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Background The detection of food quality and safety is important in the whole food supply chain. In recent years, fluorescent detection technology has been extensively applied in food analysis. In particular, nanomaterial-based “on-off-on” fluorescent sensors have received much attention because of their high sensitivity, wide detection range, strong anti-interference ability, and flexible design. Nevertheless, there is no review focusing on the “on-off-on” fluorescent sensors for food analysis. Scope and approach In the current review, several common nanomaterials are introduced, including quantum dots (QDs), carbon dots (CDs), graphene quantum dots (GQDs), and metal nanoclusters (MNCs). Main detection strategies of “on-off-on” fluorescent sensors are elaborated, involving redox reaction, competitive reaction, DNA hybridization reaction and enzymatic reaction. In addition, recent applications of “on-off-on” fluorescent sensors for trace level detection of nutrients, food additives, drug residues, pesticide residues, foodborne pathogenic bacterias, mycotoxins, and heavy metal ions are also summarized. Finally, advantages, challenges and future prospects for developing the “on-off-on” fluorescent sensors are presented. Key findings and conclusions The “on-off-on” fluorescent sensors exhibit a wide detection range, strong anti-interference ability, and excellent linear responses to various analytes. However, current detection applications are still at the laboratory stage, commercial and industrial applications are rarely reported. Future research should focus on developing high-throughput detection techniques, and portable or visual fluorescent sensors, including kits and filter papers based sensors. Apps on smartphones should also be developed in future work.

Streptomyces scabies is the best-characterized plant-pathogenic streptomycete, which is a special species among the large genus Streptomyces. The pathogenicity of S. scabies relies on the production of the secondary metabolite thaxtomin A. Little is known about the molecular mechanisms underlying the regulation of thaxtomin biosynthesis in S. scabies beyond the pathway-specific activator TxtR and the cellulose utilization repressor CebR. The leucine-responsive regulatory protein (Lrp) family modulates secondary metabolism in nonpathogenic streptomycetes. However, the regulatory relationship between the Lrp and pathogenic streptomycetes remains unknown. In this study, we demonstrated that SCAB_Lrp (SCAB_77931) from S. scabies significantly affects thaxtomin biosynthesis, pathogenicity, and morphological development. SCAB_Lrp deletion resulted in a dramatic decline in thaxtomin A production and a low-virulence phenotype of S. scabies. An in-depth dissection of the regulatory mechanism of SCAB_Lrp revealed that it positively regulates the transcription of the thaxtomin biosynthetic gene cluster by directly binding to the promoter of the cluster-situated regulator gene txtR. SCAB_Lrp also controls the morphological development of S. scabies by directly activating the transcription of amfC, whiB, and ssgB. SCAB_Lrp directly controls the transcription of its own gene by binding a specific sequence (5'-GGACAGTCGCCGTGCTACG-3'). Moreover, phenylalanine and methionine have been characterized as SCAB_Lrp effectors by strengthening the binding affinity and complex status between SCAB_Lrp and DNA. Our findings characterize a multifunctional regulatory protein, SCAB_Lrp, that controls secondary metabolism, pathogenicity, and sporulation in S. scabies and provide new insights into the complex regulatory network that modulates thaxtomin phytotoxins in pathogenic Streptomyces.

New kinds of dispersion elements are required for the minimization of the spectrometers. Metasurfaces offer new methods for a novel type of spectrometers due to their ultra-thin property and great ability to manipulate the electromagnetic field. Here, we propose and demonstrate a spectral modulated metasurface as a miniaturized dispersion element that possesses parabolic phase profile. Different wavelengths of the incident light can be dispersed to different spatial positions due to the accumulation of the dynamic phase varies with the wavelengths from metasurface. Detailed theoretical spectrum dispersion ability is analyzed and experimental demonstration is achieved. The polarization conversion efficiency is high, which is promising to be used in practical applications. Such metasurface provides a new and simple way to design dispersion devices and has the potential to be used in spectrometers, variable filters, spectrum tomography, etc.

Food aflatoxin B1 (AFB1) contamination greatly threatens human health and its sensitive determination is imperative. In this study, a surface-enhanced Raman scattering (SERS) and fluorescence dual-signal aptasensor was constructed for sensitive AFB1 detection in peanuts, walnuts, and almonds samples. Fluorescent dye cy5 was used as fluorophore and Raman reporter, while polyethyleneimine modified Ag coating magnetic nanoparticles (MNP@Ag-PEI) were utilized to absorb the cy5 modified aptamer (apt-cy5). Results indicated that linear ranges of 0.001-1000 ng/mL and 0.2-20,000 ng/mL with detection limits of 0.45 pg/mL and 0.135 ng/mL for the SERS and fluorescence methods were obtained, respectively, and AFB1 detection in the nut samples using the aptasensor achieved satisfactory recoveries of 95.2%-108.6% for SERS and 94.7%-109.7% for fluorescence. Compared with other mono signal detection, the established aptasensor facilely fused the merits of the two signals and improved the detection accuracy and flexibility.

Batteries are important for promoting renewable energy, but, like most engineered products, they contain multiple hazardous materials. The purpose of this study is to evaluate industrial-scale batteries using GreenScreen® for Safer Chemicals, an established chemical hazard assessment (CHA) framework, and to develop a systematic, transparent methodology to quantify the CHA results, harmonize them, and aggregate them into single-value hazard scores, which can facilitate quantitative comparison and a robust evaluation of data gaps, inconsistencies, and uncertainty through the implementation of carefully selected scenarios and stochastic multicriteria acceptability analysis (SMAA). Using multiple authoritative toxicity data sources, six battery products are evaluated: three lithium-ion batteries (lithium iron phosphate, lithium nickel cobalt manganese hydroxide, and lithium manganese oxide), and three redox flow batteries (vanadium redox, zinc-bromine, and all-iron). The CHA results indicate that many materials in these batteries, including reagents and intermediates, inherently exhibit high hazard; therefore, safer materials should be identified and considered in future designs. The scenario analysis and SMAA, combined, provide a quantitative evaluation framework to support the decision-making needed to compare alternative technologies. Thus, this study highlights specific strategies to reduce the use of hazardous materials in complex engineered products before they are widely used in this rapidly-expanding industry sector.

Author(s): Tian, S; He, H; Kendall, A; Davis, SJ; Ogunseitan, OA; Schoenung, JM; Samuelsen, S; Tarroja, B | Abstract: Energy storage systems are critical for enabling the environmental benefits associated with capturing renewable energy to displace fossil fuel-based generation, yet producing these systems also contributes to environmental impacts through their materials use and manufacturing. As energy storage capacity is scaled up to support increasingly renewable grids, the environmental benefits from their use may scale at different rates than the environmental impacts from their production. This implies the existence of capacity thresholds beyond which installing additional storage capacity may be environmentally detrimental. Identifying such thresholds are important for ensuring that energy storage capacity selection in future grids are consistent with net emissions reduction goals, but such thresholds have not been studied in the present literature. To identify such thresholds, here we combine electric grid dispatch modeling with life cycle analysis to compare how the emissions reductions from deploying three different flow battery energy storage types on a future California grid (g80% wind and solar) compare with emissions contributions from producing such batteries as total battery capacity installed on the grid increases. Depending on the type of battery and environmental impact indicator (greenhouse gas or particulate matter emissions), we find that the marginal environmental benefits of storage begin to diminish at deployed capacities of 38–76% of the mean daily renewable generation (256–512 GWh in our California scenarios) and reach zero at 105–284% of mean daily renewable generation (700–1810 GWh). Such storage capacities are conceivable, but upstream impacts of storage must be assessed in evaluating the environmental benefits of large-scale storage deployment, or they could negate the environmental benefits of regional electricity system decarbonization.

Distributed camera network for human pose estimation can solve the problem of limited view and occlusion of single view, which has great potential for wide area surveillance applications. To fuse different field of view information, we propose a distributed human pose estimation method by combining the interactive multiple model (IMM) algorithm with the distributed information fusion of human skeleton joints. Compared with the state-of-the-art works which often use a single motion model to depict the motion of human skeleton joints, e.g., constant velocity, the novelty of our work is that the maneuvering property of human action is handled by the IMM, i.e., the motion model of human skeleton joints in the filter is approximated using constant velocity, constant acceleration, and Singer motion models. Based on the advantages of IMM algorithm for maneuvering target tracking, our method can not only solve the single-view occlusion problem, but also solve the problem of joint point fluctuation caused by the estimation error of each sensor node after distributed information fusion. The final human action recognition experimental results show that the proposed method can improve the action recognition rate on the datasets captured by Kinect V2. In addition, we built a distributed camera network using embedded machine learning boards, such that deep learning-based human pose estimation methods can be employed in our framework to handle the limitations of original Kinect SDK.

Chemical hazard assessment (CHA), which aims to investigate the inherent hazard potential of chemicals, has been developed with the purpose of promoting safer consumer products. Despite the increasing use of CHA in recent years, finding adequate and reliable toxicity data required for CHA is still challenging due to issues regarding data completeness and data quality. Also, collecting data from primary toxicity reports or literature can be time consuming, which promotes the use of secondary data sources instead. In this study, we evaluate and characterize numerous secondary data sources on the basis of 5 performance attributes: reliability, adequacy, transparency, volume, and ease of use. We use GreenScreen for Safer Chemicals v1.4 as the CHA framework, which defines the endpoints of interest used in this analysis. We focused upon 34 data sources that reflect 3 types of secondary data: chemical-oriented data sources, hazard-trait-oriented data sources, and predictive data sources. To integrate and analyze the evaluation results, we applied 2 multicriteria decision analysis (MCDA) methodologies: multiattribute utility theory (MAUT) and stochastic multiobjective acceptability analysis (SMAA). Overall, the findings in this research program allow us to explore the relative importance of performance criteria and the data source quality for effectively conducting CHA. Integr Environ Assess Manag 2019;00:1-14. © 2019 SETAC.

System interchanges have played an important role in traffic flow transference in Chinese freeway network. With the increase of traffic volume, crashes and congestions intensively occur in early built system interchange. How to evaluate the safety level and take effective countermeasures to promote the operating safety of system interchange will be a long-term and tough task in the next decades. This paper analyzes the geometric components of a system interchange and classifies the typical schemes widely built in China into eight forms. Based on driving behavior analysis, the safety influencing segment of interchange (SISI) is defined as the mainline segment affected by the deployment of interchange, causing the variations of traffic flow characteristic and driving behavior. Based on driver’s behavior of mainline and ramp, the geometric organizations of traffic flow are classified into seven types and the safety level of all types is further analyzed. Results are the theoretical foundation and important support for future study on safety evaluation, deployment of traffic signs and markings, safety management in system interchange. Countermeasures that have been taken into practical safety engineering in China is summarized from the aspects of geometric component, behavior management and visibility promotion.

Energy storage systems, such as flow batteries, are essential for integrating variable renewable energy sources into the electricity grid. While a primary goal of increased renewable energy use on the grid is to mitigate environmental impact, the production of enabling technologies like energy storage systems causes environmental impact. Thus, understanding the impact of producing energy storage systems is crucial for determining the overall environmental performance of renewable energy from a systems perspective. In this study, the environmental impact associated with the production of emerging flow battery technologies is evaluated in an effort to inform materials selection and component design decisions. The production of three commercially available flow battery technologies is evaluated and compared on the basis of eight environmental impact categories, using primary data collected from battery manufacturers on the battery production phase including raw materials extraction, materials processing, manufacturing and assembly. In the baseline scenario, production of all-iron flow batteries led to the lowest impact scores in six of the eight impact categories such as global warming potential, 73 kg CO2 eq/kWh; and cumulative energy demand, 1090 MJ/kWh. While the production of vanadium redox flow batteries led to the highest impact values for six categories including global warming potential, 184 kg CO2 eq/kWh; and cumulative energy demand, 5200 MJ/kWh. Production of zinc-bromine flow batteries had the lowest values for ozone depletion, and freshwater ecotoxicity, and the highest value for abiotic resource depletion. The analysis highlight that the relative environmental impact of producing the three flow battery technologies varies with different system designs and materials selection choices. For example, harmonization of the battery system boundary led to freshwater eutrophication and freshwater ecotoxicity values for vanadium redox flow batteries lower than the values for zinc-bromine flow batteries. Regarding alternative material use strategies, we conclude that vanadium redox flow batteries exhibit the lowest potential in four of the eight impact categories including global warming potential at 61 kg CO2 eq/kWh. In zinc-bromine flow batteries, the titanium-based bipolar plate contributes higher environmental impact compared to carbon-based materials, and the polymer resins used in all-iron flow batteries could be replaced with material with lower potential for ecotoxicity. Overall, the analysis reveals the sources of potential environmental impact, due to the production of flow battery materials, components and systems. The findings from this study are urgently needed before these batteries become widely deployed in the renewable energy sector. Furthermore, our results indicate that materials options change the relative environmental impact of producing the three flow batteries and provide the potential to significantly reduce the environmental impact associated with flow battery production and deployment.

With the development of robot technology and the arrival of industry 4.0 era, society pays more attention to col- laboration and interaction between human and robots. However, safety is still main concern in the development of human-robot collaboration. In this paper, a novel real-time collision avoidance approach for mobile manipulator is proposed by considering the motion status of the human, which includes the relative minimum distance and velocity (both magnitude and direction) between the robot and the human. The distance and velocity of the human hand are first estimated online using a vision sensor, and then defined as danger factors in the potential function of the potential field. The novel potential function proposed in this paper considers not only the safety problem, but also the efficient problem, i.e., the manipulator can make smart control decision to avoid the collision according to the relative velocity in case of the cross over. To overcome the local minimum problem and choose a best motion direction, we propose a motion sampling mechanism for motion planning. For each sample, the robot calculates the potential function to evaluate the safety and efficiency, and chooses a direction which is best for avoidance. We finally demonstrate our idea on a real mobile manipulator platform in a simulated co-worker environment.

Amphibians have developed successful defensive strategies for combating predators and invasive microorganisms encountered in their broad range of environments, which involve secretion of complex cocktails of noxious, toxic and diverse bioactive molecules from the skins. In recent years, amphibian skin secretions have been considered as an extraordinary warehouse for the discovery of therapeutic medicines. In this study, through bioactivity screening of the Hylarana latouchii skin secretion-derived fractions, a novel peptide belonging to ranatensin subfamily (ranatensin-HLa) was discovered, and structurally and pharmacologically-characterised. It consists of 15 amino acid residues, pGlu-NGDRAPQWAVGHFM-NH2, and its synthetic replicate was found to exhibit pharmacological activities on increasing the contraction of the in vitro rat bladder and uterus smooth muscles. Corresponding characteristic sigmoidal dose-response curves with EC50 values of 7.1 nM and 5.5 nM were produced, respectively, in bladder and uterus. Moreover, the precursor of ranatensin-HLa showed a high degree of similarity to those of bombesin-like peptides from Odorrana grahami and Odorrana schmackeri. Hylarana latouchii skin continues to serve as a storehouse with diverse lead compounds for the development of therapeutically effective medicines.

Chemical hazard assessment (CHA), designed to evaluate the inherent hazard of chemicals used in everyday consumer products, is gaining in popularity and rigor. Although CHA is being more commonly used by industry and government organizations, there is limited information in the academic literature on the merits and limitations of CHA methods. In the current study, the significance of the need to use multiple data sources to successfully complete a CHA is explored. Specifically, a case study approach is used in which more than one hundred organic substances used in the synthesis of organic solar cells are evaluated using the GreenScreen® for Safer Chemicals framework as the basis for the CHA. Seven data sources, including three chemical-oriented, two hazard-trait-oriented, and two predictive data sources, are utilized to minimize data gaps and allow for complete assessments for most of the chemicals of interest. Findings from sensitivity analysis using single data sources and combinations of data sources highlight that the CHA outcomes can vary considerably as a function of data sources used, which highlights the importance of identifying and/or creating more comprehensive and standardized data sources.