to achieve the most discriminative features, resulting in the limited MI-EEG decoding performance. To address these issues, in this paper, a MI-EEG decoding framework is proposed, which uses a novel temporal-spectral-based squeeze-and-excitation feature fusion network (TS-SEFFNet). First, the deep-temporal convolution block (DT-Conv block) implements convolutions in a cascade architecture, which extracts high-dimension temporal representations from raw EEG signals. Second, the multi-spectral convolution block (MS-Conv block) is then conducted in parallel using multi-level wavelet convolutions to capture discriminative spectral features from corresponding clinical subbands. Finally, the proposed squeeze-and-excitation feature fusion block (SE-Feature-Fusion block) maps the deep-temporal and multi-spectral features into comprehensive fused feature maps, which highlights channel-wise feature responses by constructing interdependencies among different domain features. Competitive experimental results on two public datasets demonstrate that our method is able to achieve promising decoding performance compared with the state-of-the-art methods.
During the novel coronavirus pandemic, many people stopped going to the gym, and lack of exercise is likely to cause physical and mental health problems such as decreased immunity, in turn making ...them vulnerable to infection. Fitness apps can help people exercise at home by providing online professional guidance and supervision. This study explored the factors influencing fitness the intention to use apps during the epidemic in China. A new variable named epidemic crisis risk perception was added to the Unified Theory of Acceptance and Use of Technology model to reflect the impact of the epidemic. Performance expectation has the greatest impact on the willingness to use fitness apps. Therefore, developers must pay close attention to the needs of the public and improve the functions of apps to improve their satisfaction. In addition, the risk perception of epidemic crisis positively correlates with the willingness to use such apps, indicating that the novel coronavirus pandemic indeed affected public psychology and behavioural intention.
•A fuzzy logic controller is designed to save lighting energy consumption.•Experiment and simulation results verify the effectiveness of the controller.•The smart LED lighting system can regulate ...lighting output automatically.•Users can choose their illumination levels according to various lighting preferences.
In commercial buildings, lighting constitutes a large proportion of energy consumption. Saving lighting energy in commercial buildings has aroused great interest among researchers. Achieving energy savings and satisfying lighting comfort are the two primary objectives in designing a lighting system. In this paper, a fuzzy logic controller was designed that considered daylight, movement information and lighting comfort. The DALI protocol was used to communicate the controller with LED luminaires. The simulation results demonstrate that lighting system without control can provide sufficient illumination. The lighting system provides wider controllability to make lighting environment operating at the most energy-saving state. The experimental results show that by using the designed controller, significant lighting energy can be saved. The office where the smart LED lighting system is installed can regulate lighting output automatically based on users’ movements and allow users to choose their own lighting preferences.
Major pathways in the antibacterial activity and eukaryotic toxicity of nanosilver involve the silver cation and its soluble complexes, which are well established thiol toxicants. Through these ...pathways, nanosilver behaves in analogy to a drug delivery system, in which the particle contains a concentrated inventory of an active species, the ion, which is transported to and released near biological target sites. Although the importance of silver ion in the biological response to nanosilver is widely recognized, the drug delivery paradigm has not been well developed for this system, and there is significant potential to improve nanosilver technologies through controlled release formulations. This article applies elements of the drug delivery paradigm to nanosilver dissolution and presents a systematic study of chemical concepts for controlled release. After presenting thermodynamic calculations of silver species partitioning in biological media, the rates of oxidative silver dissolution are measured for nanoparticles and macroscopic foils and used to derive unified area-based release kinetics. A variety of competing chemical approaches are demonstrated for controlling the ion release rate over 4 orders of magnitude. Release can be systematically slowed by thiol and citrate ligand binding, formation of sulfidic coatings, or the scavenging of peroxy-intermediates. Release can be accelerated by preoxidation or particle size reduction, while polymer coatings with complexation sites alter the release profile by storing and releasing inventories of surface-bound silver. Finally, the ability to tune biological activity is demonstrated through a bacterial inhibition zone assay carried out on selected formulations of controlled release nanosilver.
With the advent of the "Internet plus" era, the Internet of Things (IoT) is gradually penetrating into various fields, and the scale of its equipment is also showing an explosive growth trend. The ...age of the "Internet of Everything" is coming. The integration and diversification of IoT terminals and applications make IoT more vulnerable to various intrusion attacks. Therefore, it is particularly important to design an intrusion detection model that guarantees the security, integrity and reliability of the IoT. Traditional intrusion detection technology has the disadvantages of low detection rate and poor scalability, which cannot adapt to the complex and changeable IoT environment. In this paper, we propose a particle swarm optimization-based gradient descent (PSO-LightGBM) for the intrusion detection. In this method, PSO-LightGBM is used to extract the features of the data and inputs it into one-class SVM (OCSVM) to discover and identify malicious data. The UNSW-NB15 dataset is applied to verify the intrusion detection model. The experimental results show that the model we propose is very robust in detecting either normal or various malicious data, especially small sample data such as Backdoor, Shellcode and Worms.
Independent component analysis (ICA) has become an increasingly utilized approach for analyzing brain imaging data. In contrast to the widely used general linear model (GLM) that requires the user to ...parameterize the data (e.g. the brain’s response to stimuli), ICA, by relying upon a general assumption of independence, allows the user to be agnostic regarding the exact form of the response. In addition, ICA is intrinsically a multivariate approach, and hence each component provides a grouping of brain activity into regions that share the same response pattern thus providing a natural measure of functional connectivity. There are a wide variety of ICA approaches that have been proposed, in this paper we focus upon two distinct methods. The first part of this paper reviews the use of ICA for making group inferences from fMRI data. We provide an overview of current approaches for utilizing ICA to make group inferences with a focus upon the group ICA approach implemented in the GIFT software. In the next part of this paper, we provide an overview of the use of ICA to combine or fuse multimodal data. ICA has proven particularly useful for data fusion of multiple tasks or data modalities such as single nucleotide polymorphism (SNP) data or event-related potentials. As demonstrated by a number of examples in this paper, ICA is a powerful and versatile data-driven approach for studying the brain.
In order to promote China's biogas industry development, this paper comprehensively compared the biogas status and related policies between China and Europe and tried to find the shortage and ...potential implications. China has access to abundant biomass resources, with considerable biogas potential and an annual theoretical output of 73.6 billion m3. Household-based biogas digesters coexist with medium and large-scale biogas plants (MLBPs) in China. Although the number of MLBPs in China was almost two times higher than Europe, the annul biogas production yield was only half of those in Europe. In China, biogas is mainly used for heating and cooking, and its power generation capacity is far lower than that in Europe. Overall, biogas industry is more commercialized in Europe than China. In terms of biogas related policies, China has an advantage in quantity, but is weak in their implementation. Biogas related policies in China mainly focus on agricultural and rural development, while in Europe, they are aimed at increasing the utilization of renewable energy and reducing greenhouse gas emissions. In addition, policies in China are mostly filled with encouragement, lacking detailed subsidy schemes and modes, whereas in European countries are more targeted and scientific. Based on the dissimilarity of current status and the disparity in policies, a series of countermeasures and suggestions for the development of the Chinese biogas industry are presented.
•China's biomass sources have lower utilization rate compared to Europe.•Biogas industry in Europe is more industrialized and commercialized than in China.•The related-biogas policy framework of Europe is more mature and perfect.•European biogas policy provide valuable reference for China's biogas development.•China's biogas industry has great potential for development.
The widespread use of silver nanoparticles (Ag-NPs) in consumer and medical products provides strong motivation for a careful assessment of their environmental and human health risks. Recent studies ...have shown that Ag-NPs released to the natural environment undergo profound chemical transformations that can affect silver bioavailability, toxicity, and risk. Less is known about Ag-NP chemical transformations in biological systems, though the medical literature clearly reports that chronic silver ingestion produces argyrial deposits consisting of silver-, sulfur-, and selenium-containing particulate phases. Here we show that Ag-NPs undergo a rich set of biochemical transformations, including accelerated oxidative dissolution in gastric acid, thiol binding and exchange, photoreduction of thiol- or protein-bound silver to secondary zerovalent Ag-NPs, and rapid reactions between silver surfaces and reduced selenium species. Selenide is also observed to rapidly exchange with sulfide in preformed Ag(2)S solid phases. The combined results allow us to propose a conceptual model for Ag-NP transformation pathways in the human body. In this model, argyrial silver deposits are not translocated engineered Ag-NPs, but rather secondary particles formed by partial dissolution in the GI tract followed by ion uptake, systemic circulation as organo-Ag complexes, and immobilization as zerovalent Ag-NPs by photoreduction in light-affected skin regions. The secondary Ag-NPs then undergo detoxifying transformations into sulfides and further into selenides or Se/S mixed phases through exchange reactions. The formation of secondary particles in biological environments implies that Ag-NPs are not only a product of industrial nanotechnology but also have long been present in the human body following exposure to more traditional chemical forms of silver.
Recent examples for nonbridged group 4 half-metallocenes containing anionic donor ligands of the type, Cp′MX
2(L), as catalysts for precise olefin polymerization have been reviewed. These catalysts ...displayed unique characteristics especially for ethylene copolymerizations, affording new polyolefins that can not be prepared by ordinary catalysts; ligand modifications are the key for precise olefin (co)polymerization.
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Recent examples for synthesis of group 4 transition metal (Ti, Zr, Hf) complexes, especially nonbridged half-metallocenes containing anionic donor ligands of the type, Cp′MX
2(L) (Cp′
=
cyclopentadienyl group; M
=
Ti, Zr, Hf; X
=
halogen, alkyl etc.; L
=
anionic donor ligands), as catalysts for precise olefin polymerization have been reviewed. It has been revealed that these complex catalysts displayed unique characteristics especially for ethylene copolymerizations and some examples are known to produce new polyolefins that cannot be prepared by ordinary catalysts such as classical Ziegler–Natta, metallocenes. Modification of both cyclopentadienyl fragment and anionic ancillary donor ligands are the key for precise olefin (co)polymerization.
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