Rapid determination of starch and alcohol contents in fermented grains by hyperspectral imaging combined with data fusion techniques.

Starch and alcohol serve as pivotal indicators in assessing the quality of lees fermentation. In this paper, two hyperspectral imaging (HSI) techniques (visible-near-infrared (Vis-NIR) and NIR) were utilized to acquire separate HSI data, which were then fused and analyzed toforecast the starch and alcohol contents during the fermentation of lees. Five preprocessing methods were first used to preprocess the Vis-NIR, NIR, and the fused Vis-NIR and NIR data, after which partial least squares regression models were established to determine the best preprocessing method. Following, competitive adaptive reweighted sampling, successive projection algorithm, and principal component analysis algorithms were used to extract the characteristic wavelengths to accurately predict the starch and alcohol levels. Finally, support vector machine (SVM)-AdaBoost and XGBoost models were built based on the low-level fusion (LLF) and intermediate-level fusion (ILF) of single Vis-NIR and NIR as well as the fused data. The results showed that the SVM-AdaBoost model built using the LLF data afterpreprocessing by standard normalized variable was most accurate for predicting the starch content, with an R P 2 $\ R_P^2$ of 0.9976 and a root mean square error of prediction (RMSEP) of 0.0992. The XGBoost model built using ILF data was most accurate for predicting the alcohol content, with an R P 2 $R_P^2$ of 0.9969 and an RMSEP of 0.0605. In conclusion, the analysis of fused data from distinct HSI technologies facilitates rapid and precise determination of the starch and alcohol contents in fermented grains.

Response mechanism of a highly efficient partial nitritation-anammox (PN/A) process under antibiotic stress: Extracellular polymers, microbial community, and functional genes.

The Partial nitritation-Anammox (PN/A) process can be restricted when treating high ammonia nitrogen wastewater containing antibiotics. This study aims to explore the response mechanism of the PN/A process under antibiotic stress. Results showed the PN/A process achieved a nitrogen removal rate higher than 1.01 ± 0.03 kg N/m3/d under long-term sulfamethazine stress. The increase of extracellular polymers from 22.52 to 43.96 mg/g VSS was conducive to resisting antibiotic inhibitory. The increase of Denitratisoma and SM1A02 abundance as well as functional genes nirS and nirK indicated denitrifiers should play an important role in the stability of the PN/A system under sulfamethazine stress. In addition, antibiotic-resistant genes (ARGs) sul1 and intI1 significantly increased by 8.78 and 5.12 times of the initial values to maintain the resistance of PN/A process to sulfamethazine stress. This study uncovers the response mechanism of the PN/A process under antibiotic stress, offering a scientific basis and guidance for further application in the future.

Detection of wheat saccharification power and protein content using stacked models integrated with hyperspectral imaging.

BACKGROUND: Wheat is one of the key ingredients used to make Chinese liquor, and its saccharification power and protein content directly affect the quality of the liquor. In pursuit of a non-destructive assessment of wheat components and the optimization of raw material proportions in liquor, this study introduces a precise predictive model that integrates hyperspectral imaging (HSI) with stacked ensemble learning (SEL). RESULTS: This study extracted hyperspectral information from 14 different varieties of wheat and employed various algorithms for preprocessing. It was observed that multiplicative scatter correction (MSC) emerged as the most effective spectral preprocessing method. The feature wavelengths were extracted from the preprocessed spectral data using three different feature extraction methods. Then, single models (support vector machine (SVM), backpropagation neural network (BPNN), random forest (RF), and gradient boosting tree (XGBoost)) and a SEL model were developed to compare the prediction accuracies of the SEL model and the single models based on the full-band spectral data and the characteristic wavelengths. The findings indicate that the MSC-competitive adaptive reweighted sampling-SEL model demonstrated the highest prediction accuracy, with Rp 2 (test set-determined coefficient) values of 0.9308 and 0.9939 for predicting the saccharification power and protein content and root mean square error of the test set values of 0.0081 U and 0.0116 g kg-1, respectively. CONCLUSION: The predictive model established in this study, integrating HSI and SEL models, accurately detected wheat saccharification power and protein content. This validation underscores the practical potential of the SEL model and holds significant importance for non-destructive component analysis of raw materials used in liquor. © 2024 Society of Chemical Industry.

Aberrant degree centrality profiles during rumination in major depressive disorder.

Rumination is closely linked to the onset and maintenance of major depressive disorder (MDD). Prior neuroimaging studies have identified the association between self-reported rumination trait and the functional coupling among a network of brain regions using resting-state functional magnetic resonance imaging (MRI). However, little is known about the underlying neural circuitry mechanism during active rumination in MDD. Degree centrality (DC) is a simple metric to denote network integration, which is critical for higher-order psychological processes such as rumination. During an MRI scan, individuals with MDD (N = 45) and healthy controls (HC, N = 46) completed a rumination state task. We examined the interaction effect between the group (MDD vs. HC) and condition (rumination vs. distraction) on vertex-wise DC. We further characterized the identified brain region's functional involvement with Neurosynth and BrainMap. Network-wise seed-based functional connectivity (FC) analysis was also conducted for the identified region of interest. Finally, exploratory correlation analysis was conducted between the identified region of interest's network FCs and self-reported in-scanner affect levels. We found that a left superior frontal gyrus (SFG) region, generally overlapped with the frontal eye field, showed a significant interaction effect. Further analysis revealed its involvement with executive functions. FCs between this region, the frontoparietal, and the dorsal attention network (DAN) also showed significant interaction effects. Furthermore, its FC to DAN during distraction showed a marginally significant negative association with in-scanner affect level at the baseline. Our results implicated an essential role of the left SFG in the rumination's underlying neural circuitry mechanism in MDD and provided novel evidence for the conceptualization of rumination in terms of impaired executive control.

2D Heterostructure of Amorphous CoFeB Coating Black Phosphorus Nanosheets with Optimal Oxygen Intermediate Absorption for Improved Electrocatalytic Water Oxidation.

The oxygen evolution reaction (OER) plays a paramount role in a variety of electrochemical energy conversion devices, and the exploration of highly active, stable, and low-cost electrocatalysts is one of the most important topics in this field. The exfoliated black phosphorus (EBP) nanosheet with a two-dimensional (2D) layered structure has high carrier mobility but is limited by excessive oxygen-containing intermediate absorption and fast deterioration in air. We here report the fabrication of nanohybrids of amorphous CoFeB nanosheets on EBP nanosheets (EBP/CoFeB). The 2D/2D heterostructure, thanks to the electronic interactions and oxygen affinity difference between EBP and CoFeB nanosheets, is capable of balancing the oxygen-containing intermediate absorption to an optimal status for facilitating the OER process. While the crystalline EBP contributes to the improved conductivity, the amorphous coating protects EBP and thus ensures the catalytic stability. The EBP/CoFeB electrocatalyst shows excellent OER performance with an ultralow overpotential of 227 mV at 10 mA cm-2 with an ultrasmall Tafel slope of 36.7 mV dec-1 with excellent stability. This study may inspire more researches to develop heterostructured nanohybrid electrocatalysts for a diversity of electrochemical reactions.

In situ growth of Z-scheme CuS/CuSCN heterojunction to passivate surface defects and enhance charge transport.

Copper thiocyanate (CuSCN) has been considered as a promising hole transport material (HTMs), attributing to its inherent stability, low-cost, and suitable energy levels. To make it more attractive in practical applications, the drawbacks of CuSCN in poor charge transport and serious defect recombination are bottlenecks that need to be overcome. In this work, we propose an effective strategy of in-situ decorating CuSCN with copper sulfide quantum dots (CuS QDs), a simple one-step electrochemical deposition process, to solve these issues. Compared with the pristine CuSCN, the constructed Z-Scheme heterojunction of CuS QDs/CuSCN can significantly promote charge transport and restrict recombination. In addition, the decorated CuS QDs can not only passivate defects of CuSCN, but also provide more contacting sites to facilitate hole injection when employing as HTM. As a result, the average bulk charge lifetime was improved from 0.37 ms to 0.47 ms, and the surface recombination rate constant was suppressed. We believe that the excellent performances will pave it toward practical device applications, including solar cells, photocatalysis, photoelectrochemical sensors, and light-emitting diodes.

Recent Progress and Development in Inorganic Halide Perovskite Quantum Dots for Photoelectrochemical Applications.

Inorganic halide perovskite quantum dots (IHPQDs) have recently emerged as a new class of optoelectronic nanomaterials that can outperform the existing hybrid organometallic halide perovskite (OHP), II-VI and III-V groups semiconductor nanocrystals, mainly due to their relatively high stability, excellent photophysical properties, and promising applications in wide-ranging and diverse fields. In particular, IHPQDs have attracted much recent attention in the field of photoelectrochemistry, with the potential to harness their superb optical and charge transport properties as well as spectacular characteristics of quantum confinement effect for opening up new opportunities in next-generation photoelectrochemical (PEC) systems. Over the past few years, numerous efforts have been made to design and prepare IHPQD-based materials for a wide range of applications in photoelectrochemistry, ranging from photocatalytic degradation, photocatalytic CO2 reduction and PEC sensing, to photovoltaic devices. In this review, the recent advances in the development of IHPQD-based materials are summarized from the standpoint of photoelectrochemistry. The prospects and further developments of IHPQDs in this exciting field are also discussed.

Hydrogenated ZnIn2S4 microspheres: boosting photocatalytic hydrogen evolution by sulfur vacancy engineering and mechanism insight.

In some oxide photocatalysts, changing their surface structure rather than crystal structure by introducing some defects (such as oxygen vacancies) has been proven to be effective in enhancing the separation efficiency of photogenerated carriers and thus photocatalytic activity. To the best of our knowledge, however, such a surface defect engineering strategy for sulfide photocatalysts has rarely been verified. The present work shows the first case of employing pressure hydrogenation to prepare hydrogenated ZnIn2S4 (H-ZIS) microspheres with surface-deficient porous structures, which are favorable for furnishing sufficient surface sulfur vacancies to realize excellent photocatalytic hydrogen evolution reactions. The hydrogen evolution rate (HER) of H-ZIS is as high as 1.9 mmol h-1 g-1 (nearly 8.6 times that of the pristine ZIS sample), which rivals or exceeds those of previously-reported ZIS-based photocatalysts under visible light irradiation. Meanwhile, the inherent correlation between surface sulfur vacancies and photocatalytic activities of H-ZIS is also explored. Thus, this work demonstrates the feasibility of enhancing the hydrogen evolution capability of sulfide photocatalysts by the formation of sulfur vacancies through a pressure hydrogenation process.

Oxygen vacancies induced by zirconium doping in bismuth ferrite nanoparticles for enhanced photocatalytic performance.

Doping with certain foreign metal ions in a photocatalyst might introduce surface defects (such as extrinsic oxygen vacancies), which can probably play an important role in the photocatalytic performance. In this work, oxygen vacancies were for the first time introduced into bismuth ferrite (BiFeO3, denoted as BFO) nanoparticles by zirconium (Zr) doping, and the relationship between oxygen vacancies and the photocatalytic activity of Zr-doped BFO was investigated. It was found that the optical properties and the photocatalytic activities of Zr-doped BFO photocatalysts were significantly affected by the Zr doping amount. The Zr-doped BFO photocatalysts showed much higher photocatalytic activities for methyl orange degradation or Cr(VI) reduction than the pristine BFO. When the Zr doping content was 2mol%, the highest photocatalytic efficiency was achieved, which was more than two times that of the pristine BFO. The boosted photocatalytic performance of Zr-doped BFO was mainly attributed to the presence of surface oxygen vacancies induced by Zr doping, which could act as electron traps and active sites to promote the efficient separation and migration of photogenerated charge carriers, as verified by the trapping experiments and the photoelectrochemical measurements. Thus, the present work provides a simple approach to introduce oxygen vacancies in semiconductor photocatalysts through metal ion doping with a great potential for development of efficient visible light photocatalysts, and also enlarges the understanding of surface-defect dependence of photocatalytic performance for environmental remediation.

Enhanced visible light photocatalytic activity of Gd-doped BiFeO3 nanoparticles and mechanism insight.

To investigate the effect of Gd doping on photocatalytic activity of BiFeO3 (BFO), Gd-doped BFO nanoparticles containing different Gd doping contents (Bi(1-x)GdxFeO3, x = 0.00, 0.01, 0.03, 0.05) were synthesized using a facile sol-gel route. The obtained products were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, X-ray photoelectron spectra, and ultraviolet-visible diffuse reflectance spectroscopy, and their photocatalytic activities were evaluated by photocatalytic decomposition of Rhodamine B in aqueous solution under visible light irradiation. It was found that the Gd doping content could significantly affect the photocatalytic activity of as-prepared Gd-doped BFO, and the photocatalytic activity increased with increasing the Gd doping content up to the optimal value and then decreased with further enhancing Gd doping content. To elucidate the enhanced photocatalytic mechanism of Gd-doped BFO, the trapping experiments, photoluminescence, photocurrent and electrochemical impedance measurements were performed. On the basis of these experimental results, the enhanced photocatalytic activities of Gd-doped BFO could be ascribed to the increased optical absorption, the efficient separation and migration of photogenerated charge carriers as well as the decreased recombination probability of electron-hole pairs derived from the Gd doping effect. Meanwhile, the possible photocatalytic mechanism of Gd-doped BFO was critically discussed.

Hydrothermal Synthesis of BiFeO3 Nanoparticles for Visible Light Photocatalytic Applications.

Bismuth ferrite is a promising material for visible light response photocatalytic applications due to its narrow band gap. In this work, single crystalline BiFeO3 nanoparticles were prepared by a modified hydrothermal process. The effects of hydrothermal temperature, reaction time and precursor xerogel amoumt on the as-prepared BiFeO3 particle size and morphology were investigated by XRD, TEM and HRTEM. The XRD analysis reveals that single crystalline BiFeO3 particles can be obtained when the hydrothermal temperature is kept below 220 degrees C. TEM observation showed that the as-formed BFO particles are in a square or rectangle-like shape and that the particle size is increased with increasing hydrothermal temperature. The hydrothermal reaction time and the amount of xerogel could also influence the as-formed BFO particle morphology and size. The band gap of the as-prepared BFO nanoparticles was identified by UV-vis diffuse reflectance spectrum. The measurement of photodegradation of methyl orange dye in an aqueous solution revealed that the as-prepared BFO nanoparticles exhibit photocatalytic activity under visible light irradiation.

[Meta-analysis of the relationship between dairy product consumption and gastric cancer].

OBJECTIVE: To clarify the effect of milk consumption on gastric cancer in China. METHODS: China National Knowledge Infrastructure (CNKI) and other Chinese databases were searched for randomized controlled trials reporting the relationship between dairy products consumption and gastric carcinoma patients from January 1985 to June 2008. Manual searching was also performed. Gastric carcinoma, dietary, milk or diary product were using as key words. A Meta-analysis method was applied to estimate the combined odds ratio (OR) and 95% confidence interval (95% CI) between dairy product consumption and gastric cancer. RESULTS: Eight case-control studies published between 1985 and 2008 were selected for Meta-analysis. The cumulative cases and controls were 1684 and 5410, respectively. Fixed-effect model was used because of homogeneity among these studies. The overall pooled OR estimate was 0.57 (95% CI = 0.46 - 0.71), suggesting a negative association between dairy product consumption and gastric cancer. CONCLUSION: This Meta-analysis supports the hypothesis that dairy product consumption might decrease the risk of gastric cancer.