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  • 1
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    Online Resource
    Impacts of Drought Stress on Water Use Efficiency and Grain Productivity of Rice and Utilization of Genotypic Variability to Combat Climate Change
    MDPI AG ; 2022
    In:  Agronomy Vol. 12, No. 10 ( 2022-10-15), p. 2518-
    Details
    In: Agronomy, MDPI AG, Vol. 12, No. 10 ( 2022-10-15), p. 2518-
    Abstract: Rice is an important cereal and drought stress is a critical abiotic stress that negatively influences the performance and productivity of rice crop, particularly under a changing climate scenario. The objectives of this study were to evaluate the impacts of drought stress on grain productivity and water use efficiency of rice cultivars and to assess the genotypic variability among the tested cultivars. Two irrigation treatments including a control and drought stress were applied to the experiments during 2018–2019 and 2019–2020. The statistical evaluation included a comparison of means, genotypic and phenotypic coefficients of variation, path analysis, correlation assessment, hierarchical clustering of tested cultivars and principal component analysis. The results indicated that drought stress negatively affected the grain productivity of the rice cultivars. The grain productivity of the cultivars decreased, ranging between 21–45% and 21–52% in the first and second season, respectively. Similarly, water use efficiency was significantly decreased ranging between 7–53% and 21–55% during the first and the second season, respectively. The broad-sense heritability for grain productivity was differed under control and drought stress treatment, indicating that the chances of the transfer of grain-productivity-related traits could be affected during selection for stress tolerance. The correlation assessment indicated that the intensity of association among the evaluated parameters was higher under the control treatment. A maximum direct effect was observed by water consumption (1.76) under control whereas, by water use efficiency (1.09) under drought stress treatment on grain productivity in path analysis. Considering the water use efficiency as a desired trait for selection in path analysis, a maximum direct effect was observed by grain productivity under the control (0.68) and under drought treatment (0.88). Hom Pathum and Pathum Thani−1 were identified as highly tolerant cultivars in the hierarchical clustering and principal component analysis. It was concluded that the results obtained for the assessment of drought stress on grain productivity, water use efficiency and genotypic variability among these cultivars could be utilized in selection program for stress tolerance and the stress tolerant cultivars could be used for sustaining grain productivity to reduce the impacts of climate change.
    Type of Medium: Online Resource
    ISSN: 2073-4395
    URL: Article
    DOI: 10.3390/agronomy12102518
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2607043-1
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  • 2
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    The Design of a Wideband Antenna with Notching Characteristics for Small Devices Using a Genetic Algorithm
    MDPI AG ; 2021
    In:  Mathematics Vol. 9, No. 17 ( 2021-09-01), p. 2113-
    Details
    In: Mathematics, MDPI AG, Vol. 9, No. 17 ( 2021-09-01), p. 2113-
    Abstract: This paper presents the design and realization of a compact printed ultra-wideband (UWB) antenna with notching characteristics for compact devices using a genetic algorithm. The antenna is capable of mitigating an adjacent sub-band ranging from 3.75 to 4.875 GHz, mainly used by many applications and standards such as WiMAX, WLAN and sub-6-GHz. The notch band functionality is achieved by etching out two symmetrical slots from the pentagonal radiating element. The simulation and measured results demonstrate that the proposed antenna overperformed compared with state-of-the-art antennas in terms of compactness with an overall size of 20 mm×15 mm×0.508 mm. Moreover, the proposed design shows a large bandwidth in the UWB region with a fractional bandwidth of 180% with respect to the center frequency of 5.25 GHz. The antenna also presents omnidirectional radiations all over the operation band and a good return loss performance.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math9172113
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704244-3
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  • 3
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    Low-Profile Antenna System for Cognitive Radio in IoST CubeSat Applications
    MDPI AG ; 2023
    In:  Sensors Vol. 23, No. 10 ( 2023-05-16), p. 4782-
    Details
    In: Sensors, MDPI AG, Vol. 23, No. 10 ( 2023-05-16), p. 4782-
    Abstract: Since the CubeSats have become inherently used for the Internet of space things (IoST) applications, the limited spectral band at the ultra-high frequency (UHF) and very high frequency should be efficiently utilized to be sufficient for different applications of CubeSats. Therefore, cognitive radio (CR) has been used as an enabling technology for efficient, dynamic, and flexible spectrum utilization. So, this paper proposes a low-profile antenna for cognitive radio in IoST CubeSat applications at the UHF band. The proposed antenna comprises a circularly polarized wideband (WB) semi-hexagonal slot and two narrowband (NB) frequency reconfigurable loop slots integrated into a single-layer substrate. The semi-hexagonal-shaped slot antenna is excited by two orthogonal +/−45° tapered feed lines and loaded by a capacitor in order to achieve left/right-handed circular polarization in wide bandwidth from 0.57 GHz to 0.95 GHz. In addition, two NB frequency reconfigurable slot loop-based antennas are tuned over a wide frequency band from 0.6 GHz to 1.05 GH. The antenna tuning is achieved based on a varactor diode integrated into the slot loop antenna. The two NB antennas are designed as meander loops to miniaturize the physical length and point in different directions to achieve pattern diversity. The antenna design is fabricated on FR-4 substrate, and measured results have verified the simulated results.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s23104782
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2052857-7
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  • 4
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    Delineating Novel and Known Pathogenic Variants in TYR, OCA2 and HPS-1 Genes in Eight Oculocutaneous Albinism (OCA) Pakistani Families
    MDPI AG ; 2022
    In:  Genes Vol. 13, No. 3 ( 2022-03-12), p. 503-
    Details
    In: Genes, MDPI AG, Vol. 13, No. 3 ( 2022-03-12), p. 503-
    Abstract: Oculocutaneous albinism (OCA) is associated with a wide range of clinical presentations and has been categorized with syndromic and non-syndromic features. The most common causative genes in non-syndromic OCA are TYR and OCA2 and HSP1 is in the syndromic albinism. The objective of this study was to identify pathogenic variants in congenital OCA families from Pakistan. Eight consanguineous families were recruited, and clinical and ophthalmological examination was carried out to diagnose the disease. Whole blood was collected from the participating individuals, and genomic DNA was extracted for sequencing analysis. TruSight one-panel sequencing was carried out on one affected individual of each family, and termination Sanger sequencing was carried out to establish the co-segregation of the causative gene or genes. In silico analysis was conducted to predict the causative pathogenic variants. Two families were found to have novel genetic pathogenic variants, and six families harbored previously reported variants. One novel compound heterozygous pathogenic variant in the TYR gene, c.1002delA; p.Ala335LeufsTer20, a novel frameshift deletion pathogenic variant and c.832C 〉 T; and p.Arg278Ter (a known pathogenic variant) were found in one family, whereas HPS1; c.437G 〉 A; and p.Trp146Ter were detected in another family. The identification of new and previous pathogenic variants in TYR, OCA2, and HPS1 genes are causative of congenital OCA, and these findings are expanding the heterogeneity of OCA.
    Type of Medium: Online Resource
    ISSN: 2073-4425
    URL: Article
    DOI: 10.3390/genes13030503
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527218-4
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  • 5
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    Recognition of Student Engagement State in a Classroom Environment Using Deep and Efficient Transfer Learning Algorithm
    MDPI AG ; 2023
    In:  Applied Sciences Vol. 13, No. 15 ( 2023-07-26), p. 8637-
    Details
    In: Applied Sciences, MDPI AG, Vol. 13, No. 15 ( 2023-07-26), p. 8637-
    Abstract: A student’s engagement in a real classroom environment usually varies with respect to time. Moreover, both genders may also engage differently during lecture procession. Previous research measures students’ engagement either from the assessment outcome or by observing their gestures in online or real but controlled classroom environments with limited students. However, most works either manually assess the engagement level in online class environments or use limited features for automatic computation. Moreover, the demographic impact on students’ engagement in the real classroom environment is limited and needs further exploration. This work is intended to compute student engagement in a real but least controlled classroom environment with 45 students. More precisely, the main contributions of this work are twofold. First, we proposed an efficient transfer-learning-based VGG16 model with extended layer, and fine-tuned hyperparameters to compute the students’ engagement level in a real classroom environment. Overall, 90% accuracy and 0.5 N seconds computational time were achieved in terms of computation for engaged and non-engaged students. Subsequently, we incorporated inferential statistics to measure the impact of time while performing 14 experiments. We performed six experiments for gender impact on students’ engagement. Overall, inferential analysis reveals the positive impact of time and gender on students’ engagement levels in a real classroom environment. The comparisons were also performed by various transfer learning algorithms. The proposed work may help to improve the quality of educational content delivery and decision making for educational institutions.
    Type of Medium: Online Resource
    ISSN: 2076-3417
    URL: Article
    DOI: 10.3390/app13158637
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2704225-X
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  • 6
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    An Ensemble Model for Consumer Emotion Prediction Using EEG Signals for Neuromarketing Applications
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 24 ( 2022-12-12), p. 9744-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 24 ( 2022-12-12), p. 9744-
    Abstract: Traditional advertising techniques seek to govern the consumer’s opinion toward a product, which may not reflect their actual behavior at the time of purchase. It is probable that advertisers misjudge consumer behavior because predicted opinions do not always correspond to consumers’ actual purchase behaviors. Neuromarketing is the new paradigm of understanding customer buyer behavior and decision making, as well as the prediction of their gestures for product utilization through an unconscious process. Existing methods do not focus on effective preprocessing and classification techniques of electroencephalogram (EEG) signals, so in this study, an effective method for preprocessing and classification of EEG signals is proposed. The proposed method involves effective preprocessing of EEG signals by removing noise and a synthetic minority oversampling technique (SMOTE) to deal with the class imbalance problem. The dataset employed in this study is a publicly available neuromarketing dataset. Automated features were extracted by using a long short-term memory network (LSTM) and then concatenated with handcrafted features like power spectral density (PSD) and discrete wavelet transform (DWT) to create a complete feature set. The classification was done by using the proposed hybrid classifier that optimizes the weights of two machine learning classifiers and one deep learning classifier and classifies the data between like and dislike. The machine learning classifiers include the support vector machine (SVM), random forest (RF), and deep learning classifier (DNN). The proposed hybrid model outperforms other classifiers like RF, SVM, and DNN and achieves an accuracy of 96.89%. In the proposed method, accuracy, sensitivity, specificity, precision, and F1 score were computed to evaluate and compare the proposed method with recent state-of-the-art methods.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22249744
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
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  • 7
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    Relevancy of Nizatidine’s Release from Floating Tablets with Viscosity of Various Cellulose Ethers
    MDPI AG ; 2021
    In:  Sci Vol. 3, No. 2 ( 2021-04-08), p. 22-
    Details
    In: Sci, MDPI AG, Vol. 3, No. 2 ( 2021-04-08), p. 22-
    Abstract: Nizatidine is a gastroprotective drug with a short biological half-life and narrow absorption window. This study aimed at developing floating tablets of nizatidine using various HPMC viscosity grades, namely K4M, E4M, K15 and K200M. Directly compressed tablets revealed an excellent uniformity in hardness, thickness and weight and nizatidine was evenly distributed within the matrix floating tablets. Buoyancy study revealed floating lag time as low as 18–38 s, and tablets remain buoyant for upto 24 h. However, the later depended upon viscosity grade of HPMC and that the higher the viscosity, the less was the total floating time. In vitro dissolution indicated viscosity dependent nizatidine release from the floating tablets. HPMC K4M and E4M based floating tablets released almost 100% drug in 12 h, whilst higher viscosity polymers such as K15 and K200M only released 81.88% and 75.81% drug, respectively. The drug release followed non-Fickian diffusion from tablets formulated with K4M, K15 and K200M, whilst super case II transport was observed with E4M based tablets. More interestingly, K4M and E4M polymers have similar viscosity yet exhibited different drug release mechanism. This was attributed to the difference in degree of substitution of methoxyl- and hydroxypropoxyl- groups on polymer backbone.
    Type of Medium: Online Resource
    ISSN: 2413-4155
    URL: Article
    DOI: 10.3390/sci3020022
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2963087-3
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  • 8
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    Online Resource
    An Integrated Delphi-AHP and Fuzzy TOPSIS Approach toward Ranking and Selection of Renewable Energy Resources in Pakistan
    MDPI AG ; 2019
    In:  Processes Vol. 7, No. 2 ( 2019-02-25), p. 118-
    Details
    In: Processes, MDPI AG, Vol. 7, No. 2 ( 2019-02-25), p. 118-
    Abstract: Pakistan has long relied on fossil fuels for electricity generation. This is despite the fact that the country is blessed with enormous renewable energy (RE) resources, which can significantly diversify the fuel mix for electricity generation. In this study, various renewable resources of Pakistan—solar, hydro, biomass, wind, and geothermal energy—are analyzed by using an integrated Delphi-analytical hierarchy process (AHP) and fuzzy technique for order of preference by similarity to ideal solution (F-TOPSIS)-based methodology. In the first phase, the Delphi method was employed to define and select the most important criteria for the selection of RE resources. This process identified four main criteria, i.e., economic, environmental, technical, and socio-political aspects, which are further supplemented by 20 sub-criteria. AHP is later used to obtain the weights of each criterion and the sub-criteria of the decision model. The results of this study reveal wind energy as the most feasible RE resource for electricity generation followed by hydropower, solar, biomass, and geothermal energy. The sensitivity analysis of the decision model results shows that the results of this study are significant, reliable, and robust. The study provides important insights related to the prioritizing of RE resources for electricity generation and can be used to undertake policy decisions toward sustainable energy planning in Pakistan.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr7020118
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2720994-5
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  • 9
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    Benzoic Acid Derivatives of Ifloga spicata (Forssk.) Sch.Bip. as Potential Anti-Leishmanial against Leishmania tropica
    MDPI AG ; 2019
    In:  Processes Vol. 7, No. 4 ( 2019-04-11), p. 208-
    Details
    In: Processes, MDPI AG, Vol. 7, No. 4 ( 2019-04-11), p. 208-
    Abstract: This study aimed to appraise the anti-leishmanial potentials of benzoic acid derivatives, including methyl 3,4-dihydroxybenzoate (compound 1) and octadecyl benzoate (compound 2), isolated from the ethnomedicinally important plant Ifloga spicata (I. spicata). Chemical structures were elucidated via FT-IR, mass spectrometry, and multinuclear (1H and 13C) NMR spectroscopy. Anti-leishmanial potentials of the compounds were assessed using Leishmania tropica promastigotes. Moreover, acridine orange fluorescent staining was performed to visualize the apoptosis-associated changes in promastigotes under a fluorescent microscope. A SYTOX assay was used to check rupturing of Leishmania promastigote cell membranes using 0.1% Triton X-100 as positive control. A DNA interaction assay was carried out to assess DNA attachment potential. AutoDock software was used to check the binding affinity of compounds with surface enzyme leishmanolysin gp63 (1LML). Both compounds exhibited considerable anti-leishmanial potential, with LD50 values of 10.40 ± 0.09 and 14.11 ± 0.11 μg/mL for compound 1 and compound 2, respectively. Both compounds showed higher binding affinity with the leishmanolysin (gp63) receptor/protease of Leishmania, as assessed using computational analysis. The binding scores of compounds 1 and 2 with target gp63 were −5.3 and −5.6, respectively. The attachment of compounds with this receptor resulted in their entry into the cell where they bound with Leishmania DNA, causing apoptosis. The results confirmed that the investigated compounds have anti-leishmanial potential and are potential substitutes as natural anti-leishmanial agents against L. tropica.
    Type of Medium: Online Resource
    ISSN: 2227-9717
    URL: Article
    DOI: 10.3390/pr7040208
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
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  • 10
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    Analysis and Optimization of Axial Flux Permanent Magnet Machine for Cogging Torque Reduction
    MDPI AG ; 2021
    In:  Mathematics Vol. 9, No. 15 ( 2021-07-23), p. 1738-
    Details
    In: Mathematics, MDPI AG, Vol. 9, No. 15 ( 2021-07-23), p. 1738-
    Abstract: In this paper, a hexagonal magnet shape is proposed to have an arc profile capable of reducing torque ripples resulting from cogging torque in a single-sided axial flux permanent magnet (AFPM) machine. The arc-shaped permanent magnet increases the air-gap length effectively and makes the flux of the air-gap more sinusoidal, which decreases air-gap flux density and hence causes a reduction in cogging torque. Cogging torque is the basic source of vibration, along with the noise in PM machines, since it is the main cause of torque ripples. Cogging torque is independent of the load current and is proportional to the air-gap flux and the reluctance variation. Three-dimensional finite element analysis (FEA) is used in the JMAG-Designer to analyze the performance of the conventional and proposed hexagonal-shaped PM AFPM machines. The proposed shape is designed to reduce cogging torque, and the voltage remains the same as compared to the conventional hexagonal-shaped PM machine. Further, optimization is performed by utilizing an asymmetric overhang. Latin hypercube sampling (LHS) is used to create samples, the kriging method is applied to approximate the model, and a genetic algorithm is applied to obtain the optimum parameters of the machine.
    Type of Medium: Online Resource
    ISSN: 2227-7390
    URL: Article
    DOI: 10.3390/math9151738
    Language: English
    Publisher: MDPI AG
    Publication Date: 2021
    detail.hit.zdb_id: 2704244-3
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