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In this study, we aimed to develop a low-mexthoxyl pectin (LMP) from mango peel pectin through a de-esterification method for use as a film forming agent. The prepared de-esterified pectin (DP) was compared to commercial LMP (cLMP) which possessed a 29% degree of esterification (DE). Mango peel pectin was extracted from ripe Nam Dokmai mango peel using the microwave-assisted extraction method. Pectin derived from the mango peel was classified as a high mexthoxyl pectin (79% DE) with 75% of galacturonic acid (GalA) content. A de-esterification experiment was designed by central composite design to plot the surface response curve. Our prepared DP was classified as LMP (DE 29.40%) with 69% GalA. In addition, the Fourier-transform infrared spectrophotometer (FTIR) spectra of the DP were similar to cLMP and the pectin backbone was not changed by the de-esterification process. Strikingly, the cLMP and DP films showed non-significant differences between their physical properties (p > 0.05) with respect to the puncture not significantly different from a commercial clindamycin solution. check details The results of this study suggest that mango peel pectin can be de-esterified and utilized as an LMP and the de-esterified pectin has the potential for use as a film forming agent, similar to cLMP. In addition, the remarkable use of de-esterified mango peel pectin to prepare films, as shown by our study, holds a great promise as an alternative material for anti-bacterial purposes.Today, daily life is composed of many computing systems, therefore interacting with them in a natural way makes the communication process more comfortable. Human-Computer Interaction (HCI) has been developed to overcome the communication barriers between humans and computers. One form of HCI is Hand Gesture Recognition (HGR), which predicts the class and the instant of execution of a given movement of the hand. One possible input for these models is surface electromyography (EMG), which records the electrical activity of skeletal muscles. EMG signals contain information about the intention of movement generated by the human brain. This systematic literature review analyses the state-of-the-art of real-time hand gesture recognition models using EMG data and machine learning. We selected and assessed 65 primary studies following the Kitchenham methodology. Based on a common structure of machine learning-based systems, we analyzed the structure of the proposed models and standardized concepts in regard to the types of models, data acquisition, segmentation, preprocessing, feature extraction, classification, postprocessing, real-time processing, types of gestures, and evaluation metrics. Finally, we also identified trends and gaps that could open new directions of work for future research in the area of gesture recognition using EMG.Predicting developmental outcomes with growth measurement would be beneficial for primary healthcare or in developing countries with low medical resources. This study aimed to identify physical growth measures that indicate neurodevelopment in very preterm infants. Preterm infants, born at less then 32 weeks' gestation or weighing less then 1500 g, were included. We calculated the changes in z-score of weight, length, and head circumference (HC) at different time points birth, postmenstrual age (PMA) 35 weeks, and 4 and 18 months corrected age (CA). We examined the relationship between growth and Bayley-III scores using linear regression. Among 122 infants, HC at 4 months CA and HC growth between PMA 35 weeks and 4 months CA showed a positive correlation with Bayley-III scores in appropriate-for-gestational-age infants (AGAs). Weight and length increases between birth and 18 months CA were also associated with AGAs' development. In small-for-gestational-age infants (SGAs), only birthweight's z-score was associated with improved neurodevelopmental outcomes. HC at 4 months CA was an important indicator of favorable neurodevelopmental outcomes, and head growth spurt between PMA 35 weeks and 4 months CA contributed to this benefit in preterm AGAs. The period and indices should be monitored differently for SGAs and AGAs.This work aimed to study the anti-bacterial, anti-biofilm and anti-oxidant potential effects of low molecular weight (LMW) peptides (Br-p) isolated from burdock (Arctium lappa L.) roots. We conducted a preliminary study to exclude or confirm the antibiotic activity of the LMW peptides fraction of this plant. Br-p were isolated using gel filtration and a 10 kDa cut-off membrane. The obtained peptides were identified by MALDI TOF/TOF. Antibacterial activity was tested against acne strains using diffusion tests, MIC and MBC. The fibroblast cytotoxicity of Br-p was tested, and the selectivity index (SI) value was determined. The fraction of 46 Br-p peptides isolated from burdock root with a molecular weight below 5000 Da and theoretic pI (isoelectric point) of 3.67-11.83 showed a narrow spectrum of activity against Gram-positive acne bacterial strains. One of the Br-p peptides assessed on MALDI RapidDeNovo was LRCDYGRFFASKSLYDPLKKRR cationic peptide. It was analogous to that contained in A. lappa protein, and theoretically it was matched as a peptide with antibiotic nature. Br-p did not show toxicity to fibroblasts in the tested concentration up to 10 mg/mL, obtaining CC50 10 mg/mL. check details The SI value for the tested Propionibacterium strains ranged from 160 to 320. Finally, an active dressing based on chitosan/alginate/genipin was prepared using freeze-drying. The formed dressing was evaluated for its anti-acne activity. To sum up preliminary biological studies confirmed the anti-acne properties of the isolated peptide fraction from burdock root and pointed to the possibility of using it to create an active dressing on the skin.Late wilt is a destructive disease of corn outbreaks occur at the advanced growth stage and lead to severe dehydration of susceptible hybrids. The disease's causal agent is the fungus Magnaporthiopsis maydis, whose spread relies on infested soils, seeds, and several alternative hosts. The current study aimed at advancing our understanding of the nature of this plant disease and revealing new ways to monitor and control it. Two field experiments were conducted in a heavily infested area in northern Israel seeded with highly sensitive corn hybrid. The first experiment aimed at inspecting the Azoxystrobin (AS) fungicide applied by spraying during and after the land tillage. Unexpectedly, the disease symptoms in this field were minor and yields were high. Nevertheless, up to 100% presence of the pathogen within the plant's tissues was measured using the quantitative real-time PCR method. The highest AS concentration tested was the most effective treatment, and resulted in a 6% increase in cob yield and a 4% increase in A-class yield.