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Internal solitary waves are very common physical phenomena in the ocean, which play an important role in the transport of marine matter, momentum and energy. The non-linear Schrodinger equation is suitable for describing the deep-sea internal wave propagation. Firstly, by designing skillfully, the trial-Lagrange functional, variational principles are successfully established for the non-linear Schrodinger equation by the semi-inverse method. Secondly, the constructed var-iational principle is proved by minimizing the functionals with the calculus of variations. Finally, different kinds of internal solitary waves are obtained by the semi-inverse variational principle for the non-linear Schrodinger equation.

It is an important and difficult inverse problem to construct variational principles from complex models directly, because their variational formulations are theoretical bases for many methods to solve or analyze the non-linear problems. At first, this paper extends two kinds of non-linear geophysical KdV equations in continuum mechanics to their fractional partners in fractal porous media or with irregular boundaries. Then, by designing skillfully, the trial-Lagrange functional, variational principles are successfully established for the non-linear geophysical KdV equation with Coriolis term, and the high-order extended KdV equation with fractal derivatives, respectively. Furthermore, the obtained variational principles are proved to be correct by minimizing the functionals with the calculus of variations.

This paper extends the (2+1)-dimensional Eckhaus-type dispersive long wave equations in continuous medium to their fractional partner, which is a model of non-linear waves in fractal porous media. The derivation is shown briefly using He?s fractional derivative. Using the semi-inverse method, the variational principles are established for the fractional system, which up to now are not discovered. The obtained fractal variational principles are proved correct by minimizing the functional with the calculus of variations, and might find potential applications in numerical modeling.

Ulcerative colitis, a kind of inflammatory bowel disease (IBD), is caused by dysregulated immune response of intestinal bacteria. This chronic disorder can lead to a deficiency of O

Ulcerative colitis is a prevalent inflammatory disease caused by the intestinal bacterial infection. And it is related to the hypoxic degrees in the colon microenvironment. Hypoxia, a condition of imbalance in O

Mitophagy, a mitochondria-selective autophagy process, plays critical roles in maintaining intracellular homeostasis by removing the damaged mitochondria and recycling the nutrients in a lysosome-dependent manner. Mitophagy process could result in the changes of mitochondrial pH. So fluorescent probes for detecting mitochondrial pH during mitophagy are highly needed for exploring the functions of mitochondria. Herein, a series of near-infrared pH probes were designed based on the rhodamine framework. The probes showed high sensitivity for pH with the tunable pKa from 4.74 to 6.54. Particularly, for probe 5 (with the pKa of 6.54), a linear relationship between fluorescence intensity and pH in the range of 5.6-7.2 was observed, which was suitable for mitochondrial pH detection. The probe displayed excellent mitochondria-targeting ability. It was applied to monitor pH changes during mitophagy caused by starvation. Besides, in vivo non-invasive visualization of tumor pH variations was achieved via the fluorescence imaging in the near-infrared region. We anticipate that the probe may be a useful tool for revealing essential information about mitophagy-related research and clinical tumor diagnosis.

In this work, a multifunctional microporous metal–organic framework (MOF), [Cu2(BPDC)2(H2O)2]·5.6H2O·DMA (1, BPDC = 5,5′-dicarboxylate-3,3′-dipyridine anion and DMA = dimethylacetamide), has been synthesized based on the ligand BPDC under solvothermal conditions. Single crystal X-ray analysis reveals that it possesses a non-interpenetrating binodal (4,4)-connected three-dimensional PtS-type network with the Schlafli point symbol of {42·84}. Remarkably, the activated 1 (1a) with dual functionalities of open metal sites (OMSs) and O-rich Lewis basic sites (LBSs) exhibits excellent CO2 adsorption (193 cm3 g−1 at 298 K) and high-effect separation ability (41.5 for CO2/N2 = 15/85 and 9.7 for CO2/CH4 = 5/95 under 1 bar at 298 K). Additionally, 1a exhibits impressive performance for I2 sorption and release in solvents.

The variation of polar vortex intensity is a significant factor affecting the atmospheric conditions and weather in the Northern Hemisphere (NH) and even the world. However, previous studies on the prediction of polar vortex intensity are insufficient. This paper establishes a deep learning (DL) model for multi-day and long-time intensity prediction of the polar vortex. Focusing on the winter period with the strongest polar vortex intensity, geopotential height (GPH) data of NCEP from 1948 to 2020 at 50 hPa are used to construct the dataset of polar vortex anomaly distribution images and polar vortex intensity time series. Then, we propose a new convolution neural network with long short-term memory based on Gaussian smoothing (GSCNN-LSTM) model which can not only accurately predict the variation characteristics of polar vortex intensity from day to day, but also can produce a skillful forecast for lead times of up to 20 days. Moreover, the innovative GSCNN-LSTM model has better stability and skillful correlation prediction than the traditional and some advanced spatiotemporal sequence prediction models. The accuracy of the model suggests important implications that DL methods have good applicability in forecasting the nonlinear system and vortex spatial–temporal characteristics variation in the atmosphere.

Cyanide (CN

Mitochondria are the powerhouses in cells, providing the energy needed for cellular activities. However, the abnormalities in the mitochondrial microenvironment (e.g., the increased viscosity) can lead to mitochondrial dysfunctions and diseases. Herein, we develop a series of near-infrared (NIR) fluorescence probes for the detection of viscosity. After screening, probe CQ-4 is selected since it shows a great fluorescence enhancement (89-fold) in the NIR window. Its specific response to viscosity is not influenced by pH, polarity and biological species. Under stimulation with monensin or nystatin, CQ-4 can measure the cellular viscosity changes with good biocompatibility. In addition, we can observe an increase of viscosity during starvation. CQ-4 is applied to distinguish cancer cells from normal cells based on the viscosity differences. Furthermore, the probe has been successfully applied to image viscosity in inflamed and tumor-bearing mice in vivo. Therefore, CQ-4 may contribute to the future study about viscosity in the physiological and pathological processes.

The intensity variation of the South Asian high (SAH) plays an important role in the formation and extinction of many kinds of mesoscale systems, including tropical cyclones, southwest vortices in the Asian summer monsoon (ASM) region, and the precipitation in the whole Asia Europe region, and the SAH has a vortex symmetrical structure, its dynamic field also has the symmetry form. Not enough previous studies focus on the variation of SAH daily intensity. The purpose of this study is to establish a day-to-day prediction model of the SAH intensity, which can accurately predict not only the interannual variation but also the day-to-day variation of the SAH. Focusing on the summer period when the SAH is the strongest, this paper selects the geopotential height data between 1948 and 2020 from NCEP to construct the SAH intensity datasets. Compared with the classical deep learning methods of various kinds of efficient time series prediction model, we ultimately combine the Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) method, which has the ability to deal with the nonlinear and unstable single system, with the Permutation Entropy (PE) method, which can extract the SAH intensity feature of IMF decomposed by CEEMDAN, and the Convolution-based Gated Recurrent Neural Network (ConvGRU) model is used to train, test, and predict the intensity of the SAH. The prediction results show that the combination of CEEMDAN and ConvGRU can have a higher accuracy and more stable prediction ability than the traditional deep learning model. After removing the redundant features in the time series, the prediction accuracy of the SAH intensity is higher than that of the classical model, which proves that the method has good applicability for the prediction of nonlinear systems in the atmosphere.

With the continuous development of China’s economy, the problems of pollutant emissions and environmental governance are gradually emerging. Based on the monthly data of man-made emission sources in Asia from the 2008 East Asia MIX emission inventory, this study analyzed the temporal and spatial distribution characteristics of air pollutants including PM2.5, PM10, CO, CO2, NOx, OC, etc., and explored the difference and variation law of material concentration distribution between designated special regions, as well as the possible impact of various atmospheric systems on them. Firstly, in most areas of China, the distribution of pollutants has obvious temporal and spatial differences, and the overall trend of pollutant concentration is higher in the north than in the south. The results show that the monthly variation trend of pollutants in India is significantly correlated with that in China. However, compared with the monthly trend in northern China, it is not particularly obvious.

Nitroreductase (NTR) is a highly expressed endogenous enzyme in hypoxic tumor cells, which is associated with the hypoxic degree in tumors. Therefore, it is particularly important to develop low-toxicity and high-sensitivity fluorescent probes for NTR. Herein, we report an NTR-activated near-infrared probe with good selectivity and sensitivity. More importantly, the background fluorescence signal is effectively reduced due to the quenching effect of nitro group as well as the spironolactone (ring-closed) form of rhodamine moiety. Upon reaction with NTR, the probe exhibits a remarkable fluorescence off-on response at 740 nm (about 32-fold intensity enhancement), with an extremely low detection limit of 1.09 ng/mL. Moreover, the probe is able to target mitochondria. With this probe, we have achieved the visualization of NTR overexpression in hypoxic cancer cells, as well as in hypoxic tumors in vivo as revealed in the tumor-bearing mouse model. By using this probe, some essential information may be revealed about hypoxia-relevant diseases.

The various studies of partial differential equations (PDEs) are hot topics of mathematical research. Among them, solving PDEs is a very important and difficult task. Since many partial differential equations do not have analytical solutions, numerical methods are widely used to solve PDEs. Although numerical methods have been widely used with good performance, researchers are still searching for new methods for solving partial differential equations. In recent years, deep learning has achieved great success in many fields, such as image classification and natural language processing. Studies have shown that deep neural networks have powerful function-fitting capabilities and have great potential in the study of partial differential equations. In this paper, we introduce an improved Physics Informed Neural Network (PINN) for solving partial differential equations. PINN takes the physical information that is contained in partial differential equations as a regularization term, which improves the performance of neural networks. In this study, we use the method to study the wave equation, the KdV&ndash, Burgers equation, and the KdV equation. The experimental results show that PINN is effective in solving partial differential equations and deserves further research.

El Niño is an important quasi-cyclical climate phenomenon that can have a significant impact on ecosystems and societies. Due to the chaotic nature of the atmosphere and ocean systems, traditional methods (such as statistical methods) are difficult to provide accurate El Niño index predictions. The latest research shows that Ensemble Empirical Mode Decomposition (EEMD) is suitable for analyzing non-linear and non-stationary signal sequences, Convolutional Neural Network (CNN) is good at local feature extraction, and Recurrent Neural Network (RNN) can capture the overall information of the sequence. As a special RNN, Long Short-Term Memory (LSTM) has significant advantages in processing and predicting long, complex time series. In this paper, to predict the El Niño index more accurately, we propose a new hybrid neural network model, EEMD-CNN-LSTM, which combines EEMD, CNN, and LSTM. In this hybrid model, the original El Niño index sequence is first decomposed into several Intrinsic Mode Functions (IMFs) using the EEMD method. Next, we filter the IMFs by setting a threshold, and we use the filtered IMFs to reconstruct the new El Niño data. The reconstructed time series then serves as input data for CNN and LSTM. The above data preprocessing method, which first decomposes the time series and then reconstructs the time series, uses the idea of symmetry. With this symmetric operation, we extract valid information about the time series and then make predictions based on the reconstructed time series. To evaluate the performance of the EEMD-CNN-LSTM model, the proposed model is compared with four methods including the traditional statistical model, machine learning model, and other deep neural network models. The experimental results show that the prediction results of EEMD-CNN-LSTM are not only more accurate but also more stable and reliable than the general neural network model.

It is a very important but difficult task to seek explicit variational formulations for nonlinear and complex models because variational principles are theoretical bases for many methods to solve or analyze the nonlinear problem. By designing skillfully the trial-Lagrange functional, different groups of variational principles are successfully constructed for two kinds of coupled nonlinear equations in shallow water, i.e., the Broer-Kaup equations and the (2+1)-dimensional dispersive long-wave equations, respectively. Both of them contain many kinds of soliton solutions, which are always symmetric or anti-symmetric in space. Subsequently, the obtained variational principles are proved to be correct by minimizing the functionals with the calculus of variations. The established variational principles are firstly discovered, which can help to study the symmetries and find conserved quantities for the equations considered, and might find lots of applications in numerical simulation.

In this paper, a frequently employed technique named the sparsity-promoting dynamic mode decomposition (SPDMD) is proposed to analyze the velocity fields of atmospheric motion. The dynamic mode decomposition method (DMD) is an effective technique to extract dynamic information from flow fields that is generated from direct experiment measurements or numerical simulation and has been broadly employed to study the dynamics of the flow, to achieve a reduced-order model (ROM) of the complex high dimensional flow field, and even to predict the evolution of the flow in a short time in the future. However, for standard DMD, it is hard to determine which modes are the most physically relevant, unlike the proper orthogonal decomposition (POD) method which ranks the decomposed modes according to their energy content. The advanced modal decomposition method SPDMD is a variant of the standard DMD, which is capable of determining the modes that can be used to achieve a high-quality approximation of the given field. It is novel to introduce the SPDMD to analyze the atmospheric flow field. In this study, SPDMD is applied to extract essential dynamic information from the 200 hPa jet flow, and the decomposed results are compared with the POD method. To further demonstrate the extraction effect of POD/SPDMD methods on the 200 hPa jet flow characteristics, the POD/SPDMD reduced-order models are constructed, respectively. The results show that both modal decomposition methods successfully extract the underlying coherent structures from the 200 hPa jet flow. And the DMD method provides additional information on the modal properties, such as temporal frequency and growth rate of each mode which can be used to identify the stability of the modes. It is also found that a fewer order of modes determined by the SPDMD method can capture nearly the same dynamic information of the jet flow as the POD method. Furthermore, from the quantitative comparisons between the POD and SPDMD reduced-order models, the latter provides a higher precision than the former, especially when the number of modes is small.

In this study, we report a fluorescent probe (CBT) based on coumarin and benzothiazole moieties for detecting SO2 derivatives (HSO3−/SO32−) in a ratiometric fluorescence manner. Probe CBT exhibited desirable properties such as a high specificity, a rapid response, good water solubility and a low detection limit. The Michael addition reaction was proved to be the sensing mechanism of CBT. Moreover, fluorescence imaging of cells indicated that probe CBT with low cytotoxicity can be used to monitor the endogenous SO2 derivatives in pathological liver cells (HepG2) but not in the normal liver cells (L-02), indicating that probe CBT can be applied to distinguish the two kinds of cells. Fluorescence co-localization studies proved that this probe shows an excellent mitochondria-targeting activity. Therefore, probe CBT has great potential to be applied in exploring the role of the SO2 derivatives in biology.

Polar vortex is an important weather system that affects the atmospheric circulation in the Northern Hemisphere and the climate change in the Arctic. The intensity variation of polar vortex is related to El Nino-Southern Oscillation (ENSO), Arctic Oscillation (AO) and many other climate phenomena. However, there are few researches on the prediction of polar vortex intensity change, our study analyzes and predicts the intensity variation of the Northern Hemisphere stratospheric polar vortex, and further uses convolution smoothing and depth learning methods to improve the accuracy of the prediction. The result shows that the long-short time memory network method’s prediction accuracy is not enough high. After the convolution smoothing of the time series of intensity signal, the prediction accuracy of neural network has been significantly improved. The average absolute error of the traditional long short-term memory network method is 18.29, while the average absolute error of the smoothed prediction intensity and the actual intensity is 13.77. In addition, the correlation between the predicted results and the real values is also as high as 0.9981.

Heat shock is a potentially fatal condition characterized by high body temperature (>40 °C), which may lead to physical discomfort and dysfunctions of organ systems. Acidic pH environment in lysosomes can activate enzymes, thus facilitating the degradation of proteins in cellular metabolism. Owing to the lack of a practical research tool, it remains difficult to exploit relationship between heat shock and lysosome. Herein, a NIR lysosomal pH chemosensor (NRLH) was developed. One typical lysosome-locating group, morpholine, was incorporated into NRLH. The fluorescence intensity showed pH-dependent characteristics and responded sensitively to pH fluctuations in the pH range of 3.0–5.5. NRLH with a pKa of 4.24 displayed rapid response and high selectivity for H+ among common species. We also demonstrated NRLH was capable of targeting lysosomes. Importantly, NRLH was applied in cellular imaging and the data revealed that lysosomal pH increased but never decreased during the heat shock. Therefore, NRLH may act as an effective molecular tool for exploring the mechanisms of heat-related pathology in bio-systems.

In this paper, ratiometric imaging of lysosomal HOCl was realized with a molecular probe (CR-Ly) based on fluorescence resonance energy transfer by using coumarin as the donor and rhodamine as acceptor. CR-Ly showed high sensitivity and fast response to HOCl. Moreover, CR-Ly exhibited excellent selectivity and sensitivity for HOCl over other biologically relevant species. Furthermore, it was successfully utilized to image the endogenous HOCl with low cytotoxity. And CR-Ly was capable of targeting lysosomes and monitoring lysosomal hypochlorous acid changes owing to the presence of the morpholine moiety. We believe that probe CR-Ly would be helpful to further research on the HOCl-associated diseases in lysosomes.

This paper extends the [Formula: see text]-dimensional Broer–Kaup equations in continuum mechanics to its fractional partner, which can model a lot of nonlinear waves in fractal porous media. Its derivation is demonstrated in detail by applying He’s fractional derivative. Using the semi-inverse method, two variational principles are established for the nonlinear coupled equations, which up to now are not discovered. The variational formulations can help to study the symmetries and find conserved quantities in the fractal space. The obtained variational principles are proved correct by minimizing the functionals with the calculus of variations, and might find potential applications in numerical simulation. The procedure reveals that the semi-inverse method is highly efficient and powerful, and can be generalized to other nonlinear evolution equations with fractal derivatives.

A new pH-activatable ratiometric fluorescent probe (RhMP) has been developed, in which an imidazo[1,5-a]pyridine fluorophore as a fluorescence resonance energy transfer (FRET) donor linked to a rhodamine B fluorophore as a FRET acceptor. The simultaneous fluorescence intensity enhancement of imidazo[1,5-a]pyridine and rhodamine B moieties along with the decrease of pH value should result from the integration of ICT and FRET processes. It's the first time a ratiometric fluorescent probe based on FRET system using imidazo[1,5-a]pyridine derivative as a fluorophore donor has been reported. At pKa = 4.96, the fluorescence intensity ratio (I476.5/I577.5) of the probe displayed excellent pH-dependent performance and responded linearly to minor pH changes in the range of 4.0–5.8. The probe exhibited excellent selectivity among different metal cations and brilliant reversibility. In addition, RhMP has low cytotoxicity and has been successfully applied in HeLa cells. The fluorescence microscopic images demonstrated this probe could image weak acid pH changes of the lysosome in live cells.

A new imidazo[1,5-a]pyridine-based pH fluorescent probe has been synthesized and characterized. It is the first time that imidazo[1,5-a]pyridine is used as a fluorescent probe. This probe responds to acidic pH with fast response (within 3 min), high selectivity and sensitivity. It has good reversibility and nearly no interference from common metal ions. The probe is suitable for acidic conditions and can quantitatively detect pH value based on the equilibrium equation, pH = pKa − log[(Ia − Ix)/(Ix − Ib)], with a good linear relationship. Moreover, we verified that the protonation of the 2-nitrogen in the imidazole decreases the electron density on the fused ring by 1H NMR analysis and DFT calculation. We proposed that intramolecular charge transfer and solvation of the probe in aqueous solutions might be the mechanism of the fluorescence enhancement under strongly acidic conditions.

Oral colon targeted drug delivery system can be divided into pH dependent, time-dependent, enzymatic degradation etc. according to the ways of drug delivery. Mechanism of drug delivery, preparation method and application of oral colon targeted drug delivery system were introduced. In addition, it previewed the research direction of colon targeted drug delivery in the future, to provide a reference for the targeted new dosage form.

A series of novel imidazo[1,5-a]pyridine-hydrazone derivatives were synthesized and characterized by infrared spectroscopy (IR), 1H NMR, 13C NMR and high resolution mass spectrometer (HRMS). Typically, the spatial structure of compound 3j was determined using X-ray diffraction analysis. The UV–vis absorption and fluorescence spectral characteristics of the compounds in dichloromethane and acetonitrile were investigated. Absorption peaks could be observed in the wavelength range 290–450 nm. It can also be seen that they display very similar maximum emission. The group attached to hydrazone hardly influenced the maximum emission. Furthermore, all the compounds were evaluated for antibacterial activity and were found to be more effective against Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Salmonella typhimurium, Pseudomonas aeruginosa and Shigella compared with chloramphenicol. Copyright © 2013 John Wiley & Sons, Ltd.

Numerical methods for solving initial value problems (IVPs) are of fundamental importance for analyzing and controlling dynamic systems. In this paper, we first present a new Legendre wavelets-Picard iteration method (LWPIM) for solving IVPs. Combining Legendre wavelets method with Picard iteration method, LWPIM iteratively refines estimates of the solutions until the iteration converges and can avoid the solution of a system of algebraic equations. Furthermore, the developed vector-matrix form makes MCPI methods computationally efficient. Numerical results show that the proposed method is mathematically simple and easy to implement while still keeps the high accuracy.

A series of novel 5-aryl-3-benzimidazolyl-1-phenyl-pyrazoline derivatives were synthesized by the reaction of benzimidazolyl chalcone and phenylhydrazine in 41–72% yields. The compounds were characterized using IR, 1 H NMR and HRMS. Absorption and fluorescence spectra were measured in different organic solvent. An intense absorption maxima was noted at ca. 370 nm and emission maxima was noted at ca. 460 nm. The absorption spectra of the pyrazoline derivatives reveal that 5-aryl group attached to the pyrazoline ring hardly influenced the maximum absorption. The fluorescence spectra of these compounds indicated the emission wavelength was red shifted and the fluorescence intensity was decreased with the increase in solvent polarity.

A new ratiometric fluorescent probe based on Forster resonance energy transfer (FRET) for sensing lysosomal pH has been developed. The probe (RMPM) was composed of imidazo[1,5-α]pyridine quaternary ammonium salt fluorophore as the FRET donor and the rhodamine moiety as the FRET acceptor. It’s the first time to report that imidazo[1,5-α]pyridine quaternary ammonium salt acts as the FRET donor. The ratio of fluorescence intensity of the probe at two wavelengths (I424/I581) changed significantly and responded linearly toward minor pH changes in the range of 5.4–6.6. It should be noted that it’s rare to report that a ratiometric pH probe could detect so weak acidic pH with pKa = 6.31. In addition, probe RMPM exhibited excellent water-solubility, fast-response, all-right selectivity and brilliant reversibility. Moreover, RMPM has been successfully applied to sensing lysosomal pH in HeLa cells and has low cytotoxicity.

Novel imidazo[1,5-a]pyridinyl 1,3,4-Oxadiazole derivatives were synthesized and characterised by IR, (1)H NMR and HRMS.UV-vis absorption and fluorescence properties of these compounds in different solutions showed that the maximal emission wavelength was not significantly changed in different solvents; however, maximum absorption wavelength was blue-shifted with the increase of solvent polarity. Absorption λ(max) and emission λ(max) was less correlated with substituent groups on benzene rings. The calculated molecular orbital correlates well with their absorption.

Based on variational adjoint methods, theoretical analyses and numerical experiments are performed for retrievals of two-dimensional winds and related parameters from single-Doppler radar data in polar coordinates. In the method, the reflectivity conservation equation is used as the governing equation and the mass continuity equation as a weak constraint. At the same time, the stable functional of regularization and background field are also introduced in the cost functional. Based on the ideal experiments with artificial data, real two-dimensional wind fields are retrieved with low-altitude data from the Nanjing Doppler Radar Station, and the results are encouraging and promising.

A series of novel 2-acyl-6-aryl substituted indolizine derivatives was synthesized by a novel tandem reaction between 4-acyl-pyrrole-2-carbaldehyde derivatives and ethyl 4-bromo-3-arylbut-2-enoate under mild conditions. The compounds were characterized using IR, 1H NMR 13C NMR and HRMS. The crystal structure of 7a was determined using single crystal X-ray crystallography. The absorption results showed that compounds 7a–e presented their absorption maxima at ca. 270 nm, while compounds 7f and 7g with a larger conjugation system exhibited red-shifted absorption character (ca. 280 nm). Fluorescence spectra revealed that these compounds exhibited blue fluorescence (434–456 nm) in dilute solutions and showed quantum yields of fluorescence between 0.02 and 0.39 in dichloromethane.

A series of novel imidazo[1,5-a]pyridine-hydrazone derivatives were synthesized and characterized by infrared spectroscopy (IR), 1H NMR, 13C NMR and high resolution mass spectrometer (HRMS). Typically, the spatial structure of compound 3j was determined using X-ray diffraction analysis. The UV-vis absorption and fluorescence spectral characteristics of the compounds in dichloromethane and acetonitrile were investigated. Absorption peaks could be observed in the wavelength range 290-450 nm. It can also be seen that they display very similar maximum emission. The group attached to hydrazone hardly influenced the maximum emission. Furthermore, all the compounds were evaluated for antibacterial activity and were found to be more effective against Staphylococcus aureus, Listeria monocytogenes, Escherichia coli, Salmonella typhimurium, Pseudomonas aeruginosa and Shigella compared with chloramphenicol.