Mudanças físicas e químicas durante a maturação de frutos de amora preta

Blackberry (Rubus L.) is a naturally growing fruit in Anatolia. Consumption of fresh and frozen blackberries has increased in the past few years in Turkey. The aim of this study is to analyze blackberry at three levels of ripeness taking into account some physical and chemical properties (color, dry matter, soluble solids, total sugar, titratable acidity, pH, total phenolics, total anthocyanin, and minerals) in order to understand this behavior during the ripening process. Blackberry fruits were harvested at green, red and ripe (mature) stages. The determination of fruit maturity was based on fruit surface color. The dry matter, total phenolics and Hunter L, b values decreased but soluble solids, total sugar and total anthocyanins increased with maturity. In the early fruit ripening stages, pH decreased, titratable acidity and Hunter a value increased while in the later stages, pH increased, titratable acidity and Hunter a value decreased considerably. Analysis of variance revealed (P < 0.01) differences in these parameters based on ripeness stages. No remarkable changes in potassium, calcium, zinc and manganese concentrations occured during the development of fruits. Differences were observed for magnesium (P < 0.01), iron (P < 0.01) and copper (P < 0.05) during ripening of blackberry.Amora preta (blackberry, Rubus L.) é uma fruta que cresce naturalmente na península de Anatolia. O consumo de suas frutas frescas ou congeladas aumentou nos últimos anos na Turquia. Este estudo teve por objetivo analisar amoras pretas colhidas em três níveis de maturação, levando em conta propriedades físicas e químicas das frutas (cor, matéria seca, sólidos solúveis, açúcar total, acidez titulável, pH, fenóis totais, antocianina total e sais minerais) para melhor compreender o processo de maturação. As frutas foram colhidas nos estágios verde, vermelho e maduro. A determinação do estágio maduro foi baseada na cor da superfície das frutas. A materia seca, os fenóis totais e os valores de Hunter L, b diminuiram mas os sólidos solúveis, açúcares totais e total de antocianina decresceram em função do nível de maturação. Nos estágios iniciais de maturação, o pH decresceu, a acidez titulável e o valor a de Hunter aumentaram enquanto nos estágios posteriores o pH aumentou, a acidez titulável e o valor a de Hunter decresceram consideravelmente. A análise de variância revelou diferenças nestes parâmetros (P < 0,01), baseada nos estágios de maturação. Não houve mudanças marcantes nos conteúdos de potássio, calico e magnésio durante o desenvolvimento dos frutos. Diferenças foram obsevadas para magnésio (P < 0,01), ferro (P < 0,01) e cobre (P < 0,05) durante a maturação das amoras pretas

Partial purification and characterization of alkaline proteases from the Black Sea anchovy (Engraulis encrasicholus) digestive tract

Alkaline proteases from the digestive tract of anchovy were partially purified by ammonium sulfate fractionation, dialysis and Sephadex G-75 gel filtration. The purification fold and yield were 6.23 and 4.49%, respectively. The optimum activities of partially purified alkaline proteases were observed at 60°C and at pH 11.0. The alkaline proteases were stable within the temperature range of 40 to 50°C and pH range of 9.0 to 11.0. They were inhibited by the serine-protease inhibitor phenylmethylsulfonyl fluoride (PMSF) and trypsin specific inhibitor benzamidine, but were not inhibited by the β-mercaptoethanol. The enzymes were slightly activated by metal ions such as Na+ and Ba2+ and inhibited by Cu2+, Zn2+, K+ and Mn2+ at different degrees. The molecular weight of the partially purified enzyme was 24 kDa by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE).Key words: Alkaline proteases, Engraulis encrasicholus, purification, characterization, digestive tract

Teachers’ Record Keeping as Related to Teachers Job Performance in Cross River State Secondary Schools, Nigeria

This research investigated the influence of principal’s inspection of teachers’ record keeping strategy on teachers’ job performance in Cross River State, Nigeria. Subjects involved six hundred and sixty (660) teachers and three thousand, three hundred senior secondary school students which were randomly selected from two hundred and thirty two (232) secondary schools in Cross River State. Data was collected with Principals’ Instructional Supervisory Strategies Questionnaire (PISSQ) and Teachers’ Job Performance Scale Questionnaire (TJPSQ). The result of analysis utilizing one-way analysis of variance (ANOVA) indicated that principal’s inspection of record keeping strategy significantly influenced teachers’ job performance. It is recommended that regular supervision which must include teachers’ record keeping strategy be regularly organized by government to enhance teachers’ job performance

Screening for Antibacterial Activity of Andrographis paniculata Used in Malaysian Folkloric Medicine: A Possible Alternative for the Treatment of Skin Infections

In this study non-polar (dichloromethane) and polar (MeOH & aqueous) extracts of A. paniculata (whole plant) were evaluated for in vitro antibacterial activity against 12 skin disease causing bacterial strains (7 gram positive strains; Staphylococcus saprophyticus, Staphylococcus epidermis, Staphylococcus aureus, Streptococcus pyogenes, Bacillus anthracis, Micrococcus luteus, Enterococcus faecalis) and 5 gram negative strains; Proteus mirabilis, Proteus vulgaris, Klebsiella pneumoniae, Neisseria meningitis, Pseudomonas aeruginosa ) using the disc diffusion method at three concentrations; 1000, 500, and 250 μg/disc respectively in order to ascertain its folkloric claim to treat skin infections. The extracts showed significant antibacterial activities against both the Gram-positive and Gram-negative bacterial strains tested. Highest significant antibacterial activity was exerted by the MeOH extract against E. faecalis at 1000 μg/disc (24.00 ± 0.00 mm) and the least activity by the DCM extract against N. meningitis at 250 μg/disc (6.00 ± 0.00mm). The minimum inhibitory concentration ranged between 150 μg /mL and 300 μg /mL depending on microorganism and various extracts. Presence of phytochemicals such as terpenoids, tannins, flavonoids, saponins, alkaloids, amino acids and steroids were observed. These results candidly suggest the presence of promising antibacterial substances in the polar as well as non-polar extracts which could be potential phytomedicine for the treatment of skin infections caused by pathogenic bacterial strains. These findings explicitly support its traditional claims and form a strong basis for further efforts to explore A. paniculata’s antibacterial potential to treat skin frailties efficaciously. Our results confer the utility of this plant extracts in developing a novel broad spectrum antimicrobial agent

Personalized Health Assessment and Recommendations Through Iot and Mlp Classifier Algorithms

Procuring a healthy lifestyle involves a holistic approach of personalized dietary and exercise recommendations dependent on individual health statuses. In this study, we present a new paradigm for examining individual health statuses for easy self-assessment without specialist help. The heart is a full kit of assessing instruments that can align critical climacterics of body temperature, pulse rate, blood oxygen level, and body max index that could be run with minor medic assistance. The research abides a dataset obtained through a broad scope of volunteers aged 17 to 24 including both males and females. Vital signs such as SpO2, BPM, temperature, and BMI are mediated utilizing incorporated Internet of Things units. The dataset is then cautiously preprocessed and balanced using machine learning algorithms before examination. The basis of this model is a two-tier state classifier system that designs autonomous dietary and exercise responsibilities varying from examined health clots. It is exploited for adulthood healthcare systems across multiple machines learning techniques, including Decision Tree, KNN, and some classifiers with the MLP classifier being the exemplary worthy model. The MLP classifier demonstrates unbelievable outcomes through approximately 86% accuracy when the trainings and testing datasets are 70:30 ratios apart

The mechanism of the air-jet texturing: the role of wetting, spin finish and friction in forming and fixing loops

A comprehensive review of the roles played by the airflow, wetting and spin finish on the air-jet texturing process is given. An experimental investigation of the air-jet texturing process using residual spin finish, yarn-to-yarn static and kinetic friction, filament strength, filament diameter, and on-line tension measurements and high-speed cine-photography is reported. Filament yarn motion in different regions of the texturing nozzle during dry and wet texturing is analysed. It is found that water acts as lubricant to reduce friction between the filaments in the wet texturing process as the filament yarn travels through the nozzle enabling easier relative motion of the filaments resulting in enhanced entanglement. Wet texturing also reduces spin finish on the yarn surface, which in turn, causes an increase in static friction between the filaments of the textured yarn resulting in better fixing of the loops and consequently superior yarns

Decision Tree Algorithm for Breast Cancer Detection

A major form of cancer affecting women around the world is breast cancer. This underscores the importance of early detection for optimal treatment outcomes. This paper addresses the challenge of correctly classifying tumors as malignant or benign in light of the fact that breast cancer is a significant component of cancer cases around the world. As a breast cancer detection algorithm, there are several advantages to using this decision tree algorithm. Decision trees provide insight into the importance of features, which in turn allows for the identification of key factors that contribute to the classification of breast cancer. In addition to that, decision trees are able to deal with both numerical and categorical features, so they are suitable for a variety of breast cancer data sets. It is also important to note that decision trees are less sensitive than other algorithms when it comes to outliers and missing data. To begin with, decision trees provide insight into the importance of features, which allows for the identification of key factors that contribute to the classification of breast cancers. A decision tree can also be used to analyze both numerical and categorical features, making it more versatile for the analysis of breast cancer data in general. The decision tree algorithm, on the other hand, has a lower sensitivity to outliers and missing data than some other algorithms. As a result of utilizing performance metrics to assess the effectiveness of algorithms, it was found that the Decision Tree Algorithm was more effective at detecting breast cancer than other algorithms