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  • 1
    In: Environmental Pollution, Elsevier BV, Vol. 314 ( 2022-12), p. 120237-
    Type of Medium: Online Resource
    ISSN: 0269-7491
    RVK:
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 280652-6
    detail.hit.zdb_id: 2013037-5
    SSG: 12
    SSG: 14
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  • 2
    Online Resource
    Online Resource
    ZIbeline International Publishing ; 2021
    In:  Journal CleanWAS Vol. 5, No. 1 ( 2021-03-31), p. 27-30
    In: Journal CleanWAS, ZIbeline International Publishing, Vol. 5, No. 1 ( 2021-03-31), p. 27-30
    Abstract: Copper Oxide nanoparticles (NPs) have shown great acceptance in the antimicrobial application owing to their low toxicity and high surface to charge ratio. In this study, copper oxide NPs (represented as S-1, S-2 and S-3) were prepared by a simple and cost-effective thermal approach in three different environments. Fabricated NPs were characterized using x-ray diffraction (XRD), scanning electron microscopy (SEM), ultraviolet-visible (UV-Vis) spectroscopy and Fourier transform infrared spectroscopy (FTIR) technique. The XRD patterns revealed that the synthesized S-2 was of pure Cu2O phase while S-3 was composed of monoclinic CuO with a small quantity of Cu2O. More importantly, synthesized copper oxide NPs were used to evaluate the antimicrobial activity against three types of gram-negative bacteria namely Salmonella typhi, SK4 and E. coli (two strains). Although the NPs produced from the S-1 approach did not show encouraging results, the copper oxide NPs from S-2 and S-3 had shown enhanced antimicrobial activity. The successful antimicrobial activity of S-2 and S-3 can be related to the release of Cu+ and Cu2+ ions into the surrounding environment, which is responsible for the breaking of the cell wall membrane and ultimately causes bacterial cell disruption. The synthesized copper oxide NPs via thermal approach will be good candidates for biomedical applications.
    Type of Medium: Online Resource
    ISSN: 2521-0912 , 2521-0513
    Language: Unknown
    Publisher: ZIbeline International Publishing
    Publication Date: 2021
    detail.hit.zdb_id: 2975570-0
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  • 3
    In: Life, MDPI AG, Vol. 12, No. 11 ( 2022-10-27), p. 1719-
    Abstract: Legumes, including lentil, are a valuable source of carbohydrates, fiber, protein and vitamins and minerals. Their nutritional characteristics have been associated with a reduction in the incidence of various cancers, HDL cholesterol, type 2 diabetes and heart disease. Among these quality parameters, lectins have been associated with reducing certain forms of cancer, activating innate defense mechanisms and managing obesity. Protease inhibitors such as trypsin and chymotrypsin inhibitors have been demonstrated to reduce the incidence of certain cancers and demonstrate potent anti-inflammatory properties. Angiotensin I-converting enzyme (ACE) inhibitor has been associated with a reduction in hypertension. Therefore, legumes, including lentils, should be part of our daily food intake. However, high temperatures at the terminal stage is a major abiotic constraint leading to a reduction in lentil yield and seed quality. Thus, the selection of heat-tolerant genotypes is essential to identifying the potential for high yields with stable performance. To select lentil genotypes, an experiment was conducted with 60 genotypes including local landraces, advanced breeding lines, commercial varieties and exotic germplasm under stress and non-stress conditions from 2019 to 2020. This study was followed by a subset study involving screening based on a few physicochemical parameters and reproductive traits along with field performances. Different tolerance indices (i.e., stress susceptible index (SSI), relative heat index (RHI), tolerance (TOL), mean productivity (MP), stress tolerance index (STI), geometric mean productivity (GMP), yield index (YI), yield stability index (YSI), heat-resistance index (HRI), modified stress-tolerance index (MSTI), abiotic tolerance index (ATI) and stress susceptibility percentage (SSPI)) were used for the selection of the genotypes along with field performance. Biplot analysis was further performed for choosing the most suitable indices. Based on principal components analysis, the GMP, MP, RRI, STI, YI, YSI, ATI and MSTI indices were identified as the most reliable stress indicators, and these indicators might be used for distinguishing heat-tolerant genotypes. Based on the stress indices, the genotypes BLX 05002-3, BLX 10002-20, LRIL-21-1-1-1-1, LRIL-21-1-1-1-1-6 and BLX 09015 were selected as the most stable and heat-tolerant genotypes. In contrast, the genotypes LG 198, Bagura Local, BLX 0200-08-4, RL-12-178, Maitree, 91517 and BLX 11014-8 were selected as the most heat sensitive. Data also exhibited an average yield reduction of 59% due to heat stress on the lentils. Moreover, eight heat-tolerant (HT) genotypes (BLX 09015, PRECOZ, LRL-21-112-1-1-1-1-6, BLX 05002-3, LR-9-25, BLX 05002-6, BARI Masur-8 and RL-12-181), and two heat-susceptible (HS) genotypes (BLX 12009-6, and LG 198) were selected from the screened genotypes and subjected to further analysis by growing them in the following year under similar conditions to investigate the mechanisms associated with heat tolerance. Comparative studies on reproductive function and physiochemical traits revealed significantly higher pollen viability, proline accumulation, relative water content, chlorophyll concentration and a lower membrane stability index in HT genotypes under heat stress. Therefore, these heat-tolerant genotypes could be used as the parents in the hybridization program for achieving heat-tolerant transgressive segregation.
    Type of Medium: Online Resource
    ISSN: 2075-1729
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662250-6
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  • 4
    In: Soil Systems, MDPI AG, Vol. 7, No. 2 ( 2023-04-20), p. 41-
    Abstract: Adoption of the right rice variety and water-saving irrigation method could reduce greenhouse gas (GHG) emissions in lowland rice cultivation. A study was conducted at the research farm of Bangladesh Agricultural University, Mymensingh, Bangladesh, in 2019 during the Boro (dry) season to determine the impacts of different rice varieties (BRRI dhan29, BRRI dhan47, BRRI dhan69, Binadhan-8, Binadhan-10, and Binadhan-17) on methane (CH4) emissions under two irrigation methods, i.e., alternate wetting and drying (AWD) and continuous flooding (CF). The treatments were laid out in a split-plot design, considering water regime as the main plots and rice variety as the sub-plots. The emission rates of CH4 were determined by collecting air samples using the closed chamber technique and measuring the concentrations using a gas chromatograph. CH4 emission rates varied with the growth and development of the rice varieties. The lowest cumulative CH4 emission rate was observed in Binadhan-17, particularly under AWD irrigation. Across the rice varieties, AWD irrigation significantly reduced the cumulative CH4 emissions by about 35% compared with CF. No significant variation in rice yield was observed between AWD (5.38 t ha−1) and CF (5.16 t ha−1). This study suggests that the cultivation of Binadhan-17 under AWD irrigation could be effective at reducing the carbon footprint of lowland rice fields.
    Type of Medium: Online Resource
    ISSN: 2571-8789
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2932897-4
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  • 5
    In: Reproduction and Breeding, Elsevier BV, Vol. 1, No. 2 ( 2021-06), p. 100-107
    Type of Medium: Online Resource
    ISSN: 2667-0712
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2021
    detail.hit.zdb_id: 3093261-0
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  • 6
    Online Resource
    Online Resource
    American Society of Tropical Medicine and Hygiene ; 2022
    In:  The American Journal of Tropical Medicine and Hygiene Vol. 107, No. 2 ( 2022-08-17), p. 449-456
    In: The American Journal of Tropical Medicine and Hygiene, American Society of Tropical Medicine and Hygiene, Vol. 107, No. 2 ( 2022-08-17), p. 449-456
    Abstract: Secretor status refers to the ability of an individual to secrete blood group antigens into body fluids and onto the different epithelial surfaces. Concurrent findings have demonstrated an association of the secretor status of children with susceptibility to a plethora of enteropathogens. We aimed to determine a possible association of secretor status of children with childhood enteropathy, an important causal factor for childhood growth failure. Participants of the Malnutrition and Enteric Disease (MAL-ED) birth cohort study from the Bangladesh site were enrolled along with their mothers. Saliva was analyzed for determining blood groups and secretor status of the children and their mothers by using an in-house ELISA. Approximately 59% of children and 65% of mothers were found to be secretor positive. Secretor-positive children were found to have a significantly positive association with alpha-1-antitrypsin (β-coefficient: 0.11, 95% CI: 0.07, 0.21, P 〈 0.01) and with environmental enteric dysfunction score (β-coefficient: 0.32, 95% CI: 0.29, 0.65, P = 0.05). However, despite a negative effect size, secretor-positive children did not show any statistical significance with length-for-age and weight-for-age z scores (LAZ and WAZ), respectively. Our findings indicate toward the genetic factor of secretor status of children being associated with childhood growth faltering, through increased susceptibility to distinct enteropathogens and the consequent development of enteric inflammation and enteropathy among children. However, these findings are only applicable in Bangladeshi settings and thus need to be validated in several other similar settings, to establish a possible relationship between the secretor status of children with enteropathy and resulting childhood growth failure.
    Type of Medium: Online Resource
    ISSN: 0002-9637 , 1476-1645
    Language: Unknown
    Publisher: American Society of Tropical Medicine and Hygiene
    Publication Date: 2022
    detail.hit.zdb_id: 1491674-5
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  • 7
    In: Applied Sciences, MDPI AG, Vol. 12, No. 20 ( 2022-10-18), p. 10505-
    Abstract: An inset fed-microstrip patch antenna (MPA) with a partial ground structure is constructed and evaluated in this paper. This article covers how to evaluate the performance of the designed antenna by using a combination of simulation, measurement, creation of the RLC equivalent circuit model, and the implementation of machine learning approaches. The MPA’s measured frequency range is 7.9–14.6 GHz, while its simulated frequency range is 8.35–14.25 GHz in CST microwave studio (CST MWS) 2018. The measured and simulated bandwidths are 6.7 GHz and 5.9 GHz, respectively. The antenna substrate is composed of FR-4 Epoxy, which has a dielectric constant of 4.4 and a loss tangent of 0.02. The equivalent model of the proposed MPA is developed by using an advanced design system (ADS) to compare the resonance frequencies obtained by using CST. In addition, the measured return loss of the prototype is compared with the simulated return loss observed by using CST and ADS. At the end, 86 data samples are gathered through the simulation by using CST MWS, and seven machine learning (ML) approaches, such as convolutional neural network (CNN), linear regression (LR), random forest regression (RFR), decision tree regression (DTR), lasso regression, ridge regression, and extreme gradient boosting (XGB) regression, are applied to estimate the resonant frequency of the patch antenna. The performance of the seven ML models is evaluated based on mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and variance score. Among the seven ML models, the prediction result of DTR (MSE = 0.71%, MAE = 5.63%, RMSE = 8.42%, and var score = 99.68%) is superior to other ML models. In conclusion, the proposed antenna is a strong contender for operating at the entire X-band and lower portion of the Ku-band frequencies, as evidenced by the simulation results through CST and ADS, it measured and predicted results using machine learning approaches.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2704225-X
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  • 8
    In: BMC Public Health, Springer Science and Business Media LLC, Vol. 21, No. 1 ( 2021-12)
    Abstract: Poor growth in early childhood has been considered irreversible after 2–3 years of age and has been associated with morbidity and mortality over the short-term and with poor economic and cognitive outcomes over the long-term. The MAL-ED cohort study was performed in eight low-income settings with the goal of evaluating relationships between the child’s environment and experience (dietary, illness, and pathogen exposure, among others) and their growth and development. The goal of this analysis is to determine whether there are differences in the factors associated with growth from 24 to 60 months using two different metrics. Methods Across six MAL-ED sites, 942 children had anthropometry data at 24 and 60 months, as well as information about socioeconomic status, maternal height, gut permeability (lactulose-mannitol z-score (LMZ)), dietary intake from 9 to 24 months, and micronutrient status. Anthropometric changes were in height- or weight-for-age z-score (HAZ, WAZ), their absolute difference from the growth standard median (HAD (cm), WAD (kg)), as well as recovery from stunting/underweight. Outcomes were modeled using multivariate regression. Results At 24 months, almost half of the cohort was stunted (45%) and 21% were underweight. Among those who were stunted at 24 months ( n  = 426), 185 (43%) were no longer stunted at 60 months. Most children increased their HAZ from 24 to 60 months (81%), whereas fewer (33%) had positive changes in their HAD. Linear regression models indicate that girls improved less than boys from 24 to 60 months (HAZ: -0.21 (95% CI -0.27, -0.15); HAD: -0.75 (-1.07, -0.43)). Greater intestinal permeability (higher LMZ) at 0–24 months was associated with lower relative and absolute changes from 24 to 60 months (HAZ: -0.10 (-0.16, -0.04); HAD: -0.47 (-0.73, -0.21)). Maternal height (per 10 cm) was positively associated with changes (HAZ: 0.09 (0.03, 0.15); HAD: 0.45 (0.15, 0.75)). Similar relationships were identified for changes in WAZ and WAD. Conclusions The study children demonstrated improved growth from 24 to 60 months of age, but only a subset had positive changes in HAD and WAD. The same environmental factors were associated with growth from 24 to 60 months regardless of metric used (change in HAZ or HAD, or WAZ and WAD).
    Type of Medium: Online Resource
    ISSN: 1471-2458
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2041338-5
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  • 9
    In: Scientific Reports, Springer Science and Business Media LLC, Vol. 13, No. 1 ( 2023-08-03)
    Abstract: In this study, we present our findings from investigating the use of a machine learning (ML) technique to improve the performance of Quasi-Yagi–Uda antennas operating in the n78 band for 5G applications. This research study investigates several techniques, such as simulation, measurement, and an RLC equivalent circuit model, to evaluate the performance of an antenna. In this investigation, the CST modelling tools are used to develop a high-gain, low-return-loss Yagi–Uda antenna for the 5G communication system. When considering the antenna’s operating frequency, its dimensions are $${0.642}\lambda _0\times {0.583}\lambda _0$$ 0.642 λ 0 × 0.583 λ 0 . The antenna has an operating frequency of 3.5 GHz, a return loss of $$-43.45$$ - 43.45 dB, a bandwidth of 520 MHz, a maximum gain of 6.57 dB, and an efficiency of almost 97%. The impedance analysis tools in CST Studio’s simulation and circuit design tools in Agilent ADS software are used to derive the antenna’s equivalent circuit (RLC). We use supervised regression ML method to create an accurate prediction of the frequency and gain of the antenna. Machine learning models can be evaluated using a variety of measures, including variance score, R square, mean square error, mean absolute error, root mean square error, and mean squared logarithmic error. Among the nine ML models, the prediction result of Linear Regression is superior to other ML models for resonant frequency prediction, and Gaussian Process Regression shows an extraordinary performance for gain prediction. R-square and var score represents the accuracy of the prediction, which is close to 99% for both frequency and gain prediction. Considering these factors, the antenna can be deemed an excellent choice for the n78 band of a 5G communication system.
    Type of Medium: Online Resource
    ISSN: 2045-2322
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2615211-3
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  • 10
    In: BMC Research Notes, Springer Science and Business Media LLC, Vol. 10, No. 1 ( 2017-12)
    Type of Medium: Online Resource
    ISSN: 1756-0500
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2017
    detail.hit.zdb_id: 2413336-X
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