The probable effect of climate change on the water available for use in Bangladesh is not well known. We calculate monthly water balances for five main regions of Bangladesh to examine the likely ...impacts of climate change to 2050. We also examine the impact of past and potential future irrigation development. Climate change projections for rainfall in Bangladesh are uncertain, with increased rain in the wet season likely, but decreased rain also possible. Runoff is projected to vary in a manner similar to rainfall. However, assuming no change to the area of crops, all projections result in increases in irrigation water use, which leads to groundwater level declines. The impact of change (whether climate change or development) on water availability and use is greater in the Northwest region than elsewhere. For most water balance terms in most regions, irrigation development (both historic and future) is calculated to have a larger impact than climate change. Climate change is calculated to have a larger impact than irrigation development only on evapotranspiration and runoff, and possibly on groundwater levels. Model sensitivity tests suggest that model uncertainty is less than climate change uncertainty. To reverse lowered groundwater levels, Bangladesh’s policy includes greater use of surface water. While we calculate groundwater levels will rise, the viability of the policy may be affected by future changes to upstream use.
This article investigates the active disturbance rejection‐based distributed event‐triggered bipartite consensus problem of nonaffine nonlinear multiagent systems with input saturation. To reduce the ...update frequency of the control signal, an event‐triggered mechanism is employed for each follower. Additionally, the active disturbance rejection technology, as a combination of the extended state observer and the tracking differentiator, is introduced to estimate the uncertainties of the system and address the problem of explosion of complexity in the backstepping design process. Compared with the traditional distributed bipartite consensus schemes using neural networks/fuzzy logic systems, the design complexity of the control law is reduced in the proposed scheme. Meanwhile, the tracking error is maintained within a predefined range via the funnel function. Finally, the stability of the system is proved under the Lyapunov stability analysis theory, and the effectiveness of the proposed strategy is verified via simulation examples.
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Understanding the genetic complexity of traits is an important objective of small grain temperate cereals yield and adaptation improvements. Bi-parental quantitative trait loci (QTL) ...linkage mapping is a powerful method to identify genetic regions that co-segregate in the trait of interest within the research population. However, recently, association or linkage disequilibrium (LD) mapping using a genome-wide association study (GWAS) became an approach for unraveling the molecular genetic basis underlying the natural phenotypic variation. Many causative allele(s)/loci have been identified using the power of this approach which had not been detected in QTL mapping populations. In barley (Hordeum vulgare L.), GWAS has been successfully applied to define the causative allele(s)/loci which can be used in the breeding crop for adaptation and yield improvement. This promising approach represents a tremendous step forward in genetic analysis and undoubtedly proved it is a valuable tool in the identification of candidate genes. In this review, we describe the recently used approach for genetic analyses (linkage mapping or association mapping), and then provide the basic genetic and statistical concepts of GWAS, and subsequently highlight the genetic discoveries using GWAS. The review explained how the candidate gene(s) can be detected using state-of-art bioinformatic tools.
Non-destructive crop monitoring over large areas with high efficiency is of great significance in precision agriculture and plant phenotyping, as well as decision making with regards to grain policy ...and food security. The goal of this research was to assess the potential of combining canopy spectral information with canopy structure features for crop monitoring using satellite/unmanned aerial vehicle (UAV) data fusion and machine learning. Worldview-2/3 satellite data were tasked synchronized with high-resolution RGB image collection using an inexpensive unmanned aerial vehicle (UAV) at a heterogeneous soybean (Glycine max (L.) Merr.) field. Canopy spectral information (i.e., vegetation indices) was extracted from Worldview-2/3 data, and canopy structure information (i.e., canopy height and canopy cover) was derived from UAV RGB imagery. Canopy spectral and structure information and their combination were used to predict soybean leaf area index (LAI), aboveground biomass (AGB), and leaf nitrogen concentration (N) using partial least squares regression (PLSR), random forest regression (RFR), support vector regression (SVR), and extreme learning regression (ELR) with a newly proposed activation function. The results revealed that: (1) UAV imagery-derived high-resolution and detailed canopy structure features, canopy height, and canopy coverage were significant indicators for crop growth monitoring, (2) integration of satellite imagery-based rich canopy spectral information with UAV-derived canopy structural features using machine learning improved soybean AGB, LAI, and leaf N estimation on using satellite or UAV data alone, (3) adding canopy structure information to spectral features reduced background soil effect and asymptotic saturation issue to some extent and led to better model performance, (4) the ELR model with the newly proposed activated function slightly outperformed PLSR, RFR, and SVR in the prediction of AGB and LAI, while RFR provided the best result for N estimation. This study introduced opportunities and limitations of satellite/UAV data fusion using machine learning in the context of crop monitoring.
Abstract Ephedra is one of the many medicinal herbs that have been used as folk/traditional medicine in Jordan and other countries to cure various illnesses. Plants of this genus are well known for ...their antioxidant and antibacterial properties. In this study, three different solvents were used to obtain Ephedra extracts. When evaluated, the Ephedra alata Decne ethanolic extract reportedly had the greatest levels of total phenolic compounds (TPC) and total flavonoid compounds (TFC). The aqueous extracts displayed the highest antioxidant activity in the DPPH and ABTS assays, demonstrating their considerable capacity to neutralize free radicals. However, when evaluated using the FRAP method, the acetone extracts showed the strongest antioxidant activity, indicating their high reducing power. LC–MS/MS, a potent method of analysis that combines the liquid chromatographic separation properties with mass spectrometry detection and identification capabilities, was used in this study to detect and measure phytochemical content of a total of 24 phenolic compounds and 16 terpene compounds present in the extracts of Ephedra alata Decne . Various concentrations of these chemicals were found in these extracts. The extracts’ inhibitory effects on albumin denaturation and alpha-amylase activity were also assessed; the findings demonstrated the potentials of these extracts as anti-inflammatory and anti-diabetic medicines, with the acetone extract having the lowest IC50 values in the concomitant tests (306.45 µg/ml and 851.23 µg/ml, respectively). Furthermore, the lowest IC50 value (of 364.59 ± 0.45 µg/ml) for the 80% ethanol extract demonstrated that it has the strongest antiproliferative impact regarding the MDA-MB-231 breast cancer cell line. This finding indicates that this particular extract can be potentially used to treat cancer.
Abstract Long non-coding RNAs have emerged as highly versatile players in the regulation of gene expression in development and human disease, particularly cancer. Hundreds of lncRNAs become ...dysregulated across tumor types, and multiple lncRNAs have demonstrated functions as tumor-suppressors or oncogenes. Furthermore, studies have demonstrated that dysregulation of lncRNAs results in alterations of the epigenome in cancer cells, potentially providing a novel mechanism for the massive epigenomic alterations observed in many tumors. Here, we highlight and provide some illustrious examples of lncRNAs in various epigenetic regulatory processes, including coordination of chromatin dynamics, regulation of DNA methylation, modulation of other non-coding RNAs and mRNA stability, and control of epigenetic substrate availability through altered tumor metabolism. In light of all these known and emerging functions in epigenetic regulation of tumorigenesis and cancer progression, lncRNAs represent attractive targets for future therapeutic strategies in cancer.
This correspondence is concerned with source localization and classification for scenarios where both the far-field and near-field narrowband sources may coexist. We propose an efficient MUSIC-based ...solution that requires neither a multidimensional search nor high-order statistics (HOS). We also derive the stochastic Cramér-Rao bound (CRB) for the problem under consideration. The performance of the proposed method is compared with an existing method and with the CRB.
Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of ...the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.
In the present study, we empirically examined the “fear of missing out” (FOMO) construct and its association with psychopathology-related and technology use measures. We carried out an internet-based ...survey with 296 undergraduate participants and administered self-report questionnaires of FOMO, frequency and type of smartphone use, problematic smartphone use (PSU), and scales of negative affectivity including depression, anxiety, stress, proneness to boredom, and rumination. The results demonstrated that FOMO was related to demographic characteristics (age, sex, race, and relationship status) but with small effect sizes. FOMO was related to all measures of negative affectivity, social use of a smartphone, as well as the severity of PSU. Tests of mediation indicated that each negative affectivity construct mediated the relationship between FOMO and PSU severity, and only rumination mediated relations between FOMO and smartphone use frequency. When reversing the predictor and mediating variables, FOMO mediated relations between negative affectivity and PSU severity. Finally, results demonstrated some support for a single-factor latent construct for FOMO, but male and female participants had a different pattern of factor loadings. Negative affectivity may be a key mechanism by which FOMO may drive PSU, but future research should clarify the directionality among these variables. Gender-related social connectedness differences characterize FOMO.
•Fear of missing out (FOMO) was related to negative affectivity variables.•FOMO was related to social, and problematic smartphone use (PSU) severity.•Negative affectivity variables mediated relations between FOMO and PSU severity.•FOMO represented a single-factor model, with gender differences.
PEO/B
4
C nanocomposite films with various concentrations of B
4
C-NPs are fabricated by the casting method. The chemical and crystal structure, thermal, optical, electrical, and morphological ...properties of PEO/B
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C nanocomposites films are examined. The PEO/B
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C nanocomposite films have semicrystalline nature, and the amorphous phase is dominant in all PEO/B
4
C nanocomposite nature. Moreover, the crystallinity degree and the melting enthalpy (
Δ
H
m
) decrease as revealed by the XRD and DSC analysis, and the crystallinity behavior is the same, whether deduced from XRD or DSC. The slight shifting in the vibrational bands upon introducing B
4
C-NPs into PEO films confirms the formation of the charge transfer between the two materials. Furthermore, the transmittance (
T
) spectra, refractive index, and packing density values exhibited a substantial reduction due to adding different concentrations of B
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C-NPs into the PEO films. Further, the conductivity value of PEO/B
4
C nanocomposite increases due to the increase in B
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C-NPs contents in PEO nanocomposite. The SEM micrographs revealed that the pure PEO film has a very smooth surface with tiny cracks compared to others. The PEO/B
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C nanocomposite films with B
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C-NPs are composed of nanoparticles within the polymer matrix, accumulative nanoparticles on the surface, and cracks. These PEO/B
4
C nanocomposite films may be employed as an anti-corrosion coating.
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