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Food packaging can develop defects during the production process due to various factors. The types of packaging defects are numerous with complex background. Machine vision detection, which uses visual imaging and computer information processing to complete tasks such as identification, detection, and measurement of packaging, has faster execution speed and higher accuracy compared to traditional manual inspection. This can significantly improve the degree of production automation. This article analyzes the common defects in food packaging and their causes, introduces traditional machine vision detection algorithms, and explores the research application of deep learning algorithms in food packaging defect detection. It also analyzes the prospects and challenges of applying detection algorithms in food packaging defect detection.

Clouds play a vital role in weather, climate system and the atmospheric water cycle. The diagnosis and evaluation of numerical model prediction results is important for numerical model research and development. Reasonable diagnosis and evaluation methods can not only provide references for model researchers to optimize model schemes, but also help users understand the performance of model prediction. The cloud characteristics of different regions and seasons should be considered for evaluation because the attributes in different regions are markedly different. The performance and deviation characteristics of the operational CMA-GFS of four seasons are evaluated, based on the reanalysis of ERA5 reanalysis data from March 2021 to February 2022. The frequency bias of cloud occurrence, cloud fraction, integrated cloud hydrometeors from various levels, and the bias and root mean square error of those variables are carefully diagnosed and evaluated via different methods. The deviation characteristics of cloud are emphatically analyzed according to different regions. The possible causes for the significant difference of cloud prediction deviation characteristics at different levels in different regions are preliminarily discussed. The results show that the overall distribution of cloud predicted by CMA-GFS is reasonable, which can describe the meridional peak and valley distribution characteristics of global cloud and reflect the seasonal trend. The cloud amount deviation of high cloud and medium cloud by CMA-GFS is greater than that of low cloud. The root mean square error of cloud amount of high cloud and medium cloud is smaller than that of low cloud. And the model stability for high cloud and medium cloud prediction is also better. The liquid-phased hydrometers integration is mainly negative deviation, and the ice-phased hydrometers integration is mainly positive deviation. The causes of the deviation of cloud predicted by CMA-GFS are different in different regions. In tropical region the deviation is related to the incongruity of convective parameterization and microphysical schemes, while in middle and high latitudes regions the deviations are related to the bias of relative humidity. It also shows that the diagnosis of model cloud features will cover up the actual problems only by a single method, and it needs to be evaluated comprehensively by combining a variety of methods.

We investigated the potential role of hydrogen sulfide (H2S) as a novel therapy for diabetic peripheral neuropathy in diabetic rats. A single dose of streptozotocin (60 mg/kg) was applied to the rats for the diabetic rat models. Sodium bisulfide (50 μmol/kg/d) was injected intraperitoneally daily for 2 weeks as H2S treatment. Electromyogram, haematoxylin eosin staining, transmission electron microscopy, western blotting and enzyme‐linked immunosorbent assay were then performed. H2S treatment did not affect body weights, blood glucose levels or liver function of diabetic rats, while the creatine levels of the H2S‐treated diabetic rats decreased compared with the diabetic control rats. H2S treatment for 2 weeks did not affect the sciatic nerve conduction velocity of the diabetic rats. However, H2S treatment relieved neurons loss and cell atrophy of dorsal root ganglion, and axon degeneration of sciatic nerve in diabetic rats. Serum super oxide dismutase (SOD) levels and SOD2 levels in the sciatic nerve of diabetic rats were lower than the non‐diabetic rats but were restored after H2S treatment. Serum and sciatic nerve homogenate malondialdehyde and aldose reductase expression were higher in diabetic rats but decreased significantly after H2S treatment. Our study revealed that H2S alleviates neural degeneration in diabetic rats probably by reducing oxidative stress and downregulating aldose reductase expression. [ABSTRACT FROM AUTHOR]

ABSTRACT Aims/Introduction Methods Results Conclusions The aim of this study was to identify a metabolic signature of MIDD as compared to healthy controls and other types of diabetes.We performed a comprehensive serum metabolomic analysis using gas chromatography‐time of flight mass spectrometry (GC‐TOFMS) in participants diagnosed with MIDD (n = 14), latent autoimmune diabetes in adults (LADA) (n = 14), type 2 diabetes mellitus (n = 14), and healthy controls (n = 14). Each group was matched for gender and age.There were significant metabolic differences among MIDD and other diabetic and control groups. Compared with control, MIDD patients had high levels of carbohydrates (glucose, galactose, mannose, sorbose, and maltose), fatty acids (2‐Hydroxybutyric acid, eicosapentaenoic acid, and octadecanoic acid), and other metabolites (alanine, threonic acid, cholesterol, lactic acid, and gluconic acid), but low level of threonine. Compared with LADA, MIDD patients had high levels of threonic acid and some amino acids (alanine, tryptophan, histidine, proline, glutamine, and creatine) but low levels of serine. Compared with type 2 diabetes mellitus, MIDD patients had high levels of citrulline, creatine, 3‐Amino‐2‐piperidone, but low levels of ornithine, fatty acids (arachidonic acid and octadecanoic acid), and intermediates of the tricarboxylic acid cycle (malic acid and succinic acid).Our study identified a specific metabolic profile related to glycolysis and the tricarboxylic acid cycle in MIDD that differs from healthy controls and other types of diabetes. This unique metabolic signature provides new perspectives for understanding the pathophysiology and underlying mechanisms of MIDD. [ABSTRACT FROM AUTHOR]

Modified polyimide (MPI) flexible printed circuits (FPCs) are used as chip carrier boards. The quality of the FPC directly affects the reliability of the integrated circuit. Furthermore, micro-holes are critical components of FPCs. In this study, an ultraviolet (UV) femtosecond laser is used to drill micro-holes in double-layer flexible circuit boards with MPI as the substrate. The morphology of the micro-hole wall in the copper foil and MPI layer is observed, and the effects of the laser processing parameters on the diameter and depth of the micro-holes are analyzed. The drilling process and mechanism of micro-holes obtained using a UV femtosecond laser in MPI FPCs are discussed. The results show that the morphology of femtosecond laser-machined copper is closely related to the laser energy, and a periodic structure is observed during the machining process. Copper, MPI, and copper oxides are the most common molten deposits in micro-holes during drilling. The depth of the micro-holes increases with an increase in the energy of a single pulse, scanning time, and scanning overlap rate of the laser beam. However, the diameter exhibits no discernible alteration. The material removal rate increased significantly when laser processing was applied to the MPI resin layer. [ABSTRACT FROM AUTHOR]