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Rice-based Baijiu has gained popularity in the Chinese market. Qingya-flavored Baijiu, a variant of Xiaoqu-fermented Baijiu, employs rice as its primary raw material, with an improved production process compared to traditional rice-flavored Baijiu. We comprehensively characterized and compared the aroma profiles of these two rice-based Baijiu types using static sensory experiments (QDA, quantitative descriptive analysis) and dynamic sensory experiments (TDS, temporal dominance of sensations). Qingya-flavored Baijiu exhibited pronounced plant, oily, and roasted aromas, while traditional rice-flavored Baijiu displayed more prominent fruity, floral, and sour notes. Utilizing GC-O-MS (gas chromatography-olfactometry–mass spectrometry) and multi-method quantification, we qualitatively and quantitatively analyzed 61 key aroma compounds, identifying 22 compounds with significant aroma contributions based on odor activity values (OAVs). Statistical analyses, combining sensory and chemical results, were conducted to predict important aroma compounds responsible for the aroma differences between the two Baijiu types. Aroma Recombination and Omission experiments showed that seven compounds play key roles in the aroma of Qingya-flavored Baijiu, including (2E,4E)-Deca-2,4-dienal, linalool, apricolin, ethyl acetate, ethyl isobutyrate, ethyl caprylate, and ethyl isovalerate.

This work aimed to compare the aroma characteristics of representative brandies with different grades from Yantai (one of the Chinese core production areas) and Cognac and to establish relationships between sensory descriptors and chemical composition. Descriptive analysis was performed with a trained panel to obtain the sensory profiles. Forty-three aroma-active compounds were quantified by four different methodologies. A prediction model on the basis of partial least squares analysis was performed to identify candidate compounds that were unique to a certain group of brandies. The result showed that brandies from Yantai could be distinguished from Cognac brandies on the basis of spicy, dried fruit, floral, and fruity-like aromas, which were associated with an aromatic balance between concentrations of a set of compounds such as 5-methylfurfural, γ-nonalactone, and γ-dodecalactone. Meanwhile, brandy with different grades could be distinguished on the basis of compounds derived mostly during the aging process.

This study comprehensively characterized and compared the aroma differences between four different grades of Fenjiu (FJ, the most representative light-flavor Baijiu). Aroma-active compounds were analyzed by liquid-liquid extraction (LLE) coupled with gas chromatography-olfactometry-mass spectrometry (GC-O-MS). A total of 88 aroma-active compounds were identified, and 70 of them were quantified. The results showed that a majority of aroma compounds in high-grade FJ had higher aroma intensities and concentrations. Among these compounds, there were 28 compounds with odor activity values (OAVs) greater than one in all four wines, which indicated that they might contribute to the characteristic aroma of FJ. Temporal dominance of sensation (TDS) and quantitative descriptive analysis (QDA) were used to characterize the sensory differences. The results suggested that high-grade FJ had a rich, pleasant and lasting retronasal aroma perception and exhibited pleasant orthonasal aroma of floral, fruity, sweet and grassy. Partial least squares regression (PLSR) analysis effectively distinguished four kinds of FJ and revealed associations between the orthonasal aroma attributes and the aroma compounds with OAVs >1. There were 15 compounds with variable importance in projection (VIP) values >1, and they were considered potential aroma markers for quality prediction.

Extracellular vesicles (EVs) are membrane-bound vesicles that can be released by all cell types. They may have different biogenesis, physical features, and cargo. EVs are important biomarkers for the diagnosis and prediction of many diseases due to their essential role in intercellular communication, their highly variable cargoes, and their accumulation in various body fluids. These natural particles have been investigated as potential therapeutic materials for many diseases. In our previous studies, the clinical usage of tumor-cell-derived microparticles (T-MPs) as a novel medication delivery system was examined. This review summarizes the clinical translation of EVs and related clinical trials, aiming to provide suggestions for safer and more effective oncology therapeutic systems, particularly in biotherapeutic and immunotherapeutic systems.

In this study, oak barrels, glazed pottery altars, unglazed pottery altars, and stainless-steel tanks were selected as aging containers for red wine, and phenolic compounds and antioxidant activity were analyzed and compared. The color of red wine in unglazed pottery altars and glazed pottery altars changed to brick red and brownish yellow, respectively; the color of red wine in oak barrels did not change significantly; and color retention was best in stainless-steel tanks. The total content of anthocyanins and nonanthocyanin phenolic compounds was higher in the unglazed pottery altar group (227.68 mg/L and 288.88 mg/L, respectively) than in the oak barrel group (209.46 mg/L and 273.42 mg/L), the stainless-steel tank group (221.92 mg/L and 213.23 mg/L), or the glazed pottery altar group (74.71 mg/L and 204.43 mg/L). After aging, DPPH (1,1-diphenyl-2-picrylhydrazine free radical scavenging ability), I confirm. (ABTS+ free radical scavenging ability), and FRAP (a ferric ion-reducing antioxidant power reduction of Ion Ability) were decreased by 8.8%, 0.5%, and 17.1%, respectively, in the unglazed pottery altar group; by 15.2%, 1.7%, and 19.5%, respectively, in the oak barrel group; by 18.0%, 1.8%, and 20.0%, respectively, in the stainless-steel tank group; and by 18.7%, 4.2%, and 34.9%, respectively, in the glazed pottery altar group. In conclusion, antioxidative ability decreased less in the unglazed pottery altar group than in the other three groups, indicating that unglazed pottery altars retain antioxidant components in red wine well.

In this paper, a simple and environmentally friendly method was developed for the preparation of highly stable C@Fe3O4 composites with controllable morphologies using sodium alginate as the carbon source and the easily obtained α-Fe2O3 as the precursors. The morphologies of the as-prepared C@Fe3O4 composites, inherited from their corresponding precursors of α-Fe2O3, survived from the annealing treatments, were characterized by the field-emission scanning electron microscopy (FESEM), transmission electron microscopy (TEM), X-ray diffraction (XRD) and inductively coupled plasma-atomic emission spectroscopy (ICP-AES). The C@Fe3O4 composites resisted to oxidation, acidification and aggregation, exhibiting porous structures and ferromagnetic properties at room temperature. Moreover, the adsorption performance of the C@Fe3O4 composites was evaluated by absorbing MB (methylene blue) in liquid environment. Experiments indicated that the C@Fe3O4 composites exhibited highly enhanced adsorption capacities and efficiencies as compared with their corresponding precursors of α-Fe2O3. This generalized method for the synthesis of C@Fe3O4 composites provides promising applications for the highly efficient removal of MB from industrial effluents.

Source code summarization (SCS) is a natural language description of source code functionality. It can help developers understand programs and maintain software efficiently. Retrieval-based methods generate SCS by reorganizing terms selected from source code or use SCS of similar code snippets. Generative methods generate SCS via attentional encoder–decoder architecture. However, a generative method can generate SCS for any code, but sometimes the accuracy is still far from expectation (due to the lack of numerous high-quality training sets). A retrieval-based method is considered to have a higher accurac, but usually fails to generate SCS for a source code in the absence of a similar candidate in the database. In order to effectively combine the advantages of retrieval-based methods and generative methods, we propose a new method: Re_Trans. For a given code, we first utilize the retrieval-based method to obtain its most similar code with regard to sematic and corresponding SCS (S_RM). Then, we input the given code and similar code into the trained discriminator. If the discriminator outputs onr, we take S_RM as the result; otherwise, we utilize the generate model, transformer, to generate the given code’ SCS. Particularly, we use AST-augmented (AbstractSyntax Tree) and code sequence-augmented information to make the source code semantic extraction more complete. Furthermore, we build a new SCS retrieval library through the public dataset. We evaluate our method on a dataset of 2.1 million Java code-comment pairs, and experimental results show improvement over the state-of-the-art (SOTA) benchmarks, which demonstrates the effectiveness and efficiency of our method.

Source code summarization refers to the natural language description of the source code’s function. It can help developers easily understand the semantics of the source code. We can think of the source code and the corresponding summarization as being symmetric. However, the existing source code summarization is mismatched with the source code, missing, or out of date. Manual source code summarization is inefficient and requires a lot of human efforts. To overcome such situations, many studies have been conducted on Automatic Source Code Summarization (ASCS). Given a set of source code, the ASCS techniques can automatically generate a summary described with natural language. In this paper, we give a review of the development of ASCS technology. Almost all ASCS technology involves the following stages: source code modeling, code summarization generation, and quality evaluation. We further categorize the existing ASCS techniques based on the above stages and analyze their advantages and shortcomings. We also draw a clear map on the development of the existing algorithms.

Sweetness is an important Baijiu quality marker, but there is limited research on it. In this study, the main contributors to Baijiu sweetness were identified by “sensomics” combined with “flavoromics”. A total of 43 volatile compounds (mostly esters) were found that appeared to contribute to Baijiu sweetness, through sensory-guided fractionation and compositional analysis. Correlation analysis between the volatile composition and perceived sweetness of 18 Baijiu samples with different sweet intensities identified 14 potential contributors. Additional testing verified that combining the 14 compounds reproduced Baijiu sweetness exactly, and omission testing identified ethyl hexanoate, hexyl hexanoate and ethyl 3-methylbutanoate as the major contributors to Baijiu sweetness. These findings not only broadened our understanding of Baijiu sweetness, but also highlighted the major contribution of volatile compounds to sweetness perception, knowledge which may facilitate future flavor modification of a wide variety of foods and beverages.

Several anurans have broad elevational and latitudinal distribution ranges; distinct species and populations may face various environmental and selection stresses. Due to their environmental sensitivity, adaptation is critical for the long-term persistence of anurans. Previous studies have tried to identify the ecogeographical pattern and its mechanism in anurans, suggesting different patterns, but the related explanatory mechanisms are yet to be generally supported and are suggested to be complicated. To explore the elusive mechanisms, we studied the morphological variation of the plateau brown frog (Rana kukunoris) along an elevational gradient on the eastern margin of the Qinghai–Tibetan Plateau. Using body size, extremity length, and the ratio between them (extremities/body size) as testing indicators, we examined potential ecogeographical adaptations and investigated how environmental and biological factors could shape the morphological development in R. kukunoris. We found that males and females showed different variations in body size and extremities along the elevational gradient, whereas both of them showed a decreasing extremities/body size ratio along elevation. Together with the strong correlations between environmental and biological factors and the morphometrics, we identified ecogeographical adaptation and a sexual difference in the selective pressures on the extremities and body size of the plateau brown frog. Our results imply that geographic variations in anuran morphological traits should be understood as an outcome of environmental and biological factors. Furthermore, ecogeographical adaptation in anurans can manifest as an interactive change between body size and extremities.

The aim of this study is to comprehensively investigate the aroma composition and sensory attributes of Vidal icewine fermented with four yeast strains (ST, K1, EC1118, and R2). A total of 485 kinds of volatile components were identified by comprehensive two-dimensional gas chromatography-time of flight mass spectrometry, among which 347 kinds of volatile compounds were the same in four kinds of sample. The heat map was conducted with 156 volatile compounds, which have aroma contributions, and the analysis results identified the characteristics of the aroma composition of icewine fermented with different yeasts. Quantitative descriptive analysis was performed with a trained panel to obtain the sensory profiles. The aroma attributes of honey and nut of the icewine fermented by R2 were much higher than others. Partial least squares discriminant analysis further provided 40 compounds that were mainly responsible for the differences of the aroma characteristics of the icewines fermented by four yeasts. This study provides more data on the current status of Vidal icewines by main commercial yeasts.

Pungency is a crucial sensory feature that influences consumers’ appreciation and preferences toward alcoholic beverages. However, the quantitation of pungency is challenging to achieve using sensory analysis because of persistence, accumulation, and desensitization to the pungency perception. This study aimed to design a novel pungency evaluation method based on the measurement of tongue surface temperature. An infrared thermal (IRT) imager technique for measuring tongue surface temperature was established. To validate its feasibility, the IRT technique was used to measure tongue surface temperatures after the tongue was stimulated by (1) water and Baijiu, (2) different concentrations of ethanol aqueous solution (10, 20, 30, 40, and 50%, v/v), (3) ethanol aqueous solution and Baijiu samples with the same ethanol content, and (4) 26 Baijiu samples with different pungency level. For all cases, tongue surface temperatures showed large differences as a result of the different stimulation. The results showed that the tongue surface temperature correlated with the pungency intensity obtained by the sensory analysis. The relationship between tongue surface temperature and pungency intensity was established by multiple linear regression analysis. The IRT technique was able to be a useful support tool to quantitatively predict the pungency of alcoholic beverages, based on the measurement of tongue surface temperature.

Most of the construction machinery for vibro-sinking stone columns, which are widely used in China, needs to be improved in terms of degree of automation. Engineering quality control is mainly carried out post-inspection; consequently, it is difficult to control the construction quality in real time. According to the construction characteristics of traditional stone column machines, we established the theory and model for the real-time monitoring of stone column construction, as well as put forward an intelligent monitoring method for stone column machines. With the comprehensive application of critical technologies such as the Global Navigation Satellite System (GNSS) measurement technology, laser ranging sensors, and massive data processing, an intelligent data acquisition technique and associated monitoring equipment for stone column construction machines are developed. The data acquisition and storage of crucial construction parameters, such as pile depth, pile point co-ordinates, bearing layer current, and reverse insertion times, are realized. A large number of actual construction data are collected and the construction quality parameters of stone column machines are obtained. By comparison with third-party detection data, it is verified that the intelligent monitoring technique for stone column machines proposed in this paper is feasible.

Key odorants of red wine made from the hybrid grapes of Marselan (Vitis vinifera L.) were isolated by solid-phase extraction (SPE) and explored by gas chromatography-olfactometry (GC-O) analysis. Application of aroma extract dilution analysis (AEDA) revealed 43 odor-active compounds, and 31 odorants among them were detected with flavor dilution (FD) factors ranging from 9 to 2187. Comprehensive two-dimensional gas chromatography and time-of-flight mass spectrometry (GC × GC-TOF-MS) were exploited to quantitate the aroma-active compounds with FD ≥9. The identification indicated β-damascenone as having the highest FD factors, followed by eugenol, 2,3-butanedione, citronellol, 4-hydroxy-2,5-dimethyl-3(2H)-furanone, phenethyl acetate, guaiacol, and 2-methoxy-4-vinylphenol. A total of 21 compounds were found to have odor activity values (OAVs) >1.0. Aroma reconstitution validation experiments showed a good similarity of blackberry, green pepper, honey, raspberry, caramel, smoky, and cinnamon aroma attributes between the original Marselan wine and the reconstructed wine. In addition, omission tests were carried out to further determine the contribution of odorants to the overall aroma.

In this study, the aroma profiles of Cabernet Sauvignon wines from a new grape growing region, Loess Plateau, China, were established by gas chromatography–olfactometry, gas chromatography–mass spectrometry and sensory analysis. The sensory profiles of wines form five different young vineyards in the Loess Plateau region were obtained by descriptive analysis. Blackcurrant (p < 0.01), pear and dried plum (p < 0.05), mushroom, smoked and green pepper (p < 0.1) had significant differences on the five vineyards. A total of 76 odor-active aroma compounds were identified in the wines, and 45 volatile compounds were selected as those having the greatest impact on the aroma components and these were quantitated by five different methods. In addition, the correlation model of the Loess Plateau region’s sensory characteristics and aroma compounds was established by partial least squares regression (PLSR) to determine the influence of various aroma active substances on aroma attributes.

The joint is the weakest link in three-core medium-voltage power cable systems and the temperature is an essential indicator to its insulation condition. Therefore, a model to estimate the temperature inside the three-core cable joint was built based on support vector regression (SVR) with two fixed cable surface temperatures as inputs. The samples for model training were obtained from 3-D transient thermal analyses through finite element method (FEM) under different single-step currents. A temperature-rise test of 15 kV three-core cable joint was carried out and the estimated temperature based on SVR agrees well with the measured result with a maximum error of about 4 °C. Besides, the proposed model could accurately estimate the joint temperature even though the thermal conductivity of armor wrap used in thermal analysis for model training differs from its real value. The accuracies and calculation speed of the proposed model were compared with those of FEM, showing a better generality of our model. A temperature-rise test under unbalanced three-phase currents was performed and the temperature estimation errors are within 6 °C, indicating the applicability of the method. The effect of contact resistance was briefly discussed in the end. This approach helps improve cable operation and maintenance.

Accurate data about the spatial distribution and planting area of maize is important for policy making, economic development, environmental protection and food security under climate change. This paper proposes a new identification method for spring maize based on spectral and phenological features derived from the moderate resolution imaging spectroradiometer (MODIS) land surface reflectance time-series data. The method focused on the spectral differences of different land cover types in the specific phenological phases of spring maize by testing the selections and combinations of classification metrics, feature extraction methods and classifiers. Taking Liaoning province, a representative planting region of spring maize in Northeast China, as the study area, the results indicated that the combined multiple metrics, including the red reflectance, near-infrared reflectance and normalized difference vegetation index (NDVI), were conducive to the maize identification and were better than any single metric. With regard to the feature extraction and selection, maize identification based on different phenological features selected with prior knowledge was more efficient than that based on statistical features derived from the principal component analysis. Compared with the maximum likelihood classification method, the decision tree classification based on expert knowledge was more suitable for phenological features selected from some prior knowledge. In summary, discriminant rules were defined with those phenological features from multiple metrics, and the decision tree classification was used to identify maize in the study area. The producer’s accuracy of maize identification was 98.57%, and the user’s accuracy was 81.18%. This method can be potentially applied to an operational identification of maize at large scales based on remote sensing time-series data.

The numerical study of continuum-rarefied gas flows is of considerable interest because it can provide fundamental knowledge regarding flow physics. Recently, the nonlinear coupled constitutive method (NCCM) has been derived from the Boltzmann equation and implemented to investigate continuum-rarefied gas flows. In this study, we first report the important and detailed issues in the use of the H theorem and positive entropy generation in the NCCM. Importantly, the unified nonlinear dissipation model and its relationships to the Rayleigh–Onsager function were demonstrated in the treatment of the collision term of the Boltzmann equation. In addition, we compare the Grad moment method, the Burnett equation, and the NCCM. Next, differences between the NCCM equations and the Navier–Stokes equations are explained in detail. For validation, numerical studies of rarefied and continuum gas flows were conducted. These studies include rarefied and/or continuum gas flows around a two-dimensional (2D) cavity, a 2D airfoil, a 2D cylinder, and a three-dimensional space shuttle. It was observed that the present results of the NCCM are in good agreement with those of the Direct Simulation Monte Carlo (DSMC) method in rarefied cases and are in good agreement with those of the Navier–Stokes equations in continuum cases. Finally, this study can be regarded as a theoretical basis of the NCCM for the development of a unified framework for solving continuum-rarefied gas flows.