Deep Learning-enabled Spatial Phase Unwrapping for 3D Measurement

In terms of 3D imaging speed and system cost, the single-camera system projecting single-frequency patterns is the ideal option among all proposed Fringe Projection Profilometry (FPP) systems. This system necessitates a robust spatial phase unwrapping (SPU) algorithm. However, robust SPU remains a challenge in complex scenes. Quality-guided SPU algorithms need more efficient ways to identify the unreliable points in phase maps before unwrapping. End-to-end deep learning SPU methods face generality and interpretability problems. This paper proposes a hybrid method combining deep learning and traditional path-following for robust SPU in FPP. This hybrid SPU scheme demonstrates better robustness than traditional quality-guided SPU methods, better interpretability than end-to-end deep learning scheme, and generality on unseen data. Experiments on the real dataset of multiple illumination conditions and multiple FPP systems differing in image resolution, the number of fringes, fringe direction, and optics wavelength verify the effectiveness of the proposed method.Comment: 26 page

Chemical composition of Chinese palm fruit and chemical properties of the oil extracts

The proximate composition, mineral concentration of fleshy mesocarp, palm meat (PM) and palm kernel (PK) of oil palm fruit (Elaeis guineensis S.L.Dura) produced in Hainan, China were investigated. The fatty acid composition, chemical properties and minor constituents of palm oil (PO) and palm kernel oil (PKO) were also studied. The crude fat of PM and PK were 68.09±3.57% and 49.36±2.61%, respectively. The PM and PK were found to be good sources of minerals. The acid value (AV) and free fatty acid (FFA) of PO extracted from fresh PM were much higher. If the fresh PM were heated at 100ºC for 30 min, the AV and % FFA could be reduced to 4.62±0.04 mgKOH/g and 2.72±0.002%, respectively. The major fatty acid of PO was palmitic acid 39.93±1.66% and that of PKO was lauric acid 48.01±0.69%. Tocopherol isomer (α-, (β+γ)- and δ-) contents in PO were 68.8±1.84, 22.8±0.54 and 11.8±0.12 mg/kg, respectively. The β-carotene content in PO was 901.5±11.95 mg/kg. The content of sterols in PO and PKO were 880.0±5.23 and 858.0±4.37 mg/kg, respectively. PO and PKO exhibited good chemical properties and could be used as edible oils and for industrial applications. There are almost no data about Chinese palm fruit now and this study systematically researched on it, which can provide useful information for Chinese oil palm industry.Key words: Chemical composition, palm fruit, palm oil, palm kernel oil, chemical properties

InfoEntropy Loss to Mitigate Bias of Learning Difficulties for Generative Language Models

Generative language models are usually pretrained on large text corpus via predicting the next token (i.e., sub-word/word/phrase) given the previous ones. Recent works have demonstrated the impressive performance of large generative language models on downstream tasks. However, existing generative language models generally neglect an inherent challenge in text corpus during training, i.e., the imbalance between frequent tokens and infrequent ones. It can lead a language model to be dominated by common and easy-to-learn tokens, thereby overlooking the infrequent and difficult-to-learn ones. To alleviate that, we propose an Information Entropy Loss (InfoEntropy Loss) function. During training, it can dynamically assess the learning difficulty of a to-be-learned token, according to the information entropy of the corresponding predicted probability distribution over the vocabulary. Then it scales the training loss adaptively, trying to lead the model to focus more on the difficult-to-learn tokens. On the Pile dataset, we train generative language models at different scales of 468M, 1.2B, and 6.7B parameters. Experiments reveal that models incorporating the proposed InfoEntropy Loss can gain consistent performance improvement on downstream benchmarks

Response of Carex breviculmis to phosphorus deficiency and drought stress

IntroductionThe drought and phosphorus deficiency have inevitably become environmental issues globally in the future. The analysis of plants functional trait variation and response strategies under the stress of phosphorus deficiency and drought is important to explore their ability to respond to potential ecological stress.MethodsIn this study, Carex breviculmis was selected as the research object, and a 14-week pot experiment was conducted in a greenhouse, with two phosphorus treatment (add 0.5mmol/L or 0.05μmol/L phosphorus) and four drought treatment (add 0-5%PEG6000), totaling eight treatments. Biomass allocation characteristics, leaf anatomical characteristics, biochemical parameters, root morphology, chemical element content, and photosynthetic parameters were measured.ResultsThe results showed that the anatomical characteristics, chemical elements, and photosynthetic parameters of Carex breviculmis responded more significantly to main effect of phosphorus deficiency. Stomatal width, leaf phosphorus content and maximum net photosynthetic rate decreased by 11.38%, 59.39%, 38.18% significantly (p<0.05), while the change in biomass was not significant (p>0.05). Biomass allocation characteristics and root morphology responded more significantly to main effect of drought. Severe drought significantly decreased leaf fresh weight by 61% and increased root shoot ratio by 223.3% compared to the control group (p<0.05). The combined effect of severe drought and phosphorus deficiency produced the highest leaf N/P ratio (291.1% of the control) and MDA concentration (243.6% of the control). Correlation analysis and redundancy analysis showed that the contributions of phosphorus and drought to functional trait variation were similar. Lower epidermal cell thickness was positively correlated with maximum net photosynthetic rate, leaf phosphorus, chlorophyll ab, and leaf fresh weight (p<0.05).DiscussionIn terms of response strategy, Carex breviculmis was affected at the microscopic level under phosphorus deficiency stress, but could maintain the aboveground and underground biomass well through a series of mechanisms. When affected by drought, it adopted the strategy of reducing leaf yield and improving root efficiency to maintain life activities. Carex breviculmis could maintain its traits well under low phosphorus and moderate drought, or better conditions. So it may have good ecological service potential in corresponding areas if promoted. This study also provided a reference for plant response to combined drought and phosphorus deficiency stresses

Effect of additives and moisture on the fermentation quality and bacterial community of high moisture ear corn

Maize (Zea mays L) is one of the most widely cultivated crops used as energy feeds. The aim of this study was to evaluate the effects of two lactic acid bacteria additives on the fermentation quality and bacterial community of high moisture ear corn (HMEC) silage at different moisture levels. The study utilized corn kernels and cobs harvested at the stage of complete ripeness as the primary material. The cob was crushed and divided into three treatment groups: an untreated control group (CK), a group treated with a mixture of Lactobacillus plantarum and Lactobacillus brucei (TQ), or a group treated with a mixture of Lactococcus lactis and Lactobacillus brucei (KT). Moisture contents were adjusted to 37.5% (L), 42.5% (M) or 47.5% (H) and then silaged for 180 days. Compared to CK, TQ, and KT elevated the dry matter, crude protein, starch, lactic and acetic acid content of HMEC and reduced the pH, neutral detergent fiber, acid detergent fiber and ammonia nitrogen content (p < 0.05). Even though both additives improved the bacterial community structure after fermentation, KT experienced the greater enhancement. At a phylum and genus level, KT had the higher relative abundance of Firmicutes and Lactobacillus, respectively. Compared with the group of 37.5% (L) moisture content, the 42.5% (M) and 47.5% moisture content (H) group increased lactic acid, acetic acid and ammonia nitrogen concentrations and reduced the pH value (p < 0.05). In conclusion, the addition of TQ and KT at the appropriate moisture content might be helpful for producing high-quality HMEC. Among the three moisture contents, 42.5% (M) moisture content provides the best silage qualities

Quality optical measurement system for shiny jet engine turbine vanes

Our main objective is to develop a measurement algorithm and software to process the laser sensor measurement data of jet engine turbine vane surfaces, and to reconstruct 3D profiles of these surfaces. In particular, the corrupted data due to the specular reflection are processed to obtain a nominal 3D surface profile.Master of Science (Computer Control and Automation

Enantioselective Decarboxylative C(sp3)-C(sp3) Cross-Coupling of Aliphatic Acids with gem-Borazirconocene Alkanes

Asymmetric decarboxylative cross-couplings of carboxylic acids represent a powerful tool to synthesize chiral building blocks for medicinal chemistry and material science. However, synthesis of versatile chiral alkylboron derivatives via asymmetric decarboxylative C(sp3)-C(sp3) cross-coupling from readily available primary aliphatic acids and mild organometallic reagents is still challenging. In this study, we report a visible-light-induced, Ni-catalyzed enantioconvergent C(sp3)-C(sp3) cross-coupling of unactivated primary aliphatic acids with gem-borazirconocene alkanes, furnishing a diverse array of valuable chiral alkylboron building blocks. The broad substrate scope, high functional group tolerance, and the late-stage modification of complex drug molecules and natural products with high enantioselectivity demonstrate the synthetic potential of the method. Mechanistic investigations suggest an enantioconvergent radical-radical cross-coupling pathway, wherein the primary radical from carboxylic acids is generated through single-electron reduction with ZrIII species, representing an unprecedented example of enantioselective radical C(sp3)-C(sp3) cross coupling in the absence of photocatalysts

Suggestions on the Development of Environmental Monitoring Technology of CO₂ Geological Storage and Leakage under the Background of China’s “Double-Carbon” Strategy

With the proposal of China’s national “double carbon” strategic goal, carbon capture, utilization and storage (CCUS) technology has attracted more and more attention. Due to the high cost, high energy consumption and high risk of CCUS technology, this technology is still in the initial stage of development in China. Among them, CO2 geological storage is one of the risks, and the environmental monitoring technology of CO2 storage leakage is particularly important in the large-scale popularization and application of CCUS technology in China. On the basis of extensive research on the related literature concerning CO2 storage and leakage, this paper begins with the types and mechanisms of CO2 storage, analyzes the ways and risks of CO2 storage and leakage and then summarizes the existing environmental monitoring technologies of CO2 geological storage and leakage. In the future, China can promote the progress of CO2 geological storage monitoring technology and help achieve the goal of “double carbon” by strengthening the research on CO2 storage mechanism and main control factors, perfecting the risk assessment method of CO2 storage, constructing the monitoring technology system of the CO2 storage life cycle, and standardizing the CO2 storage risk response system

A Current Sharing State Estimation Method of Redundant Switched-Mode Power Supply Based on LSTM Neural Network

Redundant Switched-mode Power supplies (SMPSs) are commonly used to improve electronic systems’ reliability, and accurate estimation of the current sharing state is significant for evaluating the system’s health. Currently, the current sharing state estimation is mainly realized by using current sensors to detect each branch’s current, and the deployment and maintenance costs are high. In this paper, a method for power supply current sharing state estimation based on LSTM recurrent neural network is proposed. By taking advantage of subtle differences in the inherent spectral characteristics of SMPSs, this method only needs to detect the voltage ripple at the switching frequency of the load terminal to estimate the output current of each power supply branch. The verification experiment on the three-power redundant experimental platform shows that the estimation error is less than 10%. The method has the characteristics of simple structure, non-invasion, convenient deployment and maintenance, so it has high application and promotion value