Search Results (106)

When process operators anticipate an alarm prior to its annunciation, that alarm loses information value and becomes a nuisance. This study investigated using eye trackers to measure and adjust the salience of alarms with three methods of gaze-based acknowledgement (GBA) of alarms that estimate operator anticipation. When these methods detected possible alarm anticipation, the alarm’s audio and visual salience was reduced. A total of 24 engineering students (male = 14, female = 10) aged between 18 and 45 were recruited to predict alarms and control a process parameter in three scenario types (parameter near threshold, trending, or fluctuating). The study evaluated whether behaviors of the monitored parameter affected how frequently the three GBA methods were utilized and whether reducing alarm salience improved control task performance. The results did not show significant task improvement with any GBA methods (F(3,69) = 1.357, p = 0.263, partial η² = 0.056). However, the scenario type affected which GBA method was more utilized (X² (2, N = 432) = 30.147, p < 0.001). Alarm prediction hits with gaze-based acknowledgements coincided more frequently than alarm prediction hits without gaze-based acknowledgements (X² (1, N = 432) = 23.802, p < 0.001, OR = 3.877, 95% CI 2.25–6.68, p < 0.05). Participant ratings indicated an overall preference for the three GBA methods over a standard alarm design (F(3,63) = 3.745, p = 0.015, partial η² = 0.151). This study provides empirical evidence for the potential of eye tracking in alarm management but highlights the need for additional research to increase validity for inferring alarm anticipation. Full article

Dixu tea is one of the characteristic tea germplasm resources of southeastern Yunnan, and is also a precious wild tea germplasm resource. Background: In order to further develop Dixu tea products and improve their flavor, this article studies the effects of different processing methods on the aroma quality of Dixu tea. Methods: A comprehensive analysis of the aroma quality of Diwei tea was conducted using HS-SPME combined with GC-MS and multivariate statistical analysis. A principal component analysis (PCA) was applied to process the detected volatile substances and an orthogonal partial least squares-discriminant analysis (OPLS-DA) model was established. We evaluated the contribution of major compounds in the tea aroma by calculating the odor activity value (OAV). Results: The results showed that a total of 67 compounds were identified. A total of 27 major aromatic volatile compounds (OAV > 1) were screened, and 17 key differential volatile compounds were identified in different tea samples, including octanoic acid, d-citrol, laurene, hexanal, citral, β-cyclic citral, trans-2-hexenal, γ-nonanolide, β-ionone, geranylacetone, 1,1,6-trimethyl-1,2-dihydronaphthalene, geraniol, methyl salicylate, linalool, nerolidol, and 7,11-dimethyl-3-methylene-1,6,10-dodecatriene. Combined with the OAV analysis, it is shown that a floral fragrance is a common feature of Guangnan Dixu tea varieties. In addition, white tea also has a fragrant aroma, while black tea, green tea, and bamboo tube tea are all accompanied by a fruity aroma. Conclusions: In summary, processing techniques regulate the aroma characteristics of various types of tea by changing the types and contents of volatile aroma compounds. This provides a theoretical basis for exploring and utilizing tea production resources in the future. Full article

Accurately monitoring total nitrogen (TN) content in field soils is crucial for precise fertilization management. TN content is one of the core indicators in soil fertility evaluation systems. Rapid and accurate determination of TN in the tillage layer is essential for agricultural production. Although UAV-based multispectral remote sensing technology has shown potential in agricultural monitoring, research on its quantitative assessment of soil TN content remains limited. This study utilized UAV (unmanned aerial vehicle) multispectral imagery and field-measured TN data from four key growth stages of silage corn in 2022 at Huari Ranch, Minle County, Hexi region. The support vector machine–recursive feature elimination (SVM-RFE) algorithm was applied to select vegetation indices as model inputs. A total of 18 models based on machine learning algorithms, including BP neural networks (BPNNs), random forest (RF), and partial least squares regression (PLSR), were constructed to compare the most suitable inversion model for TN in the rhizosphere soil (0–30 cm) of silage corn at different growth stages. The optimal period for TN inversion was determined. The SVM-RFE algorithm outperformed the models built without feature selection in terms of accuracy. Among the nitrogen inversion models based on different machine learning algorithms, the PLSR model showed the best performance, followed by the RF model, while the BPNN model performed the worst. The PLSR model established for the mature growth stage at soil depths demonstrated the highest inversion accuracy, with R and RMSE values of 0.663 and 0.281, respectively. The next best period was the tasseling stage, while the worst inversion accuracy was observed during the seedling stage, indicating that the mature stage is the optimal period for TN inversion in the study area. Full article

The construction industry’s development trend has resulted in a large volume of demolished concrete. Improving the efficiency of the proper use of this waste as a recycled aggregate (RA) in concrete is a promising solution. In this study, we utilized response surface methodology (RSM) and three machine learning (ML) techniques—the M5P algorithm, the random forest (RF) algorithm, and extreme gradient boosting (XGB)—to optimize and predict the compressive strength (CS) of RA concrete containing fly ash (FA), silica fume (SF), and polypropylene fiber (PPF). To build the models, the results regarding 529 data points were used as a dataset with varying numbers of input parameters (out of a total of ten). The CS quadratic model under RSM exhibited acceptable prediction accuracy. The best CS was found with a 100% volume of RA consisting of coarse aggregate, 1.13% PPF by volume of concrete, 7.90% FA, and 5.30% SF as partial replacements of binders by weight. The XGB model exhibited superior performance and high prediction accuracy, with a higher R² and lower values of errors, as depicted by MAE, RMSE, and MAPE, when compared to the other developed models. Furthermore, SHAP analysis showed that PPF had a positive impact on predicting CS, but the curing age and superplasticizer dose had the highest positive impact on predicting the CS of RA concrete. Full article

Avocado seeds (which are discarded during fruit processing) generate residue that could be utilized in pig feeding. The objective of this study was to test the effects of dietary inclusion of dried-milled avocado seeds (DAS) on pig performance, nutrient and energy digestibility, plasma biochemical parameters, and carcass and meat traits. Twenty-four Landrace × Large White barrows (24 kg body weight, BW) were randomly allocated to three experimental treatments: control diet (CO; 18% CP, 1.12% Lys, and 14 MJ ME/kg), and two diets in which 100 or 200 g DAS/kg partially replaced a CO diet (S10 and S20, respectively). Pigs were individually housed (22 ± 1 °C), and feed and water were provided ad libitum. Animals were weighed weekly and individual intake was monitored daily. The total tract apparent digestibility (TTAD) and nitrogen balance were determined. The experiment ended at 40 kg BW, when the animals were slaughtered for blood and tissue sampling. Voluntary feed intake was not affected by the addition of up to 200 g DAS/kg to the diet. However, growth, nutrient TTAD, and nitrogen retention were depressed at the highest DAS inclusion level. The nutritional characteristics of longissimus lumborum muscle were not affected by DAS ingestion. The inclusion of up to 100 g DAS/kg in the diets of growing pigs could be used to add value to this waste product. Full article

In order to improve the technical economy of steel-reinforced concrete structures and to promote the development of prefabricated concrete structures, a new type of partial precast steel-reinforced concrete column (precast stratified concrete composite column with inserted steel tube, PSCCST column) was proposed and studied in this paper. Six PSCCST column specimens were tested to investigate their behavior under eccentric loading. The failure state, ultimate bearing capacities, load–strain relationship, as well as load-deflection curves were emphatically investigated. The failure modes of the PSCCST columns under eccentric compression and corresponding bearing capacity N_u calculation methods were proposed based on experimental research and analysis. The results of the study indicated that there are three main failure modes, which are compressive-type failure mode, total-yield-type failure mode, and tensile-type failure mode. The first two modes are preferable due to their more effective material utilization. The N_u of the PSCCST column was found to decrease obviously with the increase of eccentricity e. The deformation capacity denoted by the horizontal lateral deflection corresponding to N_u increased with the increase of e. Moreover, the proposed N_u calculation methods were proven to have high accuracy by the comparison with the experimental results (the average ratio of the calculated values to the experimental values was 0.95). Full article

(1) Background: Hepatitis B virus (HBV) infection remains a major health challenge. Although vaccination protects people from HBV infection, 5–10% of people at risk of HBV infection and associated liver diseases do not respond to vaccination. The association of hematological indices with vaccine response is a crucial contributing factor in HBV-associated liver damage and the outcome of patients. In this context, we clinically assessed the interaction between inflammatory parameters and Hepatitis B vaccine response for the first time. (2) Methods: In total, 90 volunteers (44 non-responders and 46 responders) were included in this retrospective study. The demographic data and the hemogram parameters of the volunteers were recorded and statistically analyzed. Additionally, systemic inflammation index (SII), platelet-to-lymphocyte ratio (PLR), and neutrophil-to-lymphocyte ratio (NLR) were calculated. (3) Results: Our results indicate that higher median levels of white blood cells (8.61), lymphocytes (2.37), neutrophils (5.71), and platelets (280) were determined in the non-responders compared to the responders. SII and NLR indices were significantly higher in the non-responders than in the responders (p < 0.05). (4) Conclusions: The non-responders exerted higher systemic inflammation indicators than the responders, and the NLR value partially distinguished Hepatitis B vaccine response. Nevertheless, further studies with larger cohorts are essential to confirm the clinical utility of systemic inflammatory response as a reliable criterion for predicting Hepatitis B vaccine responsiveness. Full article

The improper application of phosphorus (P) fertilizers not only leads to resource wastage and environmental concerns but also disrupts the normal growth and yield formation of maize. This study aims to explore the effects of varying P application rates on the growth, yield, photothermal response characteristics, P accumulation dynamics, and P recovery efficiency (PRE) in summer maize, which provides a theoretical foundation for the efficient and scientific application of P fertilizers. Field experiments were conducted over two growing seasons (2021−2022) in Wen County, Henan Province, with P application rates set at 0, 30, 60, 90, and 120 kg·P₂O₅·ha⁻¹. At maturity, maize yield and its components were quantified. During key growth stages—jointing, tasseling, silking, and grain filling—plant height, leaf area, Soil and Plant Analyzer Development (SPAD) value, the fraction of photosynthetically active radiation (FPAR), canopy temperature, acid phosphatase activity (ACP), and P accumulation were measured. The results indicated that maize grain yield initially increased with P application, peaking at an average increase of 7.92–15.88%, before decreasing. The optimal P application rates were determined to be 113 kg·P₂O₅·ha⁻¹ and 68 kg·P₂O₅·ha⁻¹, respectively. P application significantly lowered canopy temperature and leaf ACP activity while significantly increasing the SPAD value and FPAR at 90 kg·P₂O₅·ha⁻¹. Logistic regression analysis of P accumulation revealed that increasing P rates enhanced the maximum (V_max) and mean (V_mean) accumulation rates, as well as the total P accumulation. Moderate P application also improved P absorption in various plant tissues and promoted the transfer of P to the grains. However, PRE, partial factor productivity from P fertilizer (PPFP), and P agronomic efficiency (PAE) declined at higher P rates. In conclusion, P fertilization enhanced maize yield, promoted growth, improved P utilization, and optimized photothermal response characteristics across different growth stages. Based on these findings, the recommended P application rate for summer maize is between 70 and 110 kg·P₂O₅·ha⁻¹. Full article

The total organic carbon (TOC) content in lake sediments is an effective archive indicating past climate changes. However, the resolution of the TOC record has generally been limited by factors such as subsampling intervals, hampering further comprehension of past climate change. Recently, hyperspectral imaging technology has been increasingly employed to scan lake sediment cores, presenting new opportunities to reconstruct high-resolution sequences, but the reconstruction of long-term high-resolution TOC records using hyperspectral imaging and the climate implications have not been well studied. In this study, we scanned sedimentary cores from Wudalianchi Crater Lake in northeast China with a spatial resolution of 400 × 400 μm, utilizing visible and near-infrared (VNIR) hyperspectral imaging technology. Then, a partial least-squares regression (PLSR) model was constructed by comparing eight different preprocessing methods and optimally selecting the best spectral subset combined with a genetic algorithm (GA). Our analysis demonstrates that the PLSR model, constructed using 62 relevant bands selected by the Savitzky–Golay second derivative (D2) preprocessing method and GA, was the most reliable, with the validation set’s R-value reaching a high of 0.91 and RMSE as low as 1.18%. Notably, the spectral range of 656–669 nm showed a strong positive correlation with measured TOC, indicating its sensitivity for TOC estimation. Given this advantage, we reconstructed the TOC records of sediments from the Wudalianchi Crater Lake during the 38–13 ka BP period, which exhibited significant millennial-scale fluctuation events. These corresponded well with the millennial-scale events in pollen and TOC from Lake Sihailongwan, δ¹⁸O records of Greenland ice cores, and δ¹⁸O records from Asian stalagmites. Thus, the combination of hyperspectral imaging and the PLSR model is effective in reconstructing high-resolution TOC changes in lake sediments, which is essential for understanding climate change as well as carbon burial in lakes. Full article

In this study, hydrogenated fat and butter in traditional puff pastry were partially replaced with vegetable oils from seeds to evaluate their impact on the physicochemical and sensory properties of the final product. The incorporation of vegetable oils led to changes in texture, specifically reducing hardness and chewiness. These modifications influenced the sensory perception of texture in some cases. In terms of color, the addition of vegetable oils reduced luminosity in all reformulated samples compared to the control, while parameters a* and b* were affected by the pigments present in the oils. From a nutritional perspective, this reformulation proved beneficial in reducing total fat content (between 7.34% and 17.19%) and, consequently, the energy value. The inclusion of vegetable oils also led to a decrease in saturated fatty acids, particularly in samples where butter was replaced, while the PUFA content increased (for example, 39.04% in puff pastry with chia oil; 43.04% in puff pastry with poppy oil) as well as the bioactive compounds (vitamin E). Moreover, depending on the oil used, the n-6/n-3 ratio increased compared to the control samples. Regarding sensory evaluation, all reformulated samples were well accepted, with scores above 1. However, across all evaluated parameters, the control samples consistently received higher scores. In conclusion, this study highlights the potential of vegetable oils as a viable alternative to replace traditionally used fats known for their negative health effects. Additionally, the utilization of seed oils derived from agri-food waste contributes to sustainability efforts, aligning with the goals of the 2030 Agenda and promoting innovative applications in the food industry. Full article

The nutritional content of tiger nut (Cyperus esculentus L.) is abundant, rich in oil, protein, and starch. Conventional methods for assessing the nutrient composition of tiger nuts (TNs) are time-consuming and labor-intensive. Near-infrared spectroscopy (NIR) combined with chemometrics has been widely applied in rapidly predicting the nutritional content of various crops, but its application to TNs is rare. In order to enhance the practicality of the method, this study employed a portable NIR in conjunction with chemometrics to rapidly predict the contents of crude oil (CO), crude protein (CP), and total starch (TS) from TNs. In the period from 2022 to 2023, we collected a total of 75 TN tuber samples of 28 varieties from Xinjiang Uyghur Autonomous Region and Henan Province. The three main components were measured using common chemical analysis methods. Partial least squares regression (PLSR) was utilized to establish prediction models between NIR and chemical indicators. In addition, to further enhance the prediction performance of the models, various preprocessing and variable selection algorithms were utilized to optimize the prediction models. The optimal models for CO, CP, and TS exhibited coefficient of determination (R²) values of 0.8946, 0.8525, and 0.8778, with root mean square error of prediction (RMSEP) values of 1.1764, 0.7470, and 1.4601, respectively. The absolute errors between the predicted and actual values for the three-indicator spectral measurements were 0.80, 0.59, and 0.99. The results demonstrated that the portable NIR combined with chemometrics could be effectively utilized for the rapid analysis of quality-related components in TNs. With further refinements, this approach could revolutionize TN quality assessment and be used to determine optimal harvest times, as well as facilitate the graded marketing of TNs. Full article

Wuyi Rock tea (WRT), originating from the northern region of Fujian province, has a good reputation for its distinctive Yan flavor and floral–fruity aroma. The aroma quality, an essential element of the Yan flavor, undergoes various changes during the manufacturing process of WRT. To enhance the understanding of the formation patterns of WRT aroma and its influence on the flavor quality of WRT, we utilized both manufactured WRT (Rougui tea) and primary tea as materials. Utilizing a sensory evaluation, detection of volatile compounds, and multivariate statistical analysis, we identified and characterized the distinctive volatile components present in WRT. The sensory evaluation and radar chart analysis revealed that the primary tea exhibited a strong and lasting aroma, along with a mellow taste and a prominent Yan flavor. Through gas chromatography time-of-flight mass spectrometry (GC-TOF MS), a total of 251 volatile compounds were identified. The odor activity value (OAV) was calculated to identify key aroma-active compounds in the primary tea. The results indicated that a total of 14 compounds had an OAV greater than 1.0, including (2-nitroethyl) benzene, indole, and geranylacetone. These compounds exhibited floral and fruity aroma attributes. They primarily formed and accumulated during the latter stages of WRT. Using a partial least squares discrimination analysis (PLS-DA) combined with a variable importance in projection (VIP) score greater than 1.0 as a criterion, a total of 89 compounds were identified. Furthermore, out of the selected compounds, 15 types, including geraniol, 1-nonanol, and 1-butyl-2-ethyl-cyclopropene, were found to exclusively exist during the enzymatic manufacturing stages, particularly during the intermediate and later phases of the turn-over process (the last-three-times turn-over treatments), exhibiting predominantly floral and sweet fragrances. In contrast, during the non-enzymatic stages, only four compounds, such as pentanoic acid and phenylmethyl ester, were detected, exhibiting a fruity aroma profile. These volatile compounds significantly influenced the quality attributes of the final tea product, resulting in strong and lasting characteristics, particularly marked by a pronounced floral and fruity aroma. This study revealed how the aroma quality in WRT is developed and pinpointed possible volatile compounds that react to post-harvest treatments, thereby offering valuable insights relating to the intelligent production strategies of WRT. Full article

Understanding the distribution patterns and driving mechanisms of bamboo species diversity on islands is essential for advancing knowledge of island ecosystem processes and informing strategies for bamboo resource conservation and management. This study utilized standardized major axis regression (SMA) to assess the effects of island area and isolation on bamboo species across 30 islands in Fujian, China. Furthermore, a partial least squares structural equation model (PLS-SEM) was constructed to explore the driving mechanisms underlying bamboo species richness. This analysis incorporated six key environmental factors—island size, isolation, shape, climate, development intensity, and habitat heterogeneity—spanning a total of 12 variables. The primary findings were as follows: (1) Eight genera and twenty-nine bamboo species were identified on Fujian islands. Species richness increased significantly with island area, consistent with the theory of area effects, while isolation had no significant impact on richness. (2) Different reproductive types exhibited distinct responses to environmental conditions. This was evident in the species–area relationship slopes (z-values): SR = 2.07; monopodial = 0.94; sympodial = 0.82; and polycyclic = 0.44. These variations highlight the ecological adaptability and functional traits of different reproductive strategies within island ecosystems. (3) Among the six environmental factors, island area exerted the greatest influence on species richness, underscoring its role as the primary driver of bamboo diversity and reproductive strategies. (4) Island area and isolation also impacted species richness indirectly through their effects on development intensity. In conclusion, the bamboo species richness and reproductive types on Fujian islands are primarily shaped by island area, followed by development intensity and habitat heterogeneity. In contrast, climate, island shape, and isolation play relatively minor roles. This study provides critical insights into the interplay of island area, isolation, shape, climate, development intensity, and habitat heterogeneity in shaping bamboo diversity. The findings offer a valuable foundation for bamboo resource conservation, island ecosystem management, and sustainable development. Full article

Secure aggregation of local learning model parameters is crucial for achieving privacy-preserving federated learning. This paper presents a novel and practical aggregation method that effectively combines the advantages of masking-based aggregation with those of homomorphic encryption-based techniques. Each node conceals its local parameters using a randomly selected mask, independently chosen, thereby eliminating the need for additional computations to generate or exchange mask values with other nodes. Instead, each node homomorphically encrypts its random mask using its own encryption key. During each federated learning round, nodes send their masked parameters and the homomorphically encrypted mask to the federated learning server. The server then aggregates these updates in an encrypted state, directly calculating the average of actual local parameters across all nodes without the necessity to decrypt the aggregated result separately. To facilitate this, we introduce a new multi-key homomorphic encryption technique tailored for secure aggregation in federated learning environments. Each node uses a different encryption key to encrypt its mask value. Importantly, the ciphertext of each mask includes a partial decryption component from the node, allowing the collective sum of encrypted masks to be automatically decrypted once all are aggregated. Consequently, the server computes the average of the actual local parameters by simply subtracting the decrypted total sum of mask values from the cumulative sum of the masked local parameters. Our approach effectively eliminates the need for interactions between nodes and the server for mask generation and sharing, while addressing the limitation of a single key homomorphic encryption. Moreover, the proposed aggregation process completes the global model update in just two interactions (in the absence of dropouts), significantly simplifying the aggregation procedure. Utilizing the CKKS (Cheon-Kim-Kim-Song) homomorphic encryption scheme, our method ensures efficient aggregation without compromising security or accuracy. We demonstrate the accuracy and efficiency of the proposed method through varied experiments on MNIST data. Full article

Reasonably using reclaimed water (RW) for irrigation can help to alleviate water scarcity, while also providing both environmental and economic benefits. However, there is limited information regarding the potential impact of RW irrigation on the nutrients of saline–alkali soils and their microbial communities. This study investigates the effects of RW irrigation on saline–alkali soil properties and microbial communities using a 16S rRNA sequence analysis. The results show that the pH and electrical conductivity (EC) are significantly lower in RW treatment (p < 0.05). Compared to the saline–alkali soil that was not irrigated with RW (CK), the EC value decreased by 42.15–45.76%, in both 0–20 cm and 40–60 cm depth. RW exhibited a significant increase in the abundance of Actinobacteria (32.32–33.42%), Chloroflexi (7.63–15.79%), Firmicutes (9.27–10.42%), and Ascomycota (89.85–95.95%). Bacterial richness and diversity were significantly enhanced after RW irrigation (p < 0.05). At the genus level, the dominant bacterial genera included Bacillus, Penicillium, Aspergillus, and Talaromyces. Differences in the microbial community were observed between the two treatments and among soil depths within each treatment (p < 0.05). A network analysis indicated that the internal relationships among bacterial communities become more complex following RW irrigation, whereas the internal connections within fungal communities tend to become more simplified. A redundancy analysis (RDA) showed that soil microbial communities were directly influenced by EC, total nitrogen (TN), and available potassium (AK). Partial least squares path modeling (PLS-PM) results indicated that soil salinity and available nutrients were the most significant factors influencing the microbial community structure. Together, these results indicate that RW irrigation has a positive impact on ameliorating soil salinity and enhancing microbial community diversity in saline–alkali soils. These findings provide valuable insights for the future agricultural utilization of saline–alkali land. Full article