Multivariate optimization and comparison between conventional extraction (CE) and ultrasonic-assisted extraction (UAE) of carotenoid extraction from cashew apple

Carotenoids are an essential component of cashew and can be used in pharmaceuticals, cosmetics, natural pigment, food additives, among other applications. The present work focuses on optimizing and comparing conventional and ultrasound-assisted extraction methods. Every optimization step took place with a 1:1 (w:w) mixture of yellow and red cashew apples lyophilized and ground in a cryogenic mill. A Simplex-centroid design was applied for both methods, and the solvents acetone, methanol, ethanol, and petroleum ether were evaluated. After choosing the extractor solvent, a central composite design was applied to optimize the sample mass (59–201 mg) and extraction time (6–34 min). The optimum conditions for the extractor solvent were 38% acetone, 30% ethanol, and 32% petroleum ether for CE and a mixture of 44% acetone and 56% methanol for UAE. The best experimental conditions for UAE were a sonication time of 19 min and a sample mass of 153 mg, while the CE was 23 min and 136 mg. Comparing red and yellow cashews, red cashews showed a higher carotenoid content in both methodologies. The UAE methodology was ca. 21% faster, presented a more straightforward composition of extracting solution, showed an average yield of superior carotenoid content in all samples compared to CE. Therefore, UAE has demonstrated a simple, efficient, fast, low-cost adjustment methodology and a reliable alternative for other applications involving these bioactive compounds in the studied or similar matrix.     

Sample preparation,instrumental analysis,and natural distribution of complex organic pollutants in the wastewater from unconventional gas production

Large amounts of flowback and produced water (FPW) have been generated from hydraulic fracturing process for the production of unconventional gas such as shale gas. Complex organic pollutants are abundantly present in FPW with revealed toxicity to aquatic organisms and these contaminants may transfer into surrounding aquatic environment. Characterization and determination of complicated organic pollutants in FPW remains a challenge due to its complex composition and high salinity matrix. This review article covers the progress of recent 5 years regarding the sample preparation and instrumental analysis methods and thus summarizes the advantages and disadvantages of these methods for critical analysis of organic contaminants in FPW samples. Furthermore, the natural distribution of detected organic compounds and their transformation were reviewed and discussed to enhance the understanding of spatial and temporal behaviors of these organic pollutants in natural environment, paving the way for future development of pollution control policies and strategies. Enlightened by the studies of FPW contamination in the US, the investigations of FPW contamination in China continued to grow due to rapidly growing production of shale gas in China and resulted pollution.     

介观电路中量子纠缠的经典对应

从量子力学诞生日起,它的经典对应(或类比)一直是物理学家关心的话题.本文以介观电路量子化的框架中,带有互感的两个介观电容-电感(LC)电路为例,首次讨论了量子纠缠的经典类比(或对应)问题.先用有序算符内的积分理论证明其互感是产生量子纠缠的源头;再推导出求解特征频率的公式,就发现它与一个经典系统的小振动频率的表达式有相似之处,该经典系统组成如下:两个墙壁各连一个相同的弹簧,两个弹簧之间接着一个滑动小车可以在光滑的桌面上运动,小车挂有一根单摆.用分析力学求此系统的小振动频率,发现与上述介观电路的特征频率形式类似,单摆的摆动会造成小车来回振动,摆、小车和弹簧的互相牵制效应反映了小车和摆的"纠缠".     

Co-Training for Visual Object Recognition Based on Self-Supervised Models Using a Cross-Entropy Regularization

Automatic recognition of visual objects using a deep learning approach has been successfully applied to multiple areas. However, deep learning techniques require a large amount of labeled data, which is usually expensive to obtain. An alternative is to use semi-supervised models, such as co-training, where multiple complementary views are combined using a small amount of labeled data. A simple way to associate views to visual objects is through the application of a degree of rotation or a type of filter. In this work, we propose a co-training model for visual object recognition using deep neural networks by adding layers of self-supervised neural networks as intermediate inputs to the views, where the views are diversified through the cross-entropy regularization of their outputs. Since the model merges the concepts of co-training and self-supervised learning by considering the differentiation of outputs, we called it Differential Self-Supervised Co-Training (DSSCo-Training). This paper presents some experiments using the DSSCo-Training model to well-known image datasets such as MNIST, CIFAR-100, and SVHN. The results indicate that the proposed model is competitive with the state-of-art models and shows an average relative improvement of 5% in accuracy for several datasets, despite its greater simplicity with respect to more recent approaches.     

从知识传授到育人:高职“生活中的化学”教学实践*

深挖高职院校公选课“生活中的化学”的育人元素,精心设计教学内容,运用课堂主题辩论、趣味生活实验的设计与展示、探秘生活中的化学等理论知识传授与课内外实践相结合的教学方式,实现全过程育人,充分展现了公选课在立德树人方面的价值。     

A simple three‐wave approximate Riemann solver for the Saint‐Venant‐Exner equations

Erosion and sediments transport processes have a great impact on industrial structures and on water quality. Despite its limitations, the Saint‐Venant‐Exner system is still (and for sure for some years) widely used in industrial codes to model the bedload sediment transport. In practice, its numerical resolution is mostly handled by a splitting technique that allows a weak coupling between hydraulic and morphodynamic distinct softwares but may suffer from important stability issues. In recent works, many authors proposed alternative methods based on a strong coupling that cure this problem but are not so trivial to implement in an industrial context. In this work, we then pursue 2 objectives. First, we propose a very simple scheme based on an approximate Riemann solver, respecting the strong coupling framework, and we demonstrate its stability and accuracy through a number of numerical test cases. However, second, we reinterpret our scheme as a splitting technique and we extend the purpose to propose what should be the minimal coupling that ensures the stability of the global numerical process in industrial codes, at least, when dealing with collocated finite volume method. The resulting splitting method is, up to our knowledge, the only one for which stability properties are fully demonstrated.     

Development of a new catalytic and sustainable methodology for the synthesis of benzodiazepine triazole scaffold using magnetically separable CuFe2O4@MIL-101(Cr) nano-catalyst in aqueous medium

Magnetically retrieval CuFe₂O₄@MIL-101(Cr) metal–organic framework was successfully prepared from easily available starting materials and characterized using various spectroscopic and analytical techniques such as powder X-ray diffraction, scanning electron microscopy, energy dispersive X-ray, transmission electron microscopy, elemental mapping, Fourier transform infrared spectroscopy, thermogravimetric analysis, X-ray photoelectron spectroscopy, Brunauer–Emmett–Teller, vibrating sample magnetometer, and inductively coupled plasma optical emission spectroscopy. The catalyst was then used in the synthesis of benzodiazepines containing a triazole moiety in water. The advantages of this protocol include high yields, reusability of the catalyst, and gram-scale synthesis.     

Nickel (II) tetrapyridyl complexes as electrocatalysts and precatalysts for water oxidation

Two nickel complexes, [Ni(tpen)](ClO₄)₂.0.5CH₃COCH₃ ( 1 ) and [Ni(tpbn)](ClO₄)₂ ( 2 ), of tetrapyridyl ligands N,N,N′,N′-tetrakis(2-pyridyl-methyl)-1,2-ethanediamine (tpen) and N,N,N′,N′-tetrakis(2-pyridyl-methyl)-1,4-butanediamine (tpbn) were prepared and their catalysis for water oxidation reaction (WOR) studied. In 0.1 M phosphate buffer solution (PBS) of pH 8.0, complex 1 is a homogeneous molecular catalyst with an overpotential of ~440 mV and a Faradaic efficiency of 89%. At pH ≥ 9.0, complex 1 degraded gradually during the catalytic process and formed NiO_x composite (nickel oxide with general formula Ni_xO_yH_z) active for WOR. In contrast, complex 2 deteriorated under measured conditions (pH 8.0–12.0) and formed NiO_x composite active for WOR. The NiO_x composite derived from 1 in 0.1 M PBS at pH 11.0 showed an activity with an overpotential of ~500 mV, a Tafel slope of ~90 mV/decade and a Faradaic efficiency of 97%. Mechanisms were proposed for water oxidation catalyzed by 1 and 2 . This work revealed that the catalytic activity of the nickel complexes was related to the flexibility of the tetrapyridyl ligands and the adaptability of the coordination sphere of the nickel(II) center.