Status of uncertainty assessment in k 0-NAA measurement: anything still missing?

Several approaches to quantifying measurement uncertainty in k ₀-based neutron activation analysis (k ₀-NAA) are reviewed, comprising the original approach, the spreadsheet approach, the dedicated computer program involving analytical calculations and the two k ₀-NAA programs available on the market. Two imperfectness in the dedicated programs are identified, their impact assessed and possible improvements presented for a concrete experimental situation. The status of uncertainty assessment in k ₀-NAA is discussed and steps for improvement are recommended. It is concluded that the present magnitude of measurement uncertainty should further be improved by making additional efforts in reducing uncertainties of the relevant nuclear constants used.     

Development of a solid‐phase microextraction fiber by the chemical binding of graphene oxide on a silver‐coated stainless‐steel wire with an ionic liquid as the crosslinking agent

Graphene oxide was bonded onto a silver‐coated stainless‐steel wire using an ionic liquid as the crosslinking agent by a layer‐by‐layer strategy. The novel solid‐phase microextraction fiber was characterized by scanning electron microscopy, energy‐dispersive X‐ray spectroscopy and Raman microscopy. A multilayer graphene oxide layer was closely coated onto the supporting substrate. The thickness of the coating was about 4 μm. Coupled with gas chromatography, the fiber was evaluated using five polycyclic aromatic hydrocarbons (fluorene, anthracene, fluoranthene, 1,2‐benzophenanthrene, and benzo(a)pyrene) as model analytes in direct‐immersion mode. The main conditions (extraction time, extraction temperature, ionic strength, and desorption time) were optimized by a factor‐by‐factor optimization. The as‐established method exhibited a wide linearity range (0.5–200 μg/L) and low limits of determination (0.05–0.10 μg/L). It was applied to analyze environmental water samples of rain and river water. Three kinds of the model analytes were quantified and the recoveries of samples spiked at 10 μg/L were in the range of 92.3–120 and 93.8–115%, respectively. The obtained results indicated the fiber was efficient for solid‐phase microextraction analysis.     

A sensitive immunosorbent bio-barcode assay based on real-time immuno-PCR for detecting 3,4,3',4'-tetrachlorobiphenyl

A functionalized gold-nanoparticle bio-barcode assay, based on real-time immuno-PCR (IPCR), was designed for the determination of 3,4,3',4'-tetrachlorobiphenyl (PCB77). 15 nm gold nanoparticles were synthesized, and modified with thiol-capped DNA and goat anti-rabbit IgG. The nanoparticle probes were used to replace antibody–DNA conjugate in the IPCR, and were fixed on the PCR tube wall via the immune reaction. Real-time PCR was performed to quantify the DNA signal directly. Under optimized conditions, the new method was used to detect PCB77 with a linearity range from 5 pg L^?1 to 10 ng L^?1, and the limit of detection (LOD) was 1.72 pg L^?1. Real samples of Larimichthys polyactis, collected from the East China Sea, were analyzed. Recovery was from 82 % to 112 %, and the coefficient of variation (CV) was acceptable. The results were compared with GC–ECD, revealing that the method would be acceptable for providing rapid, semi-quantitative, and reliable test results for making environmental decisions.

Redox Dyshomeostasis Strategy for Hypoxic Tumor Therapy Based on DNAzyme-Loaded Electrophilic ZIFs

Redox homeostasis is one of the main reasons for reactive oxygen species (ROS) tolerance in hypoxic tumors, limiting ROS-mediated tumor therapy. Proposed herein is a redox dyshomeostasis (RDH) strategy based on a nanoplatform, FeCysPW@ZIF-82@CAT Dz, to disrupt redox homeostasis, and its application to improve ROS-mediated hypoxic tumor therapy. Once endocytosed by tumor cells, the catalase DNAzyme (CAT Dz) loaded zeolitic imidazole framework-82 (ZIF-82@CAT Dz) shell can be degraded into Zn²⁺ as cofactors for CAT Dz mediated CAT silencing and electrophilic ligands for glutathione (GSH) depletion under hypoxia, both of which lead to intracellular RDH and H₂O₂ accumulation. These “disordered” cells show reduced resistance to ROS and are effectively killed by ferrous cysteine-phosphotungstate (FeCysPW) induced chemodynamic therapy (CDT). In vitro and in vivo data demonstrate that the pH/hypoxia/H₂O₂ triple stimuli responsive nanocomposite can efficiently kill hypoxic tumors. Overall, the RDH strategy provides a new way of thinking about ROS-mediated treatment of hypoxic tumors.     

Pressure-Suppressed Carrier Trapping Leads to Enhanced Emission in Two-Dimensional Perovskite (HA)2(GA)Pb2I7

A remarkable PL enhancement by 12 fold is achieved using pressure to modulate the structure of a recently developed 2D perovskite (HA)₂(GA)Pb₂I₇ (HA=n-hexylammonium, GA=guanidinium). This structure features a previously unattainable, extremely large cage. In situ structural, spectroscopic, and theoretical analyses reveal that lattice compression under a mild pressure within 1.6 GPa considerably suppresses the carrier trapping, leading to significantly enhanced emission. Further pressurization induces a non-luminescent amorphous yellow phase, which is retained and exhibits a continuously increasing band gap during decompression. When the pressure is released to 1.5 GPa, emission can be triggered by above-band gap laser irradiation, accompanied by a color change from yellow to orange. The obtained orange phase could be retained at ambient conditions and exhibits two-fold higher PL emission compared with the pristine (HA)₂(GA)Pb₂I₇.     

光锥与TDI-CCD耦合监控中测试目标的一种实现方法

为了给光锥与时间延迟积分电荷耦合器件耦合监控装置提供有效的被测运动条纹,分析了传统推扫成像实验装置的不足之处,设计了电子显示目标滚屏运动装置.采用光学相机对印刷条纹静止成像,并用TDI-CCD数字相机对监视器屏幕上的运动条纹动态成像.实验结果表明,该方案解决了高分辨率的鉴别率图样无法在监视器或投影仪上精确显示的困难.与传统的实验室模拟装置相比,该方案提高了鉴别率条纹的运动稳定性,减小了条纹运动速率与TDI-CCD扫描行频间的失配误差,不仅能够对耦合过程实施监控,而且还能用于耦合系统的像质评价.     

A Maximal Correlation Framework for Fair Machine Learning

As machine learning algorithms grow in popularity and diversify to many industries, ethical and legal concerns regarding their fairness have become increasingly relevant. We explore the problem of algorithmic fairness, taking an information–theoretic view. The maximal correlation framework is introduced for expressing fairness constraints and is shown to be capable of being used to derive regularizers that enforce independence and separation-based fairness criteria, which admit optimization algorithms for both discrete and continuous variables that are more computationally efficient than existing algorithms. We show that these algorithms provide smooth performance–fairness tradeoff curves and perform competitively with state-of-the-art methods on both discrete datasets (COMPAS, Adult) and continuous datasets (Communities and Crimes).     

Recent Advances on Metal-Organic Frameworks in the Conversion of Carbon Dioxide

With the development of modern industry,global warming is becoming a challenging issue due to the emissions of large quantities of greenhouse gases,mainly carbon dioxide(CO₂).The conversion of CO₂to useful compounds is considered as an effective and economic way to solve such a climate problem.Metal-organic frameworks(MOFs)are an emerging class of porous crystalline materials that have shown great potential in the conversion of CO₂.The advantages of MOFs in CO 2 conversion lie in their high surface areas,adjustable pore size,and high porosity.More importantly,desirable functional sites can be easily designed and precisely installed to the pore wall of target MOFs by pre-assembly and/or post-synthetic modification(PSM)ways.This review summarizes the recent advances in constructing MOF catalysts for the application in CO₂conversion.We believe that the design and synthesis of MOF catalysts for CO₂conversion can be a promising way to solve the“greenhouse effect”.     

Morphine-induced conditioned place preference in mice: Metabolomic profiling of brain tissue to find “molecular switch” of drug abuse by gas chromatography/mass spectrometry

Conditioned place preference (CPP) is a widely used model to explore the mechanism of context-dependent learning. In this work, we developed a GC–MS method to investigate the metabolites in mice brain which was used to study the mechanism of context-dependent learning associated with rewarding effect of morphine. Metabolites were extracted from brain tissues and derivatized followed by analysis by gas chromatography/mass spectrometry (GC–MS). In total, 69 peaks were identified as known compounds. By a Wilcoxon ran sum test with p value ≤0.05, 21 metabolites were selected and considered as the potential biomarkers of morphine in mice brain. Using principal component analysis (PCA) and receiver-operator characteristic (ROC) curves, a model was constructed with a combination of these 21 metabolic markers. Multivariate statistics of the model yielded separation between the two groups with an area under the curve value of 0.947. Some metabolites were further discussed in detail about their pathway. Results showed that our technique can be successfully applied to profile for biomarkers and in understanding molecular mechanisms of drug abuse.