Synergistic effect of high-intensity ultrasound and β-cyclodextrin treatments on browning control in apple juice

This work evaluated the synergistic effects of combined high-intensity ultrasound (HIU) with β-cyclodextrin (β-CD) treatments on inhibiting browning of apple juice and explored the mechanism through simulation system. The combined treatment of 300 W HIU with 0.006 g mL⁻¹ β-CD had a synergistic impact on maintaining juice colour, resulting in a 39.06% reduction in browning degree, only a 36.64% decrease in total phenolic content, and a 17.82% reduction in PPO activity. The inhibition of enzymatic browning in simulated system revealed that HIU suppressed the enzyme (Polyphenol oxidase, PPO) and β-CD inhibited enzyme (PPO) and embedded substrate (polyphenol). The results of spectroscopic analysis showed that the particle-size distribution of PPO narrowed, the content of α-helix in the secondary structure increased, the fluorescence intensity increased, and the maximum wavelength was red-shifted after HIU and β-CD treatment. Changes in structure could further result in PPO activity loss. Hence, the combined treatment could synthetically alleviate the browning of apple juice.     

The Antibacterial Drug Candidate SBC3 is a Potent Inhibitor of Bacterial Thioredoxin Reductase

Antibiotic resistance is a growing problem for public health and associated with increasing economic costs and mortality rates. Silver and silver-related compounds have been used for centuries due to their antimicrobial properties. In this work, we show that 1,3-dibenzyl-4,5-diphenyl-imidazol-2-ylidene silver(I) acetate/NHC*-Ag-OAc (SBC3) is a reversible, high affinity inhibitor of E. coli thioredoxin reductase (TrxR; K_i=10.8±1.2 nM). Minimal inhibition concentration (MIC) tests with different E. coli and P. aeruginosa strains demonstrated that SBC3 can efficiently inhibit bacterial cell growth, especially in combination with established antibiotics like gentamicin. Our results show that SBC3 is a promising antibiotic drug candidate targeting bacterial TrxR.     

CuxNi1-xO nanostructures and their nanocomposites with reduced graphene oxide: Synthesis,characterization, and photocatalytic applications

NiO nanostructure was synthesized using a simple co-precipitation method and was embedded on reduced graphene oxide surface via ultrasonication. Structural investigations were made through X-ray diffraction (XRD) and functional groups were confirmed by Fourier transform infrared spectroscopy (FTIR). XRD analysis revealed the grain size reduction with doping. Fourier transform infrared spectroscopy confirmed the presence of metal-oxygen bond in pristine and doped NiO nanostructure as well as the presence of carbon containing groups. Scanning electron microscopy (SEM) indicated that the particle size decreased when NiO nanostructure was doped with copper. BET surface area was found to increase almost up to 43 m²/g for Cu doped NiO nanostructure/rGO composite. Current-voltage measurements were performed using two probe method. UV–Visible spectroscopic profiles showed the blue and red shift for Cu doped NiO nanostructure and Cu doped NiO Nanostructure/rGO composite respectively. Rate constant for Cu doped NiO nanostructure/rGO composite found to increase 4.4 times than pristine NiO nanostructure.     

Synthesis of amino-cosubstituted polyorganophosphazenes and fabrication of their nanoparticles for anticancer drug delivery

The development of safe drug carriers is cardinal in cancer therapy, which can target the cancer cells and release the loaded drug on-demand without damaging the healthy cells of the body. In our work, we synthesized three different biodegradable polymers, poly[(ethyl aminobezoate) (ethyl glycinato) phosphazenes] (PABGPs), in different mole ratio of side groups. The successful synthesis of these PABGPs was confirmed by ¹H NMR, ³¹P NMR, FT-IR, and gel permeation chromatography. These PABGPs were fabricated into drug (camptothecin, CPT, a hydrophobic anticancer drug) loaded nanoparticles. These drug-loaded nanoparticles showed good drug release behaviors under normal physiological conditions (pH 7.4 and temperature 37°C). These PABGPs-based nanoparticles may find their application as effective drug carriers for cancer therapy.     

Benchmarking performance of machine and deep learning-based methodologies for Urdu text document classification

Neural Computing and Applications - In order to provide benchmark performance for Urdu text document classification, the contribution of this paper is manifold. First, it provides a publicly...     

Transference and retrieval of voice message over low signal strength in satellite communication

This paper presents a method of transferring voice using short messaging service in satellite communication system. The method is especially applicable in a situation where signal strength is low and voice call is not possible. In a tunnel, basement or environment with bad climate conditions, signal strength usually gets weak which make voice call difficult but SMS works in such situation. An application has been developed using J2ME language in order to test the proposed method. For experimentation, Thuraya SG-2520 satellite phone has been used.     

Synthesis and characterization of caprolactone based polyurethane with degradable and antifouling performance

In this work,a degradable polyurethane composed of caprolactone(CL)and L-Lactide(LLA)as soft seg-ments,and 4,4'-methylenebis(cyclohexyl isocyanate)(H12MDI)and polytetramethylene ether glycol(PTMEG)as hard segments,was prepared.Hydrolytic degradation experiment revealed that the degrad-able polyurethane(PU)could be degraded in artificial seawater.It also showed that caprolactone-co-polyurethane(CL-PU)copolymer with higher crystallinity degraded much slower in artificial seawater.However,the introduction of LLA resulted in an increase in the hydrophilicity and reduction in the crys-tallinity of degradable PU,as demonstrated by the contact angle analysis.The result of the scanning elec-tron microscope showed that the surface of degradable PU renewed under static condition.Moreover,degradable PU was able to be used as a carrier,and it controlled the release rate of 4,5-dichloro-2-octyl-isothiazolone(DCOIT).The anti-diatom(Navicula incerta)test demonstrated that the(caprolactone-co-L-lactide)-co-polyurethane 4(CL/LAx-PU4)with DCOIT contents prevented the adhe-sion of diatom Navicula incerta(88.37％reduction)due to their self-polishing and the release of antifou-lants.Therefore,the degradable PU consisted of CL,LLA,and DCOIT could be a durable resin with good antifouling activity for the application in the marine anti-biofouling field.     

Painting-91: a large scale database for computational painting categorization

Computer analysis of visual art, especially paintings, is an interesting cross-disciplinary research domain. Most of the research in the analysis of paintings involve medium to small range datasets with own specific settings. Interestingly, significant progress has been made in the field of object and scene recognition lately. A key factor in this success is the introduction and availability of benchmark datasets for evaluation. Surprisingly, such a benchmark setup is still missing in the area of computational painting categorization. In this work, we propose a novel large scale dataset of digital paintings. The dataset consists of paintings from 91 different painters. We further show three applications of our dataset namely: artist categorization, style classification and saliency detection. We investigate how local and global features popular in image classification perform for the tasks of artist and style categorization. For both categorization tasks, our experimental results suggest that combining multiple features significantly improves the final performance. We show that state-of-the-art computer vision methods can correctly classify 50 % of unseen paintings to its painter in a large dataset and correctly attribute its artistic style in over 60 % of the cases. Additionally, we explore the task of saliency detection on paintings and show experimental findings using state-of-the-art saliency estimation algorithms.