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Spectrometer miniaturization is desired for handheld and portable applications, yet nearly no miniaturized spectrometer is reported operating within terahertz (THz) waveband. Computational strategy, which can acquire incident spectral information through encoding and decoding it using optical devices and reconstruction algorithms, respectively, is widely employed in spectrometer miniaturization as artificial intelligence emerges. We demonstrate a computational miniaturized THz spectrometer, where a plasmonic filter array tailors the spectral response of a blocked-impurity-band detector. Besides, an adaptive deep-learning algorithm is proposed for spectral reconstructions with curbing the negative impact from the optical property of the filter array. Our spectrometer achieves modest spectral resolution (2.3 cm−1) compared with visible and infrared miniaturized spectrometers, outstanding sensitivity (e.g., signal-to-noise ratio, 6.4E6: 1) superior to common benchtop THz spectrometers. The combination of THz optical devices and reconstruction algorithms provides a route toward THz spectrometer miniaturization, and further extends the applicable sphere of the THz spectroscopy technique.

With the improvement of the accuracy of experimental devices and measuring instruments, cavitation experiments such as cross-media vehicles and propellers have been carried out in small pools. However, the water quality in the laboratory and the engineering application waters differs, especially the concentration of the gas nuclei that cause cavitation, resulting in experimental results that differ from prototype experimental results, and the scale effect occurs. In order to reduce the influence of the scale effect, according to the conditions of cavitation, gas nuclei can be mixed with water before the experiment is formally implemented. Aeration behavior will affect the size and concentration of gas nuclei (gas nuclei spectrum) in water. In order to obtain better experimental results, it is necessary to clarify the variation of the gas nuclei spectrum in small-scale experimental pools before and after aeration, so as to master aeration technology. Through research, it is found that the artificial aeration method can effectively change the gas nuclei spectrum in water and increase the concentration of gas nuclei. By using the underwater acoustic measurement method, the change in the gas nuclei spectrum can be captured sensitively. The gas nuclei spectrum in water after aeration is in good agreement with the mathematical model of gas nuclei spectrum under non-artificial intervention, which shows that the distribution of gas nuclei in water under artificial aeration is similar to that under non-artificial intervention, which is conducive to the occurrence of cavitation. At the same time, it shows that the combination of experiment and numerical method can reduce the measuring state and the measurement cost and improve the measurement efficiency.

ObjectiveTo evaluate the proficiency and consistency of domestic and foreign testing institutions in the field of veterinary drug residue detection in food， and to promote international cooperation and mutual recognition of testing results among these institutions.MethodsA robust statistical analysis was conducted on the testing results of 20 laboratories in eight countries and regions across North America， Europe， and Asia. The laboratories’ testing capabilities were evaluated using Z-score comparison.ResultsAmong the 20 participating laboratories， 18 achieved satisfactory results， resulting in a satisfaction rate of 90%， while 2 laboratories （10%） failed to meet the requirements. The satisfaction rate of domestic laboratories （100%） was higher than that of foreign laboratories （81.8%）.ConclusionDomestic laboratories perform better than overseas laboratories in determining veterinary drug residues in food. To enhance testing capabilities， these overseas laboratories with unsatisfactory evaluation results should strengthen their daily quality control and ensure traceability of original records.

ObjectiveTo establish microbial limit test methods for 44 pediatric drugs.MethodsAccording to the general guidelines in Chinese Pharmacopoeia （2015 and 2020 edition， volume Ⅳ），a suitability test of the methods for 44 drugs was carried out by pour-plate method， neutralization method or dilution method.ResultsTotal aerobic microbial count： chemical oral liquid samples can be tested by 1∶10 plate method；traditional Chinese medicine need to be neutralized firstly. Then oral liquids could be tested by 1∶10 plate method and 1∶100 plate method was used for granules. Total count of molds and yeasts： all the samples can be tested by the 1∶10 plate method. The recoveries of five test strains were between 0.5 and 2.0. The specified microorganisms were all detected in the test group， while not found in the negative control group.ConclusionThe microbial limit test methods for the 44 pediatric drugs are established and the results are reliable and can be used in the quality control．

ObjectiveA rapid enrichment and detection method for Escherichia coli O157∶H7 was developed by using multienzyme isothermal rapid amplification （MIRA） fluorescence method combined with metal organic frameworks immunomagnetic beads.MethodsUsing rfbE gene as the target， the primers， probes and reaction system were screened， and the specificity， sensitivity and practical application of this method were investigated.ResultsThe detection limit of Escherichia coli O157∶H7 was 1.18×105 CFU‧mL-1， and the detection limit of DNA concentration was 9 pg‧μL-1. The detection process was completed in 20 minutes. The test results of 47 strains （24 target strains and 23 non-target strains） were consistent with real-time PCR （RT-PCR）.ConclusionA method based on metal-organic framework immunomagnetic beads enrichment combined with MIRA assay is developed in this study. The method is simple， rapid and suitable for rapid enrichment and detection of Escherichia coli O157∶H7 in food.

ObjectiveTo prepare samples of proficiency testing （PT） containing live Staphylococcus aureus with drug matrix in microbial PT program of drug testing， and to evaluate the laboratory capability of microbiology tests in China.MethodsTwo kinds of PT samples containing living bacteria with drug matrix were prepared and evaluated. The results of laboratories participated in PT program and their response to the survey questionnaire were collected and analyzed.ResultsThe homogeneity and stability of the PT samples complied with the requirements of CNAS-CL03： 2010. Samples could be stored stably for at least 6 months at -20 ℃. Among 63 laboratories participating in PT program， 53 laboratories （84.1%） achieved satisfactory results. The satisfaction rate was 94.1% （16/17） in 17 government laboratories （27.0% of total 63 laboratories）， 81.4% （35/43） in 43 pharmaceutical quality control laboratories （68.3% of total 63 laboratories）， and 66.7% （2/3） in 3 non-government laboratories （4.8% of total 63 laboratories）， respectively.ConclusionThe government laboratories performed better than pharmaceutical quality control laboratories in microbiology tests of drug， and the testing abilities of some pharmaceutical laboratories needs to be improved. The preparation and application of microbial samples in drug matrix could provide evaluation tools for drug testing laboratories in microbiology.

ObjectiveTo investigate the microbial contamination in 54 batches of commercial honey.MethodsAerobic plate colony counts for bacteria and colonies of mould and osmophilic yeasts in honey were determined according to the National Food Safety Standard. The bacteria and fungi in unqualified samples were further identified and analyzed by morphology， MALDI-TOF-MS and large subunit （LSU） rRNA gene sequence.ResultsThree unqualified batches were found. One batch had aerobic plate colony counts exceeding the standard， with a variety of bacteria including Bacillus sp.， Paenibacillus sp. and Brevibacillus sp. Two batches had mould counts exceeding the standard. Aspergillus sp was detected in both samples （from the same manufacturer）， and the DNA sequence homology was very high， suggesting the mould might come from the same pollution source.ConclusionThere are many kinds of microbial contamination in honey. Manufacturers should strengthen the microbe control in monitoring process to avoid the repeated microbial contamination.

Computational micro-spectrometers comprised of detector arrays and encoding structure arrays, such as on-chip Fabry-Perot (FP) cavity filters, have great potential in many in-situ applications owing to their compact size and snapshot imaging ability. Given manufacturing deviation and environmental influence are inevitable, easy and effective calibration for spectrometer is necessary, especially for in-situ applications. Currently calibration strategies based on iterative algorithms or neural networks require accurate measurements of pixel-level (spectral) encoding functions through monochromator or large amounts of standard samples. These procedures are time-consuming and expensive, thereby impeding in-situ applications. Meta-learning algorithms with few-shot learning ability can address this challenge by incorporating the prior knowledge in the simulated dataset. In this work, we propose a meta-learning algorithm free of measuring encoding function or large amounts of standard samples to calibrate a micro-spectrometer with manufacturing deviation effectively. Our micro-spectrometer comprises 16 types of FP filters covering a wavelength range of 550-720 nm. The center wavelength of each filter type deviates from the design up to 6 nm. After calibration with 15 different color data, the average reconstruction error on the test dataset decreased from 7.2 × 10- 3 to 1.2 × 10- 3 , and further decreased to 9.4 × 10- 4 when the calibration data increased to 24. The performance is comparable to algorithms trained with measured encoding function both in reconstruction error and generalization ability. We estimated that the cost of in-situ calibration through reflectance measurements of color chart decreased to one percent of the cost through monochromator measurements. By exploiting prior deviation information in simulation data with meta-learning, the efficiency and cost of calibration are significantly improved, thereby facilitating the large-scale production and in-situ application of micro-spectrometers.