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This experiment combines analytical techniques of solid-phase extraction (SPE) and gas chromatography quadrupole time-of-flight mass spectrometry (GC-QTOF-MS) to determine organochlorine pesticides (OCPs) in river water as a means to develop and improve student understanding of the use of GC-QTOF-MS for qualitative and quantitative analysis. In the classroom, students are presented with the principles and instrumentation of SPE, GC, and QTOF-MS via conventional lectures and question--answer sessions. In the laboratory, they are introduced to the procedure for tuning GC-QTOF-MS and developing a new method, analyzing OCPs in standard solutions to obtain retention times and characteristic ions, employing the mass spectrometry data to conduct library matching, and completing the identification and quantification of OCPs in the river. Additionally, students learn how to deduce the chemical formula of an "unknown" eluent compound by relying on high-resolution mass measurements and isotopic distributions. This method could be applied in the courses of instrumental analysis or environmental analysis. It could be readily adapted to other analytes such as the presence of steroids or other pharmaceuticals.

Microglia play a critical role in the pathophysiology of Alzheimer's disease. They are involved in Aβ-induced neuroinflammatory responses, regulating the production of inflammatory mediators. Interferon regulatory factor 5 (IRF5) plays a central role in inflammatory diseases in the periphery, the role of which in central nervous system remains elusive. This study aimed to investigate the role of IRF5 in Aβ-induced neuroinflammation and the progression of Aβ pathology. We found that Aβ1–42 oligomers significantly increased the level of IRF5 in BV2 microglia. The levels of proinflammatory cytokines TNF-α, IL-1β, and IL-6 were significantly upregulated with Aβ treatment. IRF5 knockdown with siRNA in microglia significantly reduced the expression of these proinflammatory factors induced by Aβ and promoted Aβ phagocytosis. Besides, LC3 upregulation and p62 downregulation were observed in IRF5 knockdown microglia. This was also validated in APP/PS1 mice with IRF5 knockdown, leading to reduced Aβ levels in the brain. We conclude that IRF5 mediates Aβ-induced microglial inflammatory responses. IRF5 knockdown attenuated Aβ-induced inflammatory responses and promoted the phagocytosis and autophagy of Aβ by microglia. [ABSTRACT FROM AUTHOR]

Revealing the energy transfer (ET) process from excitons to rare earth ions in halide perovskites has great guiding value for designing optoelectronic materials. Here, the multiple ET channels in multi‐exciton emissive Sb3+/Nd3+ co‐doped Cs2ZrCl6 are explored to comprehend the ET processes. Förster–Dexter ET theory reveals that the sensitizer concentration rather than the overlap integral of the spectra plays the leading function in the comparison of the ET efficiency among multiple ET channels from the host self‐trapped excitons (STEs) and dopant triplet STEs to Nd3+ ions. Besides, Sb3+/Nd3+ co‐doped Cs2ZrCl6 enables varied color delivery and has great potential as anti‐counterfeiting material. Under X‐ray irradiation, Sb3+/Nd3+ co‐doped Cs2ZrCl6 presents a high light yield of ≈13300 photons MeV−1 and promising X‐ray imaging ability. This work provides new insight for investigating the ET efficiency among multiple ET processes and presents great potentiality of multi‐exciton emissive perovskites in the fields of anti‐counterfeiting and X‐ray imaging. [ABSTRACT FROM AUTHOR]

Video analytics has a wide range of applications and has attracted much interest over the years. While it can be both computationally and energy-intensive, video analytics can greatly benefit from in/near memory compute. The practice of moving compute closer to memory has continued to show improvements to performance and energy consumption and is seeing increasing adoption. Recent advancements in solid state drives (SSDs) have incorporated near memory Field Programmable Gate Arrays (FPGAs) with shared access to the drive's storage cells. These near memory FPGAs are capable of running operations required by video analytic pipelines such as object detection and template matching. These operations are typically executed using Convolutional Neural Networks (CNNs). A CNN is composed of multiple individually processed layers that perform various image processing tasks. Due to lack of resources, a layer may be partitioned into more manageable sub-layers. These sub-layers are then processed sequentially, however, some sub-layers can be processed simultaneously. Moreover, the storage cells within FPGA equipped SSDs are capable of being augmented with in-storage compute to accelerate CNN workloads and exploit the intra-parallelism within a CNN layer. To this end, we present our work, which leverages heterogeneous architectures to create an in/near-storage acceleration solution for video analytics. We designed a NAND flash accelerator and an FPGA accelerator, then mapped and evaluated several CNN benchmarks. We show how to utilize FPGAs, local DRAMs, and in-memory SSD compute to accelerate CNN workloads. Our work also demonstrates how to remove unnecessary memory transfers to save latency and energy. [ABSTRACT FROM AUTHOR]

The dual-credit policy, as an important emerging policy in the Chinese automotive industry intended to achieve energy savings, emissions reductions, and promote the development of new energy vehicles (NEVs), has attracted considerable attention from scholars. This study investigates how this policy affects the research and development (R&D) levels of both component suppliers and vehicle manufacturers in the automotive supply chain. Assuming the bounded rationality of the participants, we construct a complex dynamic evolutionary model under Stackelberg games to explore the impact of the policy on the dynamic game behavior and equilibrium stability of R&D levels. Furthermore, we examine the influences of various parameters on the R&D level complex system. The findings reveal that the disparity in the proportion of NEVs in the policy should not be too large; otherwise, bifurcation and chaos may occur in the R&D level game system. Moreover, higher supplier research efficiency contributes to the stability of R&D levels, while the higher credit trading price is not suitable for stable R&D levels. This paper theoretically reveals the dynamic impact of the dual-credit policy on the R&D levels in the automotive supply chain, bridging the gap between previous studies assuming decision-makers as fully rational and the reality of bounded rationality. It also provides managerial recommendations for the implementation details of this policy. [ABSTRACT FROM AUTHOR]