Iodine(III)‐Catalyzed Rearrangements of Imides: A Versatile Route to α,α‐Dialkylated α‐Hydroxy Carboxylamides

A tertiary hydroxy group α to a carboxyl moiety comprises a key structural motif in many bioactive substances. With the herein presented metal‐free rearrangement of imides triggered by hypervalent λ³‐iodane, an easy and selective way to gain access to such a compound class, namely α,α‐disubstituted‐α‐hydroxy carboxylamides, was established. Their additional methylene bromide side chain constitutes a useful handle for rapid diversification, as demonstrated by a series of further functionalizations. Moreover, the in situ formation of an iodine(III) species under the reaction conditions was proven. Our findings clearly corroborate that hypervalent λ³‐benziodoxolones are involved in these organocatalytic reactions.     

Caesium carbonate supported on hydroxyapatite‐encapsulated Ni0.5Zn0.5Fe2O4 nanocrystallites as a novel magnetically basic catalyst for the one‐pot synthesis of pyrazolo[1,2‐b]phthalazine‐5,10‐diones

A novel nanomagnetic basic catalyst of caesium carbonate supported on hydroxyapatite‐coated Ni_0.5Zn_0.5Fe₂O₄ magnetic nanoparticles (Ni_0.5Zn_0.5Fe₂O₄@HAP‐Cs₂CO₃) was prepared. This new catalyst was fully characterized using Fourier transform infrared spectroscopy, transmission and scanning electron microscopy, X‐ray diffraction and vibrating sample magnetometry techniques, and then the catalytic activity of this catalyst was investigated in the synthesis of 1H‐pyrazolo[1,2‐b]phthalazine‐5,10‐dione derivatives. Also, Ni_0.5Zn_0.5Fe₂O₄@HAP‐Cs₂CO₃ could be reused at least five times without significant loss of activity and could be recovered easily by applying an external magnet. Thus, the developed nanomagnetic catalyst is potentially useful for the green and economic production of organic compounds. Copyright © 2015 John Wiley & Sons, Ltd.     

CuFe2O4 magnetic heterogeneous nanocatalyst: Low power sonochemical-coprecipitation preparation and applications in synthesis of 4H-chromene-3-carbonitrile scaffolds

The paper presents the synthesis and catalytic activity of CuFe₂O₄ nanoparticles. The CuFe₂O₄ nanoparticles have been prepared by sonochemical route under low power ultrasonic irradiation (UI) and using silent stirring at room temperature only (ST) along with co-precipitation method, without using any additive/capping agent. The synthesized magnetic nanoparticles were successfully used and compared for the synthesis of 4H-chromene-3-carbonitrile derivatives. The CuFe₂O₄ nanoparticles obtained by sonochemical route exhibit higher catalytic activity because of small size (0.5–5 nm), high surface area (214.55 m²/g), high thermal stability up to 700 °C, recyclability and reusability due to its magnetic characteristics than CuFe₂O₄ nanoparticles obtained by room temperature silent stirring. The synthesized CuFe₂O₄ nanoparticles were characterized by FT-IR, SEM–EDX, HR-TEM, XRD, TGA/DTA/DTG, BET, VSM techniques. The present method is of great interest due to its salient features such as environmentally compatible, efficient, short reaction time, chemoselectivity, high yield, cheap, moisture insensitive, green and recyclable catalyst which make it sustainable protocol.     

Metabolomics techniques applied in the investigation of phenolic acids from the agro-industrial by-product of Carapa guianensis Aubl

Processing of Carapa guianensis seeds to obtain oil on an industrial scale generates a significant amount of by-product, approximately 66% w/w, which is called cake and is a potential source of biomolecules, including simple phenolic structures. For this reason, studies were carried out on the chemical profiles of hydrolyzed extract from this agro-industrial by-product through High Performance Thin-Layer Chromatography (HPTLC) and Gas Chromatography coupled to Mass Spectrometry (GC–MS). These techniques were used to detect metabolic classes and/or groups, and to identify, for the first time, thirteen simple phenolic acids in this by-product. The sample antioxidant capacity was determined by methods of 2,2-diphenyl-1-picrylhydrazyl (DPPH)and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS⁺) radicals direct sequestration. The hydrolyzed fraction showed a total of 63.47% in the relative abundance of the total of compounds, standing out: p-hydroxybenzoic acid (39.19%) and protocatechuic acid (3,4-dihydroxybenzoic acid) (5.62%), both from hydroxybenzoic acids and 3-(3,4-dihydroxyphenyl)lactic acid, (7.76%) hydroxycinnamic acids derivatives. In these results, the fraction rich in simple phenolic acids was obtained, attributing the prominent behavior of this matrix antioxidant activity, expressed by (IC₅₀: of 16.42 µg/mL and 6.52 µg/mL for DPPH and ABTS⁺ radicals, respectively). The research demonstrated an alternative to applicability that involves sustainability from agro-industrial. These techniques were used to detect metabolic classes and/or groups, and to identify, for the first time, thirteen simple phenolic acids in this by-product, generating a process capable of converting biomass into a bioproduct, consisting of bioactive compounds, in addition to adding value to the industrial chain.     

Finding any given 2‐factor in sparse pseudorandom graphs efficiently

Given an $n$‐vertex pseudorandom graph $G$ and an $n$‐vertex graph $H$ with maximum degree at most two, we wish to find a copy of $H$ in $G$, that is, an embedding $\phi :V\left(H\right)\to V\left(G\right)$ so that $\phi \left(u\right)\phi \left(v\right)\in E\left(G\right)$ for all $uv\in E\left(H\right)$. Particular instances of this problem include finding a triangle‐factor and finding a Hamilton cycle in $G$. Here, we provide a deterministic polynomial time algorithm that finds a given $H$ in any suitably pseudorandom graph $G$. The pseudorandom graphs we consider are $\left(p,\lambda \right)$‐bijumbled graphs of minimum degree which is a constant proportion of the average degree, that is, $\mathrm{\Omega }\left(pn\right)$. A $\left(p,\lambda \right)$‐bijumbled graph is characterised through the discrepancy property: $|e\left(A,B\right)?p|A||B||<\lambda \sqrt{|A||B|}$ for any two sets of vertices $A$ and $B$. Our condition $\lambda =O(p^{2}n/\log n)$ on bijumbledness is within a log factor from being tight and provides a positive answer to a recent question of Nenadov. We combine novel variants of the absorption‐reservoir method, a powerful tool from extremal graph theory and random graphs. Our approach builds on our previous work, incorporating the work of Nenadov, together with additional ideas and simplifications.     

Sentinel-2卫星的多光谱轻量级船舶目标检测算法

近年来深度卷积神经网络在可见光船舶检测方面取得了显著的进展，然而，大多数相关研究是通过改进大型的网络结构来提高检测性能，因此加大了对更高计算机性能的需求。此外，可见光图像难以在云、雾、海杂波、黑夜等复杂场景检测到船舶。针对以上问题，提出了一种融合红（red, R）、绿（green, G）、蓝（blue, B）和近红外（NIR）4个波段光谱信息的由粗到精细的轻量型船舶检测算法。与现有的方法中根据光谱特性利用水体检测算法提取水体区域不同之处是该算法是利用改进的水体检测算法来提取船舶候选区域。为获取更准确的候选区域，对船舶、厚云、薄云、平静海面、杂波海面5种场景中4个波段的像素值进行了统计分析，选取近红外大于阈值作为辅助判断，并以其中心点获取候选区域32×32大小的切片，并对切片进行非极大值抑制，由此获得了船舶粗检测结果。随后构建了轻量级LSGFNet网络对船舶候选区域切片进行精细识别。构建的网络融合了1×1卷积提取的波谱特征与3×3的提取几何特征，为防止光谱特征与几何特征的信息在融合时“信息不流通”，在LSGFNet网络中引入了ShuffleNet中的通道打乱机制，并减小了模型结构，与典型的轻量级网络相比具有更好的效果且模型较小。最后，利用Sentinel-2卫星多光谱10 m分辨率数据构建了512×512大小的1 120组数据进行粗检测，以及32×32大小的6 014组数据进行精细网络训练，其中候选区域粗提取的查全率为98.99%，精细识别网络精确度为96.04%，不同场景下的平均精确度为92.98%。实验表明该算法在抑制云层、海浪杂波等干扰的复杂背景下具有较高的检测效率，且训练时间短、计算机性能需求低。     

Highly dispersed palladium nanoclusters incorporated in amino‐functionalized silica spheres for the selective hydrogenation of succinic acid to γ‐butyrolactone

Highly dispersed palladium nanoclusters incorporated on amino‐functionalized silica sphere surfaces (Pd/SiO₂‐NH₂) were fabricated by a simple one‐pot synthesis utilizing 3‐(2‐aminoethylamino)propyltrimethoxysilane (AAPTS) as coordinating agent. Uniform palladium nanoclusters with an average size of 1.1 nm can be obtained during the co‐condensation of tetraethyl orthosilicate and AAPTS owing to the strong interaction between palladium species and amino groups in AAPTS. The palladium particle size can be controlled by addition of AAPTS and plays a significant role in the catalytic performance. The Pd/SiO₂‐NH₂ catalyst exhibits high catalytic activity for succinic acid hydrogenation with 100% conversion and 94% selectivity towards γ‐butyrolactone using 1,4‐dioxane as solvent at 240°C and 60 bar for 4 h. Moreover, the Pd/SiO₂‐NH₂ catalyst is robust and readily reusable without loss of its catalytic activity. Copyright © 2015 John Wiley & Sons, Ltd.     

Computational and dynamic NMR investigation of 2,2-dimesityl-1,1,1,3,3,3-hexamethyltrisilane

The structure and rotational barrier for the mesityl-silicon bond of 2,2-dimesityl-1,1,1,3,3,3-hexamethyltrisilane have been investigated by ¹H- and ¹³C-variable temperature nuclear magnetic resonance (NMR) as well as by density functional theory structural calculations. The calculations show that the lowest energy structure has C₂ symmetry with nonequivalent ortho methyl groups, consistent with the crystal structure and solution NMR. The nonequivalent ortho methyl groups exchange through a C_s transition state with a calculated relative free energy of 11.0 kcal mol⁻¹. The barrier for this rotation found by dynamic NMR is 13.4 ± 0.2 kcal mol⁻¹ at 298 K.     

Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study

Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.