EC-YOLO: Improved YOLOv7 Model for PCB Electronic Component Detection.

Electronic components are the main components of PCBs (printed circuit boards), so the detection and classification of ECs (electronic components) is an important aspect of recycling used PCBs. However, due to the variety and quantity of ECs, traditional target detection methods for EC classification still have problems such as slow detection speed and low performance, and the accuracy of the detection needs to be improved. To overcome these limitations, this study proposes an enhanced YOLO (you only look once) network (EC-YOLOv7) for detecting EC targets. The network uses ACmix (a mixed model that enjoys the benefits of both self-attention and convolution) as a substitute for the 3 × 3 convolutional modules in the E-ELAN (Extended ELAN) architecture and implements branch links and 1 × 1 convolutional arrays between the ACmix modules to improve the speed of feature retrieval and network inference. Furthermore, the ResNet-ACmix module is engineered to prevent the leakage of function data and to minimise calculation time. Subsequently, the SPPCSPS (spatial pyramid pooling connected spatial pyramid convolution) block has been improved by replacing the serial channels with concurrent channels, which improves the fusion speed of the image features. To effectively capture spatial information and improve detection accuracy, the DyHead (the dynamic head) is utilised to enhance the model's size, mission, and sense of space, which effectively captures spatial information and improves the detection accuracy. A new bounding-box loss regression method, the WIoU-Soft-NMS method, is finally suggested to facilitate prediction regression and improve the localisation accuracy. The experimental results demonstrate that the enhanced YOLOv7 net surpasses the initial YOLOv7 model and other common EC detection methods. The proposed EC-YOLOv7 network reaches a mean accuracy (mAP@0.5) of 94.4% on the PCB dataset and exhibits higher FPS compared to the original YOLOv7 model. In conclusion, it can significantly enhance high-density EC target recognition.

Towards advanced removal of organics in persulfate solution by heterogeneous iron-based catalyst: A review.

Heterogeneous iron-based catalysts have drawn increasing attention in the advanced oxidation of persulfates due to their abundance in nature, the lack of secondary pollution to the environment, and their low cost over the last a few years. In this paper, the latest progress in the research on the activation of persulfate by heterogeneous iron-based catalysts is reviewed from two aspects, in terms of synthesized catalysts (Fe0, Fe2O3, Fe3O4, FeOOH) and natural iron ore catalysts (pyrite, magnetite, hematite, siderite, goethite, ferrohydrite, ilmenite and lepidocrocite) focusing on efforts made to improve the performance of catalysts. The advantages and disadvantages of the synthesized catalysts and natural iron ore were summarized. Particular interests were paid to the activation mechanisms in the catalyst/PS/pollutant system for removal of organic pollutants. Future research challenges in the context of field application were also discussed.

Red blood cell folate level is associated with periodontitis in American adults: results from the NHANES 2009-2014.

BACKGROUND: Red blood cell (RBC) folate is an indicator of long-term folate nutrition. Whether there is an association between RBC folate and periodontitis is unclear. This study aimed to use the NHANES database to determine whether RBC folate is associated with moderate/severe periodontitis. METHODS: A cross-sectional analysis of 10,151 participants in the NHANES database from 2009 to 2014 was performed. Multivariate logistic regression was used to analyze the independent relationship between RBC folate and moderate/severe periodontitis. The generalized additive model (GAM), restricted cubic splines (RCS), smooth curve fitting, and threshold effect analysis were used to explore the dose-response relationship and the potential nonlinear relationship between RBC folate and periodontitis. Finally, subgroup analysis and interaction tests were performed to determine the effect of covariates on the relationship between RBC folate and moderate/severe periodontitis. RESULTS: After adjusting for all confounders, there was a negative association between RBC folate concentration and moderate/severe periodontitis. The lowest fraction Q1 (< 360 ng/mL) of RBC folate concentration was used as the reference group, multivariable-adjusted ORs and 95% CIs of the second (360-463 ng/mL), third (464-569 ng/mL), fourth (570-732 ng/mL), and the highest quintile (> 733 ng/mL) categories were 0.88 (0.77, 1.01), 0.83 (0.72, 0.96), 0.77 (0.67, 0.90), 0.65 (0.56, 0.77) respectively. Additionally, a threshold nonlinear association was found between RBC folate (ng/mL) log2 transformation and moderate/severe periodontitis. CONCLUSION: This cross-sectional study revealed a negative relationship between RBC folate and moderate/severe periodontitis within a certain threshold range. Dentists and policymakers should pay closer attention to oral hygiene and health care for people with low or high RBC folate levels. Further causal and longitudinal research mechanisms are needed to validate our findings.

Mechanism of action of Coptidis Rhizome in treating periodontitis based on network pharmacology and in vitro validation.

OBJECTIVE: Explore the therapeutic mechanism of Coptidis Rhizome (CR) in periodontitis using network pharmacology, and validate it through molecular docking and in vitro experiments. METHODS: Screened potential active components and target genes of CR from TCMSP and Swiss databases. Identified periodontitis-related target genes using GeneCards. Found common target genes using Venny. Conducted GO and KEGG pathway analysis. Performed molecular docking and in vitro experiments using Berberine, the main active component of CR, on lymphocytes from healthy and periodontitis patients. Assessed effects on inflammatory factors using CCK-8, flow cytometry, and ELISA. RESULTS: Fourteen active components and 291 targets of CR were identified. 30 intersecting target genes with periodontitis were found. GO and KEGG analysis revealed oxidative stress response and IL-17 signaling pathway as key mechanisms. Molecular docking showed strong binding of Berberine with ALOX5, AKT1, NOS2, and TNF. In vitro experiments have demonstrated the ability of berberine to inhibit the expression of Th17 + and other immune related cells in LPS stimulated lymphocytes, and reduce the secretion of IL-6, IL-8, and IL-17. CONCLUSION: CR treats periodontitis through a multi-component, multi-target, and multi-pathway approach. Berberine, its key component, acts through the IL-17 signaling pathway to exert anti-inflammatory effects.

The associations of two novel inflammation indexes, systemic immune-inflammation index (SII) and system inflammation response index (SIRI), with periodontitis: evidence from NHANES 2009-2014.

OBJECTIVES: The research's goal is to look for any potential relationships between the systemic immune-inflammation index (SII) and the system inflammation response index (SIRI), along with inflammation indicators and the likelihood of periodontitis. METHODS: Ten thousand two hundred eighty-two individuals in sum were determined to be eligible for this cross-sectional study from the National Health and Nutrition Examination Survey (NHANES) between 2009 and 2014. Multiple logistic regression, generalized additive model, smooth curve fitting, subgroup analysis, and interaction tests were done for analyzing the association between periodontitis and SII, SIRI, and other inflammatory indicators. RESULTS: The analysis, adjusted for population weighting, revealed that individuals with moderate/severe periodontitis had SII levels of 545.46 (95% CI (529.10, 561.82), P = 0.0044) and SIRI levels of 1.33 (95% CI (1.29, 1.37), P < 0.0001). In a fully adjusted multivariate logistic regression model, SII was not sensibly associated with moderate/severe periodontitis among the continuous and quartile Q1-Q4 groups (OR = 0.97, 95% CI (0.91, 1.02)). The continuous variable of SIRI (OR = 1.11, 95% CI (1.06, 1.17)) and the quartile Q4 group (OR = 1.58, 95% CI (1.28, 1.94)) had a deemed significant positive association with moderate to severe periodontitis. In addition, other inflammatory indicators, especially NLR, PPN, PLR, MLR, PC, NC, and MC were observed to be notably involved moderate/severe periodontist in this research. CONCLUSION: We explored the association between periodontitis and two novel comprehensive markers of inflammation (SII and SIRI). CLINICAL RELEVANCE: These inflammatory markers are expected to serve as tools to assist clinicians in diagnosing periodontitis.

Regulation of heterogeneous electron transfer reactivity by defect engineering through electrochemically induced brominating addition.

Enhancing the electrochemical activity of graphene holds great significance for expanding its applications in various electrochemistry fields. In this study, we have demonstrated a facile and quantitative approach for modulating the defect density of single-layer graphene (SLG) via an electrochemically induced bromination process facilitated by cyclic voltammetry. This controlled defect engineering directly impacts the heterogeneous electron transfer (HET) rate of SLG. By utilizing Raman spectroscopy and scanning electrochemical microscopy (SECM), we have established a correlation between the HET kinetics and both the defect density (nD) and mean distance between defects (LD) of SLG. The variation of the HET rate (k0) with the defect density manifested a distinctive three-stage behavior. Initially, k0 increased slightly with the increasing nD, and then it experienced a rapid increase as nD further increased. However, once the defect density surpassed a critical value of about 1.8 × 1012 cm-2 (LD < 4.2 nm), k0 decreased rapidly. Notably, the results revealed a remarkable 35-fold enhancement of k0 under the optimal defect density conditions compared to pristine SLG. This research paves the way for controllable defect engineering as a powerful strategy to enhance the electrochemical activity of graphene, opening up new possibilities for its utilization in a wide range of electrochemical applications.

The associations of early specialization, sports volume, and maturity status with musculoskeletal injury in elite youth football players.

Background: Youth football in schools has experienced rapid growth in China. Despite the increase of players engaging in more frequent, intensive, and organized sports training at their early ages, the controversy over early specialization (ES) still exists. This study aims to: a) investigate the training situation of players in the Chinese School Football Programme and b) examine the associations of early specialization, sports volume, and maturity status with musculoskeletal injury. Methods: A cross-sectional survey was used. Players who participated in the National School Football Winter Camp were invited to fill out a questionnaire that included the data of maturity, ES, sports volume, and injury history (n = 88 boys and n = 90 girls). Results: The results have shown that 80.3% of the athletes were classified as ES, while 19.7% of them were classified as non-ES. Almost all athletes (96%) participated in a sport for more than 8 months in a year. Most athletes (75.8%) spent more than twice of the time on organized sports than leisure activities. 30.3% of the athletes trained on average more hours per week than the number of their ages. Binomial logistic regression models reflected the significant differences in the odds ratios (OR) of reporting a history of injury among athletes with different levels of specialization (p = 0.024) and the OR of reporting a history of leg injury among players with different weekly sports volumes (p = 0.038). Significant differences were also shown in the OR of players reporting foot injuries between players with different maturity states (p = 0.046), and the Chi-squared test showed significant differences in the OR of reporting acute injuries between players with different levels of specialization (p = 0.048) and weekly activity (p = 0.022). No significant differences were found between the remaining variables. Conclusion: Most school football elite players follow the ES pathway even though ES increases the risk of injury, especially acute injury. Pre-pubertal and early pubertal players have a higher incidence of foot injuries. Players who train more hours per week than their ages have more leg injuries and acute injuries. Therefore, priority protection and intervention should be carried out for populations with a high risk of injury.

The Emerging Biological Functions of Exosomes from Dental Tissue-Derived Mesenchymal Stem Cells.

Exosomes are one kind of small-cell extracellular membranous vesicles that can regulate intercellular communication and give rise to mediating the biological behaviors of cells, involving in tissue formation, repair, the modulation of inflammation, and nerve regeneration. The abundant kinds of cells can secret exosomes, among them, mesenchymal stem cells (MSCs) are very perfect cells for mass production of exosomes. Dental tissue-derived mesenchymal stem cells (DT-MSCs), including dental pulp stem cells, stem cells from exfoliated deciduous teeth, stem cells from apical papilla, stem cells from human periodontal ligament (PDLSCs), gingiva-derived mesenchymal stem cells, dental follicle stem cells, tooth germ stem cells, and alveolar bone-derived mesenchymal stem cells, are now known as a potent tool in the area of cell regeneration and therapy, more importantly, DT-MSCs can also release numerous types of exosomes, participating in the biological functions of cells. Hence, we briefly depict the characteristics of exosomes, give a detailed description of the biological functions and clinical application in some respects of exosomes from DT-MSCs through systematically reviewing the latest evidence, and provide a rationale for their use as tools for potential application in tissue engineering.

Autonomous Binarized Focal Loss Enhanced Model Compression Design Using Tensor Train Decomposition.

Deep learning methods have exhibited the great capacity to process object detection tasks, offering a practical and viable approach in many applications. When researchers have advanced deep learning models to improve their performance, the model derived from the algorithmic improvement may itself require complementary increases in computational and power demands. Recently, model compression and pruning techniques have received more attention to promote the wide employment of the DNN model. Although these techniques have achieved a remarkable performance, the class imbalance issue during the mode compression process does not vanish. This paper exploits the Autonomous Binarized Focal Loss Enhanced Model Compression (ABFLMC) model to address the issue. Additionally, our proposed ABFLMC can automatically receive the dynamic difficulty term during the training process to improve performance and reduce complexity. A novel hardware architecture is proposed to accelerate inference. Our experimental results show that the ABFLMC can achieve higher accuracy, faster speed, and smaller model size.

Biomass enhances the reduction of oxidized pellets with carbon monoxide.

In this study, the reduction mechanism of using CO to reduce biomass-oxidized pellets (BOP) and general-oxidized pellets (GOP) was deeply analyzed. The effect of biomass addition on the reduction of oxidized pellets and the change of reduction kinetics were studied. The addition of 2 wt% biomass into pellets increases pores of the oxidized pellets, promotes the rate of CO entering the pellets and the overflow of CO2, which results in faster reduction of the oxidized pellets. The reduction reactions of BOP and GOP were controlled by internal diffusion, mixing control and interface control sequentially. Also, addition of the biomass to the pellets decreases the activation energy required for their reduction, from 87.30 to 80.65 kJ·mol-1. The addition of biomass shortens the reduction time by 3% which can reduce the energy consumption. Therefore, the biomass together with CO enhances the reduction of oxidized pellets and has real environmental benefits.

Rapid and Quantitative Detection of Aflatoxin B1 in Grain by Portable Raman Spectrometer.

Many foodstuffs are extremely susceptible to contamination with aflatoxins, in which aflatoxin B1 is highly toxic and carcinogenic. Therefore, it is crucial to develop a rapid and effective analytical method for detecting and monitoring aflatoxin B1 in food. Herein, a surface-enhanced Raman spectroscopic (SERS) method combined with QuEChERS (quick, easy, cheap-effective, rugged, safe) sample pretreatment technique was used to detect aflatoxin B1. Sample preparation was optimized into a one-step extraction method using an Au nanoparticle-based solution (Au sol) as the SERS detection substrate. An affordable portable Raman spectrometer was then used for rapid, label-free, quantitative detection of aflatoxin B1 levels in foodstuffs. This method showed a good linear log relationship between the Raman signal intensity of aflatoxin B1 in the 1-1000 µg L-1 concentration range with a limit of detection of 0.85 µg kg-1 and a correlation coefficient of 0.9836. Rapid aflatoxin B1 detection times of ∼10 min for wheat, corn, and protein feed powder samples were also achieved. This method has high sensitivity, strong specificity, excellent stability, is simple to use, economical, and is suitable for on-site detection, with good prospects for practical application in the field of food safety.

Catalytic pyrolysis of rain tree biomass with nano nickel oxide synthetized from nickel plating slag: A green path for treating waste by waste.

Catalytic pyrolysis of rain tree biomass (RTB), a typical horticultural waste, was investigated with nano-NiO as catalyst produced from hazardous nickel plating slag (NPS). It appeared from the analyses by FTIR, TGA, XRD, BET, and FESEM/EDX that nano-NiO produced had a SBET and mean particle size of 53.4 m2/g and 112.3 nm. The catalytic pyrolysis kinetics of RTB with and without catalyst were studied by Friedman method. It was found that the activation energy (Ea) was in the range of 177 to 360 kJ/mol at a conversion rate of 0.1 - 0.75. The results further revealed that the H2 increase ratio in pyrolysis above 500 °C was more than 40% in the presence of catalyst. Consequently, this study showed the great potential of nano-NiO as a high-efficiency catalyst in recovering energy from biomass.

Insight into the Ex Situ Catalytic Pyrolysis of Biomass over Char Supported Metals Catalyst: Syngas Production and Tar Decomposition.

Ex situ catalytic pyrolysis of biomass using char-supported nanoparticles metals (Fe and Ni) catalyst for syngas production and tar decomposition was investigated. The characterizations of fresh Fe-Ni/char catalysts were determined by TGA, SEM-EDS, Brunauer-Emmett-Teller (BET), and XPS. The results indicated that nanoparticles metal substances (Fe and Ni) successfully impregnated into the char support and increased the thermal stability of Fe-Ni/char. Fe-Ni/char catalyst exhibited relatively superior catalytic performance, where the syngas yield and the molar ratio of H2/CO were 0.91 Nm3/kg biomass and 1.64, respectively. Moreover, the lowest tar yield (43.21 g/kg biomass) and the highest tar catalytic conversion efficiency (84.97 wt.%) were also obtained under the condition of Ni/char. Ultimate analysis and GC-MS were employed to analyze the characterization of tar, and the results indicated that the percentage of aromatic hydrocarbons appreciably increased with the significantly decrease in oxygenated compounds and nitrogenous compounds, especially in Fe-Ni/char catalyst, when compared with no catalyst pyrolysis. After catalytic pyrolysis, XPS was employed to investigate the surface valence states of the characteristic elements in the catalysts. The results indicated that the metallic oxides (MexOy) were reduced to metallic Me0 as active sites for tar catalytic pyrolysis. The main reactions pathway involved during ex situ catalytic pyrolysis of biomass based on char-supported catalyst was proposed. These findings indicate that char has the potential to be used as an efficient and low-cost catalyst toward biomass pyrolysis for syngas production and tar decomposition.

Cation-exchange resin regeneration waste liquid as alternative NaCl source for enhancing anaerobic fermentation of waste activated sludge: Compositions of dissolved organic matters and chemical conditioning performance.

This study reported the NaCl-enhanced anaerobic fermentation with cation-exchange resin regeneration waste liquid (CRWL) as alternative NaCl source for waste activated sludge (WAS) disposal and carbon recovery. Through 4-day CRWL-enhanced anaerobic fermentation at Na+ concentration of 0.34 mol/L, the Na+-caused sludge disintegration triggered numerous release of dissolved organic matters (DOMs), i.e. 371.6 mg/g VSS, with composition distribution: acetic acid (28.2%) > butyric acid (16.1%) ≈ valeric acid (17.8%) ≈ proteins (16.4%) > propionic acid (14.4%) > unknown (3.2%) > carbohydrates (3.9%). Satisfying chemical conditioning performance for the fermented sludge was observed at the FeCl3 dosage of 0.3 g/g DS, attributing to the roles of double-layer compression and electric neutralization. The capillary suction time (CST) and sludge cake moisture content were decreased to 60.3 s and 75.1%, against those of 607 s and 93.5% before conditioning, respectively. Such "treating waste by waste" strategy could provide numerous environmental and economic benefits.

Batch preparation of gold nanoparticles with highly uniform morphology and tunable plasmonic properties.

The plasmonic properties of individual metallic nanostructures are of great importance for application in surface science, materials science, and nanophotonics. Herein, being facilitated with a home-made flow device and pulsed laser irradiation, we proposed a batch preparation protocol towards spherical Au nanoparticles (Au NPs) and cage shell entrapped spherical core nanoparticles (Au@cAu NPs) with highly uniform morphology and a tunable size distribution. The Fano resonance behavior exhibited by the effective interaction between spherical Au NPs and the silicon surface has great potential for the design of ultrasensitive optical sensing devices. In comparison with the spherical Au NP, the individual Au@cAu NP displayed not only a red-shifted and broadened localized surface plasmon resonance (LSPR) scattering peak, but also a higher electromagnetic field enhancement. Therefore, the Au@cAu NPs offer a better choice for plasmonic enhancement-based applications in the red and near-infrared region. In general, the current work provides a new and easy method for the large-scale preparation of gold-based uniform nanostructures, and offers an avenue to understand the interference of different plasmon modes in plasmonic systems, which has potential applications in surface science.

Shell-Isolated Nanoparticle-Enhanced Luminescence of Metallic Nanoclusters.

Metallic nanoclusters (NCs) have molecular-like structures and unique physical and chemical properties, making them an interesting new class of luminescent nanomaterials with various applications in chemical sensing, bioimaging, optoelectronics, light-emitting diodes (LEDs), etc. However, weak photoluminescence (PL) limits the practical applications of NCs. Herein, an effective and facile strategy of enhancing the PL of NCs was developed using Ag shell-isolated nanoparticle (Ag SHIN)-enhanced luminescence platforms with tuned SHINs shell thicknesses. 3D-FDTD theoretical calculations along with femtosecond transient absorption and fluorescence decay measurements were performed to elucidate the enhancement mechanisms. Maximum enhancements of up to 231-fold for the [Au7Ag8(C≡CtBu)12]+ cluster and 126-fold for DNA-templated Ag NCs (DNA-Ag NCs) were achieved. We evidenced a novel and versatile method of achieving large PL enhancements with NCs with potential for practical biosensing applications for identifying target DNA in ultrasensitive surface analysis.

Rapid and low-cost quantitative detection of creatinine in human urine with a portable Raman spectrometer.

The creatinine concentration of human urine is closely related to human kidney health and its rapid, quantitative, and low-cost detection has always been demanded. Herein, a surface-enhanced Raman spectroscopic (SERS) method for rapid and cost-effective quantification of creatinine concentrations in human urine was developed. A Au nanoparticle solution (Au sol) was used as a SERS substrate and the influence of different agglomerating salts on its sensitivity toward detecting creatinine concentrations was studied and optimized, as well as the effect of both the salt and Au sol concentrations. The variation in creatinine spectra over time on different substrates was also examined, demonstrating reproducible quantitative analysis of creatinine concentrations in solution. By adjusting the pH, a simple liquid-liquid solvent extraction procedure, which extracted creatinine from human urine, was used to increase the SERS detection selectivity toward creatinine in complex matrices. The quantitative results were compared to those obtained with a clinically validated enzymatic "creatinine kit (CK)." The limit of detection (LOD) for the SERS technique was 1.45 mg L-1, compared with 3.4 mg L-1 for the CK method. Furthermore, cross-comparing the results from the two methods, the average difference was 5.84% and the whole SERS detection process could be completed within 2 min compared with 11 min for the CK, indicating the practicality of the quantitative SERS technique. This novel quantitative technique shows promises as a high-throughput platform for relevant clinical and forensic analysis.

RGS4 Regulates Proliferation And Apoptosis Of NSCLC Cells Via microRNA-16 And Brain-Derived Neurotrophic Factor.

PURPOSE: Regulator of G-protein signaling (RGS) proteins are GTPase-activating proteins that target the α-subunit of heterotrimeric G proteins. Many studies have shown that RGS proteins contribute to tumorigenesis and metastasis. However, the mechanism in which RGS proteins, especially RGS4, affect the development of non-small cell lung cancer (NSCLC) remains unclear. The aim of this study was to characterize the role of RGS4 in NSCLC. METHODS: RGS4 expression in NSCLC tissues was assessed using an immunohistochemistry tissue microarray. Additionally, RGS4 was knocked down using short-hairpin RNA to assess the regulatory function of RGS4 in the biological behaviors of human NSCLC cell lines. A xenograft lung cancer model in nude BALB/c mice was established to study whether RGS4 knockdown inhibits cancer cell proliferation in vivo. RESULTS: We observed an increase in RGS4 protein levels in NSCLC samples. RGS4 knockdown inhibited cell proliferation and induced apoptosis in H1299 and PC9 cell lines, but did not affect cell migration. Moreover, we found that RGS4 negatively regulated the expression of microRNA-16 (miR-16), a tumor suppressor. The inhibition of miR-16 resulted in upregulated RGS4 expression. We also found that RGS4 regulated the expression of brain-derived neurotrophic factor (BDNF) and activated the BDNF-tropomyosin receptor kinase B signaling pathway. CONCLUSION: This study revealed that RGS4 overexpression positively correlated with the development of NSCLC. TDownstream RGS4 targets (eg, miR-16 and BDNF) might be involved in the development of NSCLC and may serve as potential therapeutic targets for its treatment.

Background-Free Quantitative Surface Enhanced Raman Spectroscopy Analysis Using Core-Shell Nanoparticles with an Inherent Internal Standard.

Surface enhanced Raman spectroscopy (SERS) is an ultrasensitive label-free analytical technique that can provide unique chemical and structural fingerprint information. However, gaining reliable quantitative analysis with SERS remains a huge challenge because of poor reproducibility and the instability of nanostructured SERS active surfaces. Herein, an effective strategy of coating Au nanoparticles (NPs) with ultrathin and uniform Prussian blue (PB) shell (Au@PB NPs) was developed for quantitative detection of dopamine (DA) concentrations in blood serum and crystal violet (CV) contaminants in lake water. The only intense PB Raman signal at 2155 cm-1 served as an ideal and interference-free internal standard (IS) for correcting fluctuations in the Raman intensities of analytes. Also, the stability of Au@PB NPs was investigated, exhibiting good functionality in strong acid solutions and thermal stability at 100 °C. This work demonstrates a convenient and fast quantitative SERS technique for detecting analyte concentrations in complex systems and has a great number of potential applications for use in analytical chemistry.

The selection of a surfactant for freshwater microalgae harvesting and separation by the foam separation method.

Collecting microalgae from water with less energy and cost is significant to gain economic profit from microalgae harvesting and processing. Foam separation has certain advantages including low energy consumption, simple operation and easy maintenance of the equipment. Natural surfactants, compared to traditional surfactants, were used to harvest and separate the freshwater microalgae Desmodesmus brasiliensis by foam separation. Results showed a recovery percentage of 93.6% and an enrichment ratio of 23.1 with the natural surfactant cocamidopropyl betaine (CAPB), suggesting that this low-cost surfactant can be applied to microalgae biomass recovery on a commercial scale using foam separation with no negative effect on the content of microalgae chlorophyll, carotenoid or protein.