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A significant challenge in the clothing industry is sustainable manufacturing with reduced exposure to toxic chemicals. This research presents a novel modification in the resin finishing of cotton fabric via successful compounding of etherified DMDHEU resin, waterborne polyurethane (WPU), and polyethylene wax (PEW) and its application by one-step eco-friendly route (Pad-Dry-Cure). Our hybrid finish formulation (DMDHEU resin/WPU/PEW) perfectly balanced ultra-high wear resistance, fast wrinkle recovery rate, and comfort properties. The optimal application conditions for etherified 2D resin and the conventional catalytic system magnesium chloride (MgCl2) were determined through the PAD-DRY-Cure finishing route, focusing on parameters such as resin concentration, curing time, and temperature. Second, a compounding of waterborne polyurethane (WPU) and etherified DMDHEU resin finish formulation was obtained, followed by an application and evaluation of the corresponding performance properties of the finished fabric with the compounded DMDHEU resin/WPU. Third, polyethylene wax (PEW) synthesis followed by cotton fabric finishing using optimized PEW and DMDHEU resin/ WPU hybrid finish formulation was done. Finally, finished fabric properties were investigated via scanning electron microscopy (SEM) and X-ray diffraction (XRD) structural analysis to examine its microstructure. Under optimized finishing conditions, the hybrid finish formulation consisting of MDHEU resin/WPU/polyethylene wax (PEW) application on cotton fabric demonstrated efficient wear resistance, high wrinkle recovery rate, and good laundering durability. Additionally, there was minimal loss of tensile strength and better air and water permeability, indicating enhanced wearing comfort. [ABSTRACT FROM AUTHOR]

Breast cancer is frequent among women and its early diagnosis using thermography is not been widely practiced in medical facilities due to its limitation in classification accuracy, sensitivity, and specificity. This research aims to improve the accuracy, sensitivity, and specificity of breast cancer classification in thermal images. The proposed system is composed of the Least Square Support Vector Machine (LSSVM) to improve the classification and prediction accuracy of breast thermography images using optimized hyperparameters. Multi-view breast thermal images are pre-processed using Gaussian Filtering (GF) with a standard deviation value of 1.4 which is followed by anisotropic diffusion while trying to enhance the image by removing noise. Interested regions are segmented by the level-set segmentation technique, and canny edge detection is applied to the segmented output to limit the amount of data and filter useless information. Texture features are extracted from 1370 healthy and 645 sick subjects fetched from Database for Mastology Research (DBR) which is an online free thermogram database. The features from different views of thermograms are later reduced with a t-test. Significant features are added together to obtain feature vector which produces vectors that are further supplied to the Vector Support Machine that utilizes optimized hyper-parameters for the breast thermogram classification. Compared to the state of art solution, the proposed system increased the accuracy by 9% while sensitivity and specificity get increased by 5.75% and 7.25% respectively. The proposed method focuses on modifying the anisotropic diffusion function and enhancing the segmentation of breast thermograms for classification analysis. [ABSTRACT FROM AUTHOR]

Rice bran is an essential co-product in rice meals with many biological activities. This study was aimed at evaluating the anti-inflammatory, wound healing, and hepatoprotective effects of ethanol extract of rice bran in vivo. The anti-inflammatory and hepatoprotective studies were performed in rats, and the wound-healing study was conducted in mice. Carrageenan and carbon tetrachloride were used to induce inflammation and hepatotoxicity respectively. The wound-healing activity of rice bran extract (RBE) was tested by creating a circular wound using a biopsy punch. For all the studies, animals were treated with RBE at a dose rate of 100 mg/kg and 200 mg/kg body weight (bwt). It was observed that RBE dose-dependently reduced the carrageenan-induced paw edema and wound-closing time (9–10 days) compared with that of control rats (12 days). Histological examination of the inflamed rat paw tissue showed massive infiltration of inflammatory cells, which was significantly reduced by RBE treatment. Intra-peritoneal injection of CCl4 increased the serum AST and ALT levels, which were significantly (p < 0.05) decreased by RBE treatment in a dose-dependent manner. The histological section of the liver tissue showed severe hepatic cell damage in CCl4-injected animals, which were distinctly regenerated by RBE treatment (200 mg/kg bwt). These results demonstrated that RBE has potent anti-inflammatory, wound-healing, and hepatoprotective effects in the experimental animal. [ABSTRACT FROM AUTHOR]

In this research, we proposed a stereo visual simultaneous localisation and mapping (SLAM) system that efficiently works in agricultural scenarios without compromising the performance and accuracy in contrast to the other state-of-the-art methods. The proposed system is equipped with an image enhancement technique for the ORB point and LSD line features recovery, which enables it to work in broader scenarios and gives extensive spatial information from the low-light and hazy agricultural environment. Firstly, the method has been tested on the standard dataset, i.e., KITTI and EuRoC, to validate the localisation accuracy by comparing it with the other state-of-the-art methods, namely VINS-SLAM, PL-SLAM, and ORB-SLAM2. The experimental results evidence that the proposed method obtains superior localisation and mapping accuracy than the other visual SLAM methods. Secondly, the proposed method is tested on the ROSARIO dataset, our low-light agricultural dataset, and O-HAZE dataset to validate the performance in agricultural environments. In such cases, while other methods fail to operate in such complex agricultural environments, our method successfully operates with high localisation and mapping accuracy. [ABSTRACT FROM AUTHOR]

Doctors in developing countries are too busy to write digital prescriptions. Ninety-seven percent of Bangladeshi doctors write handwritten prescriptions, the majority of which lack legibility. Prescriptions are harder to read as they contain multiple languages. This paper proposes a machine learning approach to recognize doctors' handwriting to create digital prescriptions. A 'Handwritten Medical Term Corpus' dataset is developed containing 17,431 samples of 480 medical terms. In order to improve the recognition efficiency, this paper introduces a data augmentation technique to widen the variety and increase the sample size. A sequence of line data is extracted from the augmented images of 1,591,100 samples and fed to a Bidirectional Long Short-Term Memory (LSTM) network. Data augmentation includes pattern Rotating, Shifting, and Stretching (RSS). Eight different combinations are applied to evaluate the strength of the proposed method. The result shows 93.0% average accuracy (max: 94.5%, min: 92.1%) using Bidirectional LSTM and RSS data augmentation. This accuracy is 19.6% higher than the recognition result with no data expansion. The proposed handwritten recognition technology can be installed in a smartpen for busy doctors which will recognize the writings and digitize them in real-time. It is expected that the smartpen will contribute to reduce medical errors, save medical costs and ensure healthy living in developing countries. [ABSTRACT FROM AUTHOR]

Nowadays, the most dynamic and safe imaging technique used in hospitals to diagnose is magnetic resonance imaging (MRI). In clinical applications, such as follow-up of patients with planning surgery, radiation therapy, therapy response in bone metastases assessment and treatment for brain disorders, repeated MRI scans are performed. Unfortunately, the slow acquisitions of MRI drive cost high by limiting patient throughput as well as limiting the potential indications for use. A mathematical framework called compressed sensing (CS) to accelerate MRI acquisition is used for generating undersampled measurements. Then, the iterative nonlinear numerical method is required for perfect reconstruction from highly undersampled measurements. In this work, the multiscale wavelet domain regularization prior-based iterative reconstruction algorithm is developed to address the above-mentioned reconstruction problem, in which multiscale wavelet domain generalized Gaussian mixture model is utilized for the regularization prior. The regularization-based algorithm is applied to generate three-dimensional (3D) high-quality MRI volume from multichannel k-space measurements in a compressed sensing framework. Several experiments using one synthetic and one real 3D CS multichannel k-space data were used to evaluate and validate the performance of the proposed algorithm. The total variation (TV)-based and soft-thresholding (ST) based-reconstruction methods were implemented to compare with the proposed algorithm. Extensive experimental results demonstrated that the proposed method has improved results in terms of visual quality and quantitative measurements compared to the existing methods. [ABSTRACT FROM AUTHOR]

In modern computed tomography (CT) imaging, a high-quality image is produced by passing the X-ray radiation dose through the human body. The strategy for CT dose reduction is to reduce the projection views or to limit the scan angle. However, the reduction of radiation doses generates insufficient projection data which often leads the reconstruction problem. Iterative techniques are widely used addressing this issue where a prior-based method is more beneficial to reconstruct CT images. In this paper, the soft-thresholding-based reconstruction method is presented, and the use of the generalized Gaussian distribution model is considered to find the optimal thresholding value. Experimental results show that the reconstructed CT image from fewer projection views using the proposed method has higher quality compared with the other reconstruction approaches. [ABSTRACT FROM AUTHOR]

RNA Structure Prediction (RSP) is an optimization problem, where a stable secondary structure is obtained from an RNA primary sequence. To solve the RSP problem, many exact and metaheuristic algorithms were established in recent years. We have proposed an approach based on metaheuristic algorithm named Chemical Reaction Optimization (CRO) to solve the RSP problem. CRO is a population-based metaheuristic which has been employed in different optimization problems and works better than all other related existing algorithms. We have redesigned the reaction operators of CRO algorithm and calculated the minimum free energy of the RNA structure to solve RSP problem. The operators spread out the population entirely on the solution space using both local and global searches and find the better structure, which makes the proposed algorithm more unique. We have designed a novel operator called Repair function to verify and remove the repeated stem from the solution of an RNA sequence, which makes the process more time efficient. Both the quality of solutions and execution time are considered in designing the basic operators and the repair function. Thus, the proposed methodology gives robustness, efficiency, and effectiveness in solving the problem. The results of the proposed CRO based algorithm for RSP problem are compared with genetic algorithm (RNAPredict), simulated annealing algorithm (SARNA-Predict), coincidence algorithm (COIN), two-level particle swarm optimization algorithm (TL-PSOfold) and Changing Range Bat Algorithm (CRBA) to present that, the proposed work gives better results than those. The significance testing using Kruskal-Wallis test followed by post-hoc analysis also proves that the proposed work outperforms the five related methods. [ABSTRACT FROM AUTHOR]

The study was planned to see if there is any important and significant changes in the PMN function in cows suffering from postpartum reproductive diseases (PRD). Blood sampling was done from 41 pregnant cows on 15 days prepartum (−15d), calving day (0d), 15 days (15d) and 30 days (30d) postpartum and thorough gynaecological examination was performed on 0d, 15d, 30d and 45d for diagnosis of PRD like retained placenta (RP), clinical metritis (CM), clinical endometritis (CE) and delayed involution of uterus (DIU). The heparinised blood was used for isolation of PMN leukocytes for estimation of superoxide (SO), hydrogen peroxide (HO) and enzyme myeloperoxidase (MPO) activity in each group of cows. The SO production (ΔOD) was greater for normal (0.19 ± 0.05) than cows suffering from RP (−0.12 ± 0.09), CM (−0.15 ± 0.13) and CE (−0.07 ± 0.05) at -15d. The mean value was greater for normal cows (0.12) than the cows with PRD (0.05 to 0.9) at 30d. The HO production was greater for normal than cows with PRD at all sampling days and significantly greater than cows with RP and CE at 15d ( p < 0.01) and 30d ( P < 0.05). The MPO activity (μmol/1 × 10) was greater for normal (18.77 ± 1.27) than for RP (12.52 ± 2.57) and CM (11.31 ± 3.30) cows on 0d. The depressed capability of the PMN from the cows with PRD to produce SO, HO and MPO during the periparturient period indicated their association with the development of RP, CM and CE. [ABSTRACT FROM AUTHOR]

Three-dimensional (3-D) aggregate culturing is useful for investigating the functional properties of mesenchymal stem/stromal cells (MSCs). For 3-D MSC analysis, however, pre-expansion of MSCs with two-dimensional (2-D) monolayer culturing must first be performed, which might abolish their endogenous properties. To avoid the need for 2-D expansion, we used prospectively isolated mouse bone marrow (BM)-MSCs and examined the differences in the biological properties of 2-D and 3-D MSC cultures. The BM-MSCs self-assembled into aggregates on nanoculture plates (NCP) that have nanoimprinted patterns with a low-cellular binding texture. The 3-D MSCs proliferated at the same rate as 2-D-cultured cells by only diffusion culture and secreted higher levels of pro-angiogenic factors such as vascular endothelial growth factor and hepatocyte growth factor (HGF). Conditioned medium from 3-D MSC cultures promoted more capillary formation than that of 2-D MSCs in an in vitro tube formation assay. Matrigel-implanted 3-D MSC aggregates tended to induce angiogenesis in host mice. The 3-D culturing on NCP induced alpha-fetoprotein (AFP) expression in MSCs without the application of AFP- or endodermal-inducible factors, possibly via an HGF-autocrine mechanism, and maintained their differentiation ability for adipocytes, osteocytes, and chondrocytes. Prospectively isolated mouse BM-MSCs expressed low/negative stemness-related genes including Oct3/4, Nanog, and Sox2, which were not enhanced by NCP-based 3-D culturing, suggesting that some of these cells differentiate into meso-endodermal layer cells. Culturing of prospectively isolated MSCs on NCP in 3-D allows the analysis of the biological properties of more closely endogenous BM-MSCs and might contribute to tissue engineering and repair. [ABSTRACT FROM AUTHOR]

One hundred and fifty soil samples collected from different crop fields in southern Ontario, Canada were screened to obtain microorganisms capable of transforming deoxynivalenol (DON) to de-epoxy DON (dE-DON). Microbial DON to dE-DON transformation (i.e. de-epoxydation) was monitored by using liquid chromatography-ultraviolet-mass spectrometry (LC-UV-MS). The effects of growth substrates, temperature, pH, incubation time and aerobic versus anaerobic conditions on the ability of the microbes to de-epoxydize DON were evaluated. A mixed microbial culture from one composite soil sample showed 100% DON to dE-DON biotransformation in mineral salts broth (MSB) after 144 h of incubation. Treatments of the culture with selective antibiotics followed an elevated temperature (50°C) for 1.5 h considerably reduced the microbial diversity. Partial 16S-rRNA gene sequence analysis of the bacteria in the enriched culture indicated the presence of at least six bacterial genera, namely Serratia, Clostridium, Citrobacter, Enterococcus, Stenotrophomonas and Streptomyces. The enriched culture completely de-epoxydized DON after 60 h of incubation. Bacterial de-epoxydation of DON occurred at pH 6.0-7.5, and a wide array of temperatures (12-40°C). The culture showed rapid de-epoxydation activity under aerobic conditions compared to anaerobic conditions. This is the first report on microbial DON to dE-DON transformation under aerobic conditions and moderate temperatures. The culture could be used to detoxify DON contaminated feed and might be a potential source for gene(s) for DON de-epoxydation. [ABSTRACT FROM AUTHOR]

Mucopolysaccharidosis VII (MPS VII) is an autosomal recessive disorder caused by the deficiency of β-glucuronidase leading to the intralysosomal storage of heparan, dermatan, and chondroitin sulfate. Here, we report the identification of two novel missense mutations K350N and R577L in a 37-year-old patient with β-glucuronidase deficiency and a relatively mild MPS VII phenotype. Expression of the K350N mutation in baby hamster kidney cells has revealed residual enzymatic activity and normal transport of the enzyme to the lysosome. However, expression of the R577L or the double mutant K350N/R577L results in rapid degradation of the enzyme in early biosynthetic compartments and a total loss of enzymatic activity. We attribute the mild phenotype to the residual catalytic activity provided by the K350N mutant. At the time of her death at the age of 37 years, this patient was the longest known survivor with MPS VII. [ABSTRACT FROM AUTHOR]

The objective of this paper is to deal with the design of a pilot-scale submerged membrane bioreactor (MBR) and a short-term functionality test to be performed with textile wastewater. The design calculations were done based on the design parameters analysed from local textile wastewater and typical values of activated sludge kinetic coefficients. Other process parameters like bioreactor volume (tank size), hydraulic residence time (HRT), biomass loading (F/M ratio), oxygen demand, etc., were calculated depending on the real textile wastewater characteristics. Taking the design basis into consideration, a pilot-scale MBR was constructed equipped with LabVIEW programme- and sensors-controlled computer system. Based on the theoretical calculations, the hydraulic volume of the MBR reactor was around 56.6 L with flat sheet membranes (3 sheets, with 25 cm × 25 cm dimensions of each sheet) with HRT of 16.9 h. Finally, performance tests for 6 weeks were carried out in a local (Darmstadt, Germany) laundry textile wastewater to test the functionality of MBR pilot plant. Under the operating conditions of 250 mbar suction pressure and 12 g/L of MLSS, the COD removal efficiency was around 90% for 800–3500 mg/L inlet COD fed to the membrane bioreactor. [ABSTRACT FROM AUTHOR]