Effect of Hydrogen Peroxide Concentration on 100% Cotton Knit Fabric Bleaching

This paper focuses on the effect of different concentration of hydrogen peroxide (an oxidizing bleaching agent) on 100% single jersey cotton knit fabric. Five different concentrations (25%, 30%, 35%, 40% and 45%) of hydrogen peroxide solution (5% stock solution) were adopted for this experiment. For each individual concentration, bleaching was performed in three different quantities (6gm/L, 8gm/L and 10gm/L) at the same temperature (100˚C) and same time (60 minute) cycle. 5gm samples were taken where 1:10 material and liquor ratio was maintained in each operation. Spectrophotometer (data color 650) was used to test the reflectance of all bleached samples, and their bursting strengths were measured by an Auto burst instrument following ISO 13938-1 method. The effects of hydrogen peroxide concentration on various physical properties such as weight loss, absorbency, GSM, bursting strength, and whiteness was studied to minimize the cost of bleaching process by optimizing the concentration of hydrogen peroxide. As majority of industries have concerned to alineate the production cost with maximum quality assurance which has been obtained through bleaching at 30% concentration

Impact of bleaching actions of bleaching powder and hydrogen peroxide on biopolished denim garments

U radu je ispitan utjecaj pranja s izbjeljivanjem s dva različita sredstva za bijeljenje: praškom za bijeljenje i vodikovim peroksidom na prethodno biopoliranu pamučnu denim tkaninu bojadisanu s indigo bojilom. Odjevni proizvodi od pamučne denim tkanine obojadisani indigo bojilom su prani uz dodatak enzima radi otklanjanja dlakavosti površine, odnosno biopolirani. Nakon toga je jedan dio obrađivan s praškastim sredstvom za bijeljenje u koncentraciji od 2,5 g/L u vremenima od 3 i 5 min na 50 óC, a drugi dio s vodikovim peroksidom u koncentraciji 2,5 g/L u vremenima od 5 i 10 min. Nakon obrada na uzorcima su provedena ispitivanja vlačne čvrstoće, čvrstoće u šavu, površinske mase, postojanosti obojenja na vodu, na kiselinu, lužinu, pranje i habanje. Pranje odjevnih predmeta s izbjeljivanjem provedeno primjenom dvaju sredstva za bijeljenje imalo je velik utjecaj na njihova fizikalna svojstva i postojanosti obojenja u odnosu na neobrađene predmete.This study shows the impact of bio polishing and bleach wash of two different bleaching agent one is bleaching powder and another is hydrogen peroxide on 100 % cotton denim dyed with indigo dye. Garments were washed with enzyme to remove hairiness . biopolished. Then garments were subjected to a bleach concentration with bleaching powder of 2.5 g/L for 3 and 5 minutes at 50 oC temperature and other were bleached with hydrogen peroxide of 2.5 g/L for 5 and 10 minutes. The physical and colour fastness properties were analyzed in before and after washing. The properties that were analyzed include tensile strength, seam strength, fabric weight, and colour fastness to water, acid, alkali, washing and rubbing. Bleach washed garments by two different bleaching agent exhibit a great influence on the physical and colour fastness properties than the unwashed garments

Impact of bleaching actions of bleaching powder and hydrogen peroxide on biopolished denim garments

U radu je ispitan utjecaj pranja s izbjeljivanjem s dva različita sredstva za bijeljenje: praškom za bijeljenje i vodikovim peroksidom na prethodno biopoliranu pamučnu denim tkaninu bojadisanu s indigo bojilom. Odjevni proizvodi od pamučne denim tkanine obojadisani indigo bojilom su prani uz dodatak enzima radi otklanjanja dlakavosti površine, odnosno biopolirani. Nakon toga je jedan dio obrađivan s praškastim sredstvom za bijeljenje u koncentraciji od 2,5 g/L u vremenima od 3 i 5 min na 50 óC, a drugi dio s vodikovim peroksidom u koncentraciji 2,5 g/L u vremenima od 5 i 10 min. Nakon obrada na uzorcima su provedena ispitivanja vlačne čvrstoće, čvrstoće u šavu, površinske mase, postojanosti obojenja na vodu, na kiselinu, lužinu, pranje i habanje. Pranje odjevnih predmeta s izbjeljivanjem provedeno primjenom dvaju sredstva za bijeljenje imalo je velik utjecaj na njihova fizikalna svojstva i postojanosti obojenja u odnosu na neobrađene predmete.This study shows the impact of bio polishing and bleach wash of two different bleaching agent one is bleaching powder and another is hydrogen peroxide on 100 % cotton denim dyed with indigo dye. Garments were washed with enzyme to remove hairiness . biopolished. Then garments were subjected to a bleach concentration with bleaching powder of 2.5 g/L for 3 and 5 minutes at 50 oC temperature and other were bleached with hydrogen peroxide of 2.5 g/L for 5 and 10 minutes. The physical and colour fastness properties were analyzed in before and after washing. The properties that were analyzed include tensile strength, seam strength, fabric weight, and colour fastness to water, acid, alkali, washing and rubbing. Bleach washed garments by two different bleaching agent exhibit a great influence on the physical and colour fastness properties than the unwashed garments

Analyses of variability, euclidean clustering and principal components for genetic diversity of eight Tossa Jute (Corchorus olitorius L.) genotypes

An investigation was done to assess the genetic variability, character associations, and genetic diversity of eight jute genotypes for seven morphological traits in a randomised complete block design at Bangladesh Jute Research Institute during 15 March, 2018 to 31 December, 2019. Analyses results revealed significant differences (P<0.01) among all genotypes for studied traits indicating the presence of variability. All the lines performed better than one control (JRO-524), and the line (O-0412-9-4) provided good results for desired traits than all controls. Jute fibre yield showed the highest broad sense heritability (98.54%). The studied jute morphological traits i.e. Plant population, the plant height, green weight, dry fibre yield and dry stick yield gave high heritability along with high genotypic and phenotypic variances, genetic advances in percent of the mean, highly significant and positive correlations. It indicates the possibility of crop improvement through phenotypic selection and maximum genetic gain, simultaneously at the genotypic-phenotypic level. Clustering analysis grouped all genotypes into three distinct clusters. The cluster II showed the highest mean values for all traits followed by cluster I and III. The first two principal components with higher Eigen values (>1.0) accounted for 90.88% of the total variation in the principal component analysis. PCA and cluster analyses indicated that the advanced breeding line O-0412-9-4 made its individual cluster II with higher inter-cluster distance and higher fibre yield (3.12 t ha-1). The investigation was done to select the genotype(s) with good fibre yield and distinct features in respect of developing high yielding Tossa jute variety for cultivation in the farmers’ field. This genotype O-0412-9-4 was selected based on higher plant height, base diameter, fibre yield content. It will be developed as a high yielding variety considering its’ higher genetic variability, heritability, genetic advance, significant associations for desirable characters

Determining the effects of elevated carbon dioxide on soil acidification, cation depletion, and soil inorganic carbon and mapping soil carbons using artificial intelligence

Soil carbon is the largest sink and source of the global carbon cycle and is disturbed by several natural, anthropogenic, and environmental factors. The global increase of atmospheric CO2 affects soil carbon cycling through varied biogeochemical processes. The first chapter is a compilation of current information on potential factors triggering soil acidification and weathering mechanisms under elevated CO2 and their consequences on soil inorganic carbon (SIC) pool and quality. Soil water content and precipitation were critical factors influencing elevated CO2 effects on the SIC pool. The second chapter examines a detailed column experiment in which six soils from the state of Mississippi, USA, representing acidic, neutral, and alkaline pH, were exposed to different CO2 enrichments (100%, 10%, and 1%) for 30 days. The leachates’ pH tended to attain an equilibrium state (neutral) with time under CO2 saturation. SIC increased under CO2 saturation, whereas cation exchange capacity (CEC) showed a decreasing pattern in all soils. In the third chapter, an eXplainable artificial intelligence (XAI) was performed to visualize the different forms of soil carbon variability across the Mississippi River Basin area. This model explains key insights and local discrepancies, suggesting a solution to the “Black-Box” issue. The best performing model, stack ensemble, showed improved RMSE (3 to 8%) and spatial variability for soil carbons than other ML models, especially after adding the residuals from regression analyses. Land cover type \u3e soil pH \u3e total nitrogen, \u3e NDVI were identified as the top four crucial factors for predicting SOC when bulk density \u3e precipitation, soil pH \u3e mean annual temperature described SIC. The proposed automatic machine learning (AutoML) model with model agnostic interpolations might be a hallmark to mitigate the C loss under adverse climate change conditions and allow diverse knowledge groups to adopt a new interpretable ML algorithm more confidently. Findings from this study help predict the impact of elevated atmospheric CO2 on soil pH, acidification, and nutrient availability and develop strategies for sustainable land management practices under a changing climate

Chaotic Lightweight Cryptosystem for Image Encryption

Data transmission over the Internet and the personal network has been risen day by day due to the advancement of multimedia technology. Hence, it is today’s prime concern to protect the data from unauthorized access and encrypt the multimedia element as they are stored on the web servers and transmitted over the networks. Therefore, multimedia data encryption is essential. But, the multimedia encryption algorithm is complex to implement as it requires more time and memory space. For this reason, the lightweight image encryption algorithm gains popularity that requires less memory and less time along with low power or energy and provides supreme security for limited devices. In this study, we have studied the chaotic-based lightweight image encryption method. At first, we have presented a standard framework and algorithm based on two chaotic maps such as Arnold and logistic for lightweight image encryption and performed some experiments. We have analyzed different groups of images such as miscellaneous, medical, underwater, and texture. Experimentations have provided the largest entropy 7.9920 for medical image (chest X-ray), large key space 2m×m×8, and average encryption and decryption times are 3.9771 s and 3.1447 s, respectively. Besides, we have found an equal distribution of pixels and less correlation coefficients among adjacent pixels of the encrypted image. These criteria indicate an efficient image encryption method. Also, our method is efficient and less complex than the existing state-of-the-art methods

Identification of fake news : a semantic driven technique for transfer domain

Fake news spreads quickly on online social media and adversely impacts political, social, religious, and economic stability. This necessitates an efficient fake news detector which is now feasible due to advances in natural language processing and artificial intelligence. However, existing fake news detection (FND) systems are built on tokenization, embedding, and structure-based feature extraction, and fail drastically in real life because of the difference in vocabulary and its distribution across various domains. This article evaluates the effectiveness of various categories of traditional features in cross-domain FND and proposes a new method. Our proposed method shows significant improvement over recent methods in the literature for cross-domain fake news detection in terms of widely used performance metrics. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd

Dynamics of Tree outside Forest Land Cover Development and Ecosystem Carbon Storage Change in Eastern Coastal Zone, Bangladesh

Tree outside forest (TOF) has immense potential in economic and environmental development by increasing the amount of tree vegetation in and around rural settlements. It is an important source of carbon stocks and a critical option for climate change regulation, especially in land-scarce, densely populated developing countries such as Bangladesh. Spatio-temporal changes of TOF in the eastern coastal zone of Bangladesh were analyzed and mapped over 1988–2018, using Landsat land use land cover (LULC) maps and associated ecosystem carbon storage change by linking the InVEST carbon model. Landsat TM and OLI-TIRS data were classified through the Maximum Likelihood Classifier (MLC) algorithm using Semi-Automated Classification (SAC). In the InVEST model, aboveground, belowground, dead organic matter, and soil carbon densities of different LULC types were used. The findings revealed that the studied landscapes have differential features and changing trends in LULC where TOF, mangrove forest, built-up land, and salt-aquaculture land have increased due to the loss of agricultural land, mudflats, water bodies, and hill vegetation. Among different land biomes, TOF experienced the largest increase (1453.9 km2), and it also increased carbon storage by 9.01 Tg C. However, agricultural land and hill vegetation decreased rapidly by 1285.8 km2 and 365.7 km2 and reduced carbon storage by 3.09 Tg C and 4.89 Tg C, respectively. The total regional carbon storage increased by 1.27 Tg C during 1988–2018. In addition to anthropogenic drivers, land erosion and accretion were observed to significantly alter LULC and regional carbon storage, necessitating effective river channel and coastal embankment management to minimize food and environmental security tradeoff in the studied landscape

Dynamics of Tree outside Forest Land Cover Development and Ecosystem Carbon Storage Change in Eastern Coastal Zone, Bangladesh

Tree outside forest (TOF) has immense potential in economic and environmental development by increasing the amount of tree vegetation in and around rural settlements. It is an important source of carbon stocks and a critical option for climate change regulation, especially in land-scarce, densely populated developing countries such as Bangladesh. Spatio-temporal changes of TOF in the eastern coastal zone of Bangladesh were analyzed and mapped over 1988–2018, using Landsat land use land cover (LULC) maps and associated ecosystem carbon storage change by linking the InVEST carbon model. Landsat TM and OLI-TIRS data were classified through the Maximum Likelihood Classifier (MLC) algorithm using Semi-Automated Classification (SAC). In the InVEST model, aboveground, belowground, dead organic matter, and soil carbon densities of different LULC types were used. The findings revealed that the studied landscapes have differential features and changing trends in LULC where TOF, mangrove forest, built-up land, and salt-aquaculture land have increased due to the loss of agricultural land, mudflats, water bodies, and hill vegetation. Among different land biomes, TOF experienced the largest increase (1453.9 km2), and it also increased carbon storage by 9.01 Tg C. However, agricultural land and hill vegetation decreased rapidly by 1285.8 km2 and 365.7 km2 and reduced carbon storage by 3.09 Tg C and 4.89 Tg C, respectively. The total regional carbon storage increased by 1.27 Tg C during 1988–2018. In addition to anthropogenic drivers, land erosion and accretion were observed to significantly alter LULC and regional carbon storage, necessitating effective river channel and coastal embankment management to minimize food and environmental security tradeoff in the studied landscape