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  • 1
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    Online Resource
    Evaluation of 130 Eggplant (Solanum melongena L.) Genotypes for Future Breeding Program Based on Qualitative and Quantitative Traits, and Various Genetic Parameters
    MDPI AG ; 2021
    In:  Horticulturae Vol. 7, No. 10 ( 2021-10-08), p. 376-
    Details
    In: Horticulturae, MDPI AG, Vol. 7, No. 10 ( 2021-10-08), p. 376-
    Abstract: Eggplant is an essential widespread year-round fruit vegetable. This study was conducted using 130 local germplasm of brinjal to select diverse parents based on the multiple traits selection index for the future breeding program. This selection was performed focusing on 14 qualitative and 10 quantitative traits variation and genetic parameters namely, phenotypic and genotypic variance (PV and GV) and genotypic and phenotypic coefficients of variation (GCV and PCV), broad-sense heritability (hBS), genetic advance, traits association, genotype by trait biplot (G × T), heatmap analysis and multi-trait index based on factor analysis and genotype-ideotype distance (MGIDI). Descriptive statistics and analysis of variance revealed a wide range of variability for morpho-physiological traits. Estimated hBS for all the measured traits ranged from 10.6% to 93%, indicating that all the traits were highly inheritable. Genetic variances were low to high for most morpho-physiological traits, indicating complex genetic architecture. Yield per plant was significantly correlated with fruit diameter, fruits per plant, percent fruits infestation by brinjal shoot and fruit borer, and fruit weight traits indicating that direct selection based on fruit number and fruit weight might be sufficient for improvement of other traits. The first two principal components (PCs) explained about 81.27% of the total variation among lines for 38 brinjal morpho-physiological traits. Genotype by trait (G × T) biplot revealed superior genotypes with combinations of favorable traits. The average genetic distance was 3.53, ranging from 0.25 to 20.01, indicating high levels of variability among the germplasm. The heat map was also used to know the relationship matrix among all the brinjal genotypes. MGIDI is an appropriate method of selection based on multiple trait information. Based on the fourteen qualitative and ten quantitative traits and evaluation of various genetic parameters, the germplasm G80, G54, G66, and G120 might be considered as best parents for the future breeding program for eggplant improvement.
    Type of Medium: Online Resource
    ISSN: 2311-7524
    URL: Article
    DOI: 10.3390/horticulturae7100376
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2813983-5
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  • 2
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    Causal Interaction between Foreign Direct Investment Inflows and China’s Economic Growth
    MDPI AG ; 2023
    In:  Sustainability Vol. 15, No. 10 ( 2023-05-13), p. 7994-
    Details
    In: Sustainability, MDPI AG, Vol. 15, No. 10 ( 2023-05-13), p. 7994-
    Abstract: This study examines the causal relationship between foreign direct investment (FDI) and economic growth in China over a 40-year period, from 1981 to 2020. Using a vector autoregressive (VAR) model, the study investigates the direction of causality between FDI and economic growth and finds that economic growth drives FDI inflows in China, rather than the other way around. The results suggest that policymakers should prioritize growth policies that foster sustainable economic expansion, rather than focusing solely on attracting FDI. The study contributes to the literature on the relationship between FDI and economic growth and highlights the importance of understanding the direction of causality between these two variables. Overall, these findings have important implications for policymakers seeking to promote economic growth and attract FDI to China.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su15107994
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518383-7
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  • 3
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    IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database
    MDPI AG ; 2023
    In:  Healthcare Vol. 11, No. 1 ( 2023-01-01), p. 139-
    Details
    In: Healthcare, MDPI AG, Vol. 11, No. 1 ( 2023-01-01), p. 139-
    Abstract: In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data.
    Type of Medium: Online Resource
    ISSN: 2227-9032
    URL: Article
    DOI: 10.3390/healthcare11010139
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2721009-1
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  • 4
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    Evaluation of Inbred Maize (Zea mays L.) for Tolerance to Low Phosphorus at the Seedling Stage
    MDPI AG ; 2023
    In:  Plants Vol. 12, No. 13 ( 2023-06-30), p. 2520-
    Details
    In: Plants, MDPI AG, Vol. 12, No. 13 ( 2023-06-30), p. 2520-
    Abstract: In underdeveloped nations where low-input agriculture is practiced, low phosphorus (LP) in the soil reduces the production of maize. In the present study, a total of 550 inbred maize lines were assessed for seedling traits under LP (2.5 × 10−6 mol L−1 of KH2PO4) and NP (2.5 × 10−4 mol L−1 of KH2PO4) hydroponic conditions. The purpose of this study was to quantify the amount of variation present in the measured traits, estimate the genetic involvement of these characteristics, examine the phenotypic correlation coefficients between traits, and to integrate this information to prepare a multi-trait selection index for LP tolerance in maize. A great deal of variability in the maize genotype panel was confirmed by descriptive statistics and analysis of variance (ANOVA). Estimated broad-sense heritability (h2) ranged from 0.7 to 0.91, indicating intermediate to high heritability values for the measured traits. A substantial connection between MSL and other root traits suggested that the direct selection of MSL (maximum shoot length) could be beneficial for the enhancement of other traits. The principal component analysis (PCA) of the first two main component axes explained approximately 81.27% of the variation between lines for the eight maize seedling variables. TDM (total dry matter), SDW (shoot dry weight), RDW (root dry weight), SFW (shoot fresh weight), RFW (root fresh weight), MRL (maximum root length), and MSL measurements accounted for the majority of the first principal component (59.35%). The multi-trait indices were calculated based on PCA using all the measured traits, and 30 genotypes were selected. These selected lines might be considered as the potential source for the improvement of LP tolerance in maize.
    Type of Medium: Online Resource
    ISSN: 2223-7747
    URL: Article
    DOI: 10.3390/plants12132520
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704341-1
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  • 5
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    High-Throughput Root Network System Analysis for Low Phosphorus Tolerance in Maize at Seedling Stage
    MDPI AG ; 2021
    In:  Agronomy Vol. 11, No. 11 ( 2021-11-03), p. 2230-
    Details
    In: Agronomy, MDPI AG, Vol. 11, No. 11 ( 2021-11-03), p. 2230-
    Abstract: The root system is the important organ of a plant, helping to anchor the plant and take up nutrients from the soil. The purpose of this investigation was to determine the magnitude of the root network system (RNS) through phenotypic variability in a broad range of maize inbred lines. The GiA Root software was used to identify root attributes from images. After germination, the inbred lines were grown hydroponically for 15 days in a high-lux plant growth room with low phosphorus (LP) and normal phosphorus (NP) treatments. Variance analysis revealed a large range of variability present among the inbred lines, with intermediate to high heritabilities ranging from 0.59 to 0.95 for all RNS traits, demonstrating uniformity through the experiments. The proportions of genetic variance ranged from 0.01–0.60 in different maize RNS traits. A strong positive linear relationship between best linear unbiased predictors (BLUPs) with estimated means was found for all the RNS traits. The Euclidean genetic distances between the studied inbred lines ranged from 0.61 to 29.33, showing a higher amount of diversity. More than 79% of the overall genetic variation was explained by the first three principal components, with high loadings from the measurements of network length (NWL), network surface area (NWSA), network perimeter (NWP), network area (NWA), the maximum number of roots (MANR), median number of roots (MENR), network volume (NWV), network convex area (NWCA), specific root length (SRL), network depth (NWD), number of connected components (NCC), and network width (NWW). The biplot of genotype by trait interaction exposed superior genotypes with a relatively high expression of favorable trait combinations. Some outstanding genotypes with higher values of most RNS traits were identified through MGIDI analysis. These lines may be convenient for enhancing LP tolerance in maize.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy11112230
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2607043-1
    SSG: 23
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  • 6
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    Detection of Distributed Denial of Service (DDoS) Attacks in IOT Based Monitoring System of Banking Sector Using Machine Learning Models
    MDPI AG ; 2022
    In:  Sustainability Vol. 14, No. 14 ( 2022-07-08), p. 8374-
    Details
    In: Sustainability, MDPI AG, Vol. 14, No. 14 ( 2022-07-08), p. 8374-
    Abstract: Cyberattacks can trigger power outages, military equipment problems, and breaches of confidential information, i.e., medical records could be stolen if they get into the wrong hands. Due to the great monetary worth of the data it holds, the banking industry is particularly at risk. As the number of digital footprints of banks grows, so does the attack surface that hackers can exploit. This paper aims to detect distributed denial-of-service (DDOS) attacks on financial organizations using the Banking Dataset. In this research, we have used multiple classification models for the prediction of DDOS attacks. We have added some complexity to the architecture of generic models to enable them to perform well. We have further applied a support vector machine (SVM), K-Nearest Neighbors (KNN) and random forest algorithms (RF). The SVM shows an accuracy of 99.5%, while KNN and RF scored an accuracy of 97.5% and 98.74%, respectively, for the detection of (DDoS) attacks. Upon comparison, it has been concluded that the SVM is more robust as compared to KNN, RF and existing machine learning (ML) and deep learning (DL) approaches.
    Type of Medium: Online Resource
    ISSN: 2071-1050
    URL: Article
    DOI: 10.3390/su14148374
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518383-7
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  • 7
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    Progressive Genomic Approaches to Explore Drought- and Salt-Induced Oxidative Stress Responses in Plants under Changing Climate
    MDPI AG ; 2021
    In:  Plants Vol. 10, No. 9 ( 2021-09-14), p. 1910-
    Details
    In: Plants, MDPI AG, Vol. 10, No. 9 ( 2021-09-14), p. 1910-
    Abstract: Drought and salinity are the major environmental abiotic stresses that negatively impact crop development and yield. To improve yields under abiotic stress conditions, drought- and salinity-tolerant crops are key to support world crop production and mitigate the demand of the growing world population. Nevertheless, plant responses to abiotic stresses are highly complex and controlled by networks of genetic and ecological factors that are the main targets of crop breeding programs. Several genomics strategies are employed to improve crop productivity under abiotic stress conditions, but traditional techniques are not sufficient to prevent stress-related losses in productivity. Within the last decade, modern genomics studies have advanced our capabilities of improving crop genetics, especially those traits relevant to abiotic stress management. This review provided updated and comprehensive knowledge concerning all possible combinations of advanced genomics tools and the gene regulatory network of reactive oxygen species homeostasis for the appropriate planning of future breeding programs, which will assist sustainable crop production under salinity and drought conditions.
    Type of Medium: Online Resource
    ISSN: 2223-7747
    URL: Article
    DOI: 10.3390/plants10091910
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704341-1
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  • 8
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    Trends in Complementary Feeding Indicators and Intake from Specific Food Groups among Children Aged 6–23 Months in Bangladesh
    MDPI AG ; 2022
    In:  International Journal of Environmental Research and Public Health Vol. 19, No. 1 ( 2022-01-04), p. 550-
    Details
    In: International Journal of Environmental Research and Public Health, MDPI AG, Vol. 19, No. 1 ( 2022-01-04), p. 550-
    Abstract: The present study aims to comprehensively analyse trends in complementary feeding indicators (Introduction of solid, semi-solid, and soft foods at 6–8 months (INTRO), Minimum Dietary Diversity (MDD), Minimum Meal Frequency (MMF) and Minimum Acceptable Diet (MAD)) among children aged 6–23 months in Bangladesh. The study used data from four rounds (2007, 2011, 2014, and 2017–2018) of nationally representative Bangladesh Demographic and Health Surveys (BDHSs). The Cochran–Armitage test was performed to capture the trends in complementary feeding practices and intake from specific food groups. BDHSs are periodically conducted cross-sectional surveys in all seven administrative divisions of Bangladesh. The present analysis was performed among 8116 children (1563 in 2007, 2137 in 2011, 2249 in 2014, and 2167 in 2017–2018) aged 6–23 months. Overall, a decreasing trend was observed in all the complementary feeding indicators except INTRO from 2007 to 2014, but a substantial increase in MDD, MMF and MAD was noted in 2017–2018. A statistically significant reduction in consumption from different food groups such as legumes and nuts (p 〈 0.001), dairy products (p = 0.001), vitamin-A-rich fruits or vegetables (p 〈 0.001), and other fruits and vegetables (p 〈 0.001) was also observed. However, a positive trend was noted in the consumption of grains/roots/tubers (p = 0.027), and meat/fish/egg (p 〈 0.001). After experiencing a significant decreasing trend during 2007–2014, the recent BDHS indicates improvements in all complementary feeding indicators among young children in Bangladesh, which calls for integrated, multisectoral, and multicomponent interventions to sustain this progress.
    Type of Medium: Online Resource
    ISSN: 1660-4601
    URL: Article
    DOI: 10.3390/ijerph19010550
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2175195-X
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  • 9
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    Prediction of Fruit Maturity, Quality, and Its Life Using Deep Learning Algorithms
    MDPI AG ; 2022
    In:  Electronics Vol. 11, No. 24 ( 2022-12-09), p. 4100-
    Details
    In: Electronics, MDPI AG, Vol. 11, No. 24 ( 2022-12-09), p. 4100-
    Abstract: Fruit that has reached maturity is ready to be harvested. The prediction of fruit maturity and quality is important not only for farmers or the food industry but also for small retail stores and supermarkets where fruits are sold and purchased. Fruit maturity classification is the process by which fruits are classified according to their maturity in their life cycle. Nowadays, deep learning (DL) has been applied in many applications of smart agriculture such as water and soil management, crop planting, crop disease detection, weed removal, crop distribution, strong fruit counting, crop harvesting, and production forecasting. This study aims to find the best deep learning algorithms which can be used for the prediction of fruit maturity and quality for the shelf life of fruit. In this study, two datasets of banana fruit are used, where we create the first dataset, and the second dataset is taken from Kaggle, named Fruit 360. Our dataset contains 2100 images in 3 categories: ripe, unripe, and over-ripe, each of 700 images. An image augmentation technique is used to maximize the dataset size to 18,900. Convolutional neural networks (CNN) and AlexNet techniques are used for building the model for both datasets. The original dataset achieved an accuracy of 98.25% for the CNN model and 81.75% for the AlexNet model, while the augmented dataset achieved an accuracy of 99.36% for the CNN model and 99.44% for the AlexNet model. The Fruit 360 dataset achieved an accuracy of 81.96% for CNN and 81.75% for the AlexNet model. We concluded that for all three datasets of banana images, the proposed CNN model is the best suitable DL algorithm for bananas’ fruit maturity classification and quality detection.
    Type of Medium: Online Resource
    ISSN: 2079-9292
    URL: Article
    DOI: 10.3390/electronics11244100
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2662127-7
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  • 10
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    Groundwater Quality of Some Parts of Coastal Bhola District, Bangladesh: Exceptional Evidence
    MDPI AG ; 2023
    In:  Urban Science Vol. 7, No. 3 ( 2023-07-03), p. 71-
    Details
    In: Urban Science, MDPI AG, Vol. 7, No. 3 ( 2023-07-03), p. 71-
    Abstract: The composition of groundwater governs the drinking and irrigation water suitability. A large part of the coastal region of Bangladesh is affected and is responsible for changing the composition of the groundwater. This research attempted to observe the groundwater quality of the Bhola Sadar and Char Fasson upazilas in coastal Bangladesh. Twenty-eight (28) water samples, 27 at depths of 260–430 m (850–1400 ft) and 1 from a crop field, were collected and analyzed. The quality of water samples was determined through the evaluation of odor, color, turbidity, electrical conductivity, pH, total dissolved solids, nitrate (NO3−), ammonium (NH4+), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), iron (Fe), manganese (Mn), copper (Cu), zinc (Zn) and arsenic (As) ions. An Atomic Absorption Spectrophotometer was used for heavy metal analysis. The outcomes were compared with the drinking water quality of Bangladesh and the World Health Organization. The results showed that the average values of nearly all of the parameters were underneath or within the standard level, representing that the groundwater was appropriate for drinking purposes. The water quality parameters were also compared with the irrigation water quality of Bangladesh and the Food and Agriculture Organization. It was found that the collected samples were also suitable for irrigation. To do this, the soluble sodium percentage, sodium adsorption ratio, magnesium adsorption ratio, Kelley’s ratio, and total hardness were calculated. The novelty of this research is that, despite being in a coastal district, the deep aquifer water of Bhola was appropriate for drinking and irrigation purposes.
    Type of Medium: Online Resource
    ISSN: 2413-8851
    URL: Article
    DOI: 10.3390/urbansci7030071
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2893596-2
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