Design consideration and modelling studies of ultrasound and ultraviolet combined approach for shelf-life enhancement of pine apple juice

Although both ultraviolet (UV) radiation and ultrasound (US) treatment have their capabilities in microbial inactivation, applying any one method alone may require a high dose for complete inactivation, which may affect the sensory and nutritional properties of pineapple juice. Hence, this study was intended to analyse and optimise the effect of combined US and UV treatments on microbial inactivation without affecting the selected quality parameters of pineapple juice. US treatment (33 kHz) was done at three different time intervals, viz. 10 min, 20 min and 30 min., after which, juice samples were subjected to UV treatment for 10 min at three UV dosage levels, viz. 1 J/cm², 1.3 J/cm², and 1.6 J/cm². The samples were evaluated for total colour difference, pH, total soluble solids (TSS), titrable acidity (TA), and ascorbic acid content; total bacterial count and total yeast count; and the standardization of process parameters was done using Response Surface Methodology and Artificial Neural Network. The results showed that the individual, as well as combined treatments, did not significantly impact the physicochemical properties while retaining the quality characteristics. It was observed that combined treatment resulted in 5 log cycle reduction in bacterial and yeast populations while the individual treatment failed. From the optimization studies, it was found that combined US and UV treatments with 22.95 min and1.577 J/cm² ensured a microbiologically safe product while retaining organoleptic quality close to that of fresh juice.     

The covalent functionalization of few-layered MoTe2 thin films with iodonium salts

Covalent functionalization of 2D materials provides a tailored approach towards tuning of their chemical, optical, and electronic properties making the search for new ways to graft small molecules important. Herein, the reaction with (3,5-bis(trifluoromethyl)phenyl)iodonium salt is revealed as an effective strategy for functionalization of MoTe₂ thin films. Upon decomposition of the salt, the generated radicals graft covalently as aryl-(CF₃)₂ groups at the surface of both metallic (1T’) and semiconducting (2H) polymorphs of MoTe₂. Remarkably, the reactivity of the salt is governed by the electronic structure of the given polymorph. While the functionalization of the metallic MoTe₂ occurs spontaneously, the semiconducting MoTe₂ requires activation by light. The reaction proceeds with the elimination of oxide from the original films yielding the functionalized products that remain protected in ambient conditions, presenting a viable solution to the ageing of MoTe₂ in air.     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Design,synthesis and evaluation of novel dehydroabietic acid-dithiocarbamate hybrids as potential multi-targeted compounds for tumor cytotoxicity

In the present study, novel representatives of the important group of biologically-active, dehydroabietic acid-bearing dithiocarbamate moiety, were synthesized and characterized by ¹H NMR, ¹³C NMR, HR-MS. The in vitro antiproliferative activity evaluation (MTT) indicated that these compounds exhibited potent inhibitory activities in various cancer cell lines (HepG-2, MCF-7, HeLa, T-24, MGC-803). Particularly, compound III-b possessed extraordinary cytotoxicity with low micromolar IC₅₀ values ranging from 4.07 to 38.84 µM against tested cancer cell lines, while displayed weak cytotoxicity on two normal cell lines (LO-2 and HEK 293 T). Subsequently, the potential mechanisms of representative compound III-b were elementarily investigated by Transwell experiment, which showed III-b can inhibit cancer cells migration. Annexin-V/PI dual staining showed that the compound can induce HepG-2 cells apoptosis in a dose-dependent manner. Meanwhile this apoptosis may be related to the upregulated protein expression of cleaved-caspase 3, cleaved-caspase 9, Bax and downregulated of Bcl-2 indicated by Western Blot. Later study further confirmed that ROS levels in HepG-2 cells increased significantly with the rise of concentrations. In addition, through the network pharmacology data analyzing, the core targets and signaling pathways of compound III-b for treatment of liver neoplasms were forecasted. Molecular docking model showed that compound III-b had high affinity with hub targets (CASP3, EGFR, HSP90AA1, MAPK1, ERBB2, MDM2), suggesting that compound III-b might target the hub protein to modulate signaling activity. Taken together, these data indicated that dehydroabietic acid structural modification following the “Molecular hybridization” principle is a feasible way to discover the potential multi-targeted antitumor compounds.     

Regulating Phase Junction and Oxygen Vacancies of TiO2 Nanoarrays for Boosted Photoelectrochemical Water Oxidation

In this study, we have provided a facile solution to synthesize well-aligned titanium dioxide nanorods by using hydrothermal reaction. By calcining the materials under different atmospheres and temperatures, a batch of titanium dioxides with excellent oxygen evolution reaction(OER) catalytic efficiency were obtained. This new structured TiO₂ photoanode material yields a high photocurrent density of 5.69 mA/cm² at 1.23 V vs. reversible hydrogen electrode(RHE) under simulated solar light(100 mW/cm²). Surface photovoltage techniques and other measurements were carried out to confirm that the enhanced photoelectrochemical performances were attributed to the synergistic effect of the phase junction and a certain content of surface states, which accelerate the separation and transmission of the photogenerated charges. This material with phase junction and surface states promises a potential application in the field of photoelectric catalysis under solar light.     

Diffusive search with spatially dependent resetting

We consider a stochastic search model with resetting for an unknown stationary target $a\in \mathbb{R}$ with known distribution $\mu$. The searcher begins at the origin and performs Brownian motion with diffusion constant $D$. The searcher is also armed with an exponential clock with spatially dependent rate $r=r\left(\cdot \right)$, so that if it has failed to locate the target by the time the clock rings, then its position is reset to the origin and it continues its search anew from there. Denote the position of the searcher at time $t$ by $X\left(t\right)$. Let $E_0^{\left(r\right)}$ denote expectations for the process $X\left(\cdot \right)$. The search ends at time $T_a=inf\{t\ge 0:X\left(t\right)=a\}$. The expected time of the search is then ${\int }_{\mathbb{R}}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$. Ideally, one would like to minimize this over all resetting rates $r$. We obtain quantitative growth rates for $E_0^{\left(r\right)}{T}_a$ as a function of $a$ in terms of the asymptotic behavior of the rate function $r$, and also a rather precise dichotomy on the asymptotic behavior of the resetting function $r$ to determine whether $E_0^{\left(r\right)}{T}_a$ is finite or infinite. We show generically that if $r\left(x\right)$ is of the order ${\left|x\right|}^{2l}$, with $l>-1$, then $log{E}_0^{\left(r\right)}{T}_a$ is of the order ${\left|a\right|}^{l+1}$; in particular, the smaller the asymptotic size of $r$, the smaller the asymptotic growth rate of $E_0^{\left(r\right)}{T}_a$. The asymptotic growth rate of $E_0^{\left(r\right)}{T}_a$ continues to decrease when $r\left(x\right)\sim \frac{D\lambda }{x^2}$ with $\lambda >1$; now the growth rate of $E_0^{\left(r\right)}{T}_a$ is more or less of the order ${\left|a\right|}^{\frac{1+\sqrt{1+8\lambda }}{2}}$. Note that this exponent increases to $\infty$ when $\lambda$ increases to $\infty$ and decreases to 2 when $\lambda$ decreases to 1. However, if $\lambda =1$, then $E_0^{\left(r\right)}{T}_a=\infty$, for $a\ne 0$. Our results suggest that for many distributions $\mu$ supported on all of $\mathbb{R}$, a near optimal (or optimal) choice of resetting function $r$ in order to minimize ${\int }_{{\mathbb{R}}^d}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$ will be one which decays quadratically as $\frac{D\lambda }{x^2}$ for some $\lambda >1$. We also give explicit, albeit rather complicated, variational formulas for ${inf}_{r\gneqq 0}{\int }_{{\mathbb{R}}^d}\left(E_0^{\left(r\right)}{T}_a\right)\mu \left(da\right)$. For distributions $\mu$ with compact support, one should set $r=\infty$ off of the support. We also discuss this case.     

铋化物发光玻璃中银表面等离激元对铒离子的发光增强作用

局域表面等离激元可以由自由空间的光直接激发,这也是局域表面等离激元的优点所在。研究铋化物发光玻璃中纳米银颗粒的表面等离激元对铒离子发光的增强效应、进一步的提高铋化物发光玻璃中铒离子的发光性能很有意义。首先,测量了(A)Er 3+(0.5%)Ag(0.5%):铋化物发光玻璃与(B)Er 3+(0.5%):铋化物发光玻璃样品的吸收谱,发现(A)Er 3+(0.5%)Ag(0.5%):铋化物发光玻璃在约600.0 nm处有一个较弱的宽的银表面等离激元共振吸收峰。同时发现两者都有典型的铒离子的吸收峰,它们的吸收几乎完全一样:在波峰形状、峰值强度和峰值波长等方面都很相近。测量了(A)Er 3+(0.5%)Ag(0.5%):铋化物发光玻璃和(B)Er 3+(0.5%):铋化物发光玻璃样品的激发谱,发现有位于379.0,406.0,451.0,488.0和520.5 nm的5个550.0 nm可见光的可见激发谱峰,和位于379.0,406.5,451.0,488.5,520.5,544.0,651.5和798.0 nm的8个1531.0 nm红外光的红外激发谱峰,容易指认出依次为Er 3+的4I 15/2→4G 11/2,4I 15/2→2H 9/2,4I 15/2→(4F 3/2,4F 5/2),4I 15/2→4F 7/2,4I 15/2→2H 11/2,4I 15/2→4S 3/2,4I 15/2→4F 9/2和4I 15/2→4I 9/2跃迁的吸收峰,通过测量发现(A)Er 3+(0.5%)Ag(0.5%):铋化物发光玻璃相对于(B)Er 3+(0.5%):铋化物发光玻璃样品的可见和红外激发谱的最大增强依次分别是238%和133%。最后,测量了它们的发光谱,发现有位于534.0,547.5和658.5 nm的三组可见发光峰,容易指认出依次为Er 3+的2H 11/2→4I 15/2,4S 3/2→4I 15/2,4F 9/2→4I 15/2荧光跃迁。还发现红外发光峰位于978.0和1531.0 nm,依次为Er 3+的4I 11/2→4I 15/2和4I 13/2→4I 15/2的荧光跃迁。通过测量发现(A)Er 3+(0.5%)Ag(0.5%):铋化物发光玻璃相对于(B)Er 3+(0.5%):铋化物发光玻璃样品的可见和红外发光谱的最大增强依次分别是215%和138%。对于银表面等离激元增强铒离子发光的机理,认为主要为纳米银颗粒的局域表面等离激元共振,造成金属纳米结构附近产生的局域电场的强度要远大于入射光的电场强度,从而导致了金属纳米结构对入射光产生强烈的吸收和散射,进而导致了荧光的增强;即局域表面等离子体共振局域场的场增强效应。     

考虑地表反射类型的气溶胶散射偏振特性

采用逐次阶散射法求解矢量辐射传输方程来研究气溶胶在不同地表反射模型下的散射偏振特性.首先,选取单一地表反射模型和耦合地表反射模型两种地表反射模型.然后,根据地表反射模型计算得到相应的地表反射率,进而采用逐次阶散射法对矢量辐射传输方程进行求解,得到散射光的Stokes矢量.最后,由Stokes矢量计算得出散射光的偏振度.仿真结果表明,两种地表反射模型下气溶胶单次散射的散射辐射强度和线偏振度均相等;耦合地表反射模型的总散射辐射强度和线偏振度总是大于单一地表反射模型;单一地表反射模型的气溶胶单次散射相对总散射的贡献总是大于耦合地表反射模型.研究结果对气溶胶光学特性的反演具有一定意义.