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"Adnan, Muhammad"
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Plant growth regulators for climate-smart agriculture
\"Climatic conditions are key determinants of plant growth, whether at the scale of temperature regulation of the cell cycle, or at the scale of the geographic limits for a particular species. The climate is changing, due to human activities - particularly the emission of greenhouse gases - and therefore the conditions for the establishment, growth, reproduction, survival and distribution of plant species are changing. In contrast to animals, plants can continuously cease and resume growth. This flexibility in their architecture and growth patterns is partly achieved by the action of plant hormones. Still, the role of PGRs in agriculture is modest compared to other agrochemicals, such as fungicides, herbicides, and insecticides. Plant Growth Regulators in agriculture is an invaluable guide to the varied roles filled by PGRs in the attainment of higher-quality, better-yielding crops. Salient Features: Explores the plant growth regulator and anthropogenic climate change. Provides new insights related to hormonal cross-talk in plant development and stress responses. Shed new light on the role of PGRs in agriculture in the attainment of higher-quality, better-yielding crops. Delivers a valuable information on physiological and molecular mechanisms linked to the role of plant growth regulator in stress tolerance. Provides valuable knowledge for the all students of agronomy, plant physiology, molecular biology and environmental sciences\"-- Provided by publisher.
Book
All Sequential Dip-Coating Processed Perovskite Layers from an Aqueous Lead Precursor for High Efficiency Perovskite Solar Cells
A novel, sequential method of dip-coating a ZnO covered mesoporous TiO
2
electrode was performed using a non-halide lead precursor in an aqueous system to form a nanoscale perovskite film. The introduction of a ZnO interfacial layer induced significant adsorption in the non-halide lead precursor system. An efficient successive solid-state ion exchange and reaction process improved the morphology, crystallinity, and stability of perovskite solar cells. Improved surface coverage was achieved using successive ionic layer adsorption and reaction processes. When all sequential dipping conditions were controlled, a notable power conversion efficiency of 12.41% under standard conditions (AM 1.5, 100 mW·cm
−2
) was achieved for the perovskite solar cells fabricated from an aqueous non-halide lead precursor solution without spin-casting, which is an environmentally benign and low-cost manufacturing processes.
Journal Article
Monthly runoff forecasting based on LSTM–ALO model
Accurate runoff forecasting plays an important role in management and utilization of water resources. This paper investigates the accuracy of hybrid long short-term memory neural network and ant lion optimizer model (LSTM–ALO) in prediction of monthly runoff. As the parameters of long short-term memory neural network (LSTM) have influence on the prediction performance, the parameters of the LSTM are calibrated by using ant lion optimizer. Then the selection of suitable input variables of the LSTM–ALO is discussed for monthly runoff forecasting. Finally, we decompose root mean square error into three parts, which can help us better understanding the origin of differences between the observed and predicted runoff. To test the merits of the LSTM–ALO for monthly runoff forecasting, other models are employed to compare with the LSTM–ALO. The scatter-plots and box-plots are adopted for evaluating the performance of all models. In the case study, simulation results with the historical monthly runoff of the Astor River Basin show that the LSTM–ALO model has higher accuracy than that of other models. Therefore, the proposed LSTM–ALO provides an effective method for monthly runoff forecasting.
Journal Article
Stream Flow Forecasting of Poorly Gauged Mountainous Watershed by Least Square Support Vector Machine, Fuzzy Genetic Algorithm and M5 Model Tree Using Climatic Data from Nearby Station
Forecasting stream flow is a very importance issue in water resources planning and management. The ability of three soft computing methods, least square support vector machine (LSSVM), fuzzy genetic algorithm (FGA) and M5 model tree (M5T), in forecasting daily and monthly stream flows of poorly gauged mountainous watershed using nearby hydro-meteorological data is investigated in the current study. In the first application, monthly stream flows of Hunza river are forecasted using local stream flow data of Hunza and precipitation and temperature data of nearby station. LSSVM provides slightly better forecasts than the FGA and M5T models. Stream flow and temperature inputs generally give better forecasts compared to other inputs. In the second application, daily stream flows of Hunza river are forecasted using local stream flow data of Hunza and precipitation and temperature data of nearby station. Better results are obtained from the models comprising only stream flow inputs. In general, a better accuracy is obtained from LSSVM models in relative to the FGA and M5T. The results indicate that the monthly and daily stream flows of Hunza can be accurately forecasted by using only nearby climatic data. In the third application, daily stream flows of Hunza river are forecasted using local stream flow and climatic data and the models’ accuracy is slightly increased in relative to the previous applications. LSSVM generally performs superior to the FGA and M5T in forecasting daily stream flow of Hunza river using local stream flow and climatic inputs.
Journal Article
Efficient designing of triphenylamine-based hole transport materials with outstanding photovoltaic characteristics for organic solar cells
Hole transport materials (HTMs), especially dopant-free hole transport materials, are getting attention in enhancing the power conversion efficiencies and stabilities of organic solar cells (OSCs). Herein, we have designed efficient dopant-free HTMs (DM1–DM5) from an outstanding synthetic DFM molecule (having 20.6% PCE). Photo-physical, photovoltaic, optoelectronic and structural-property relationship of newly designed molecules are extensively studied and compared with DFM (R). Density functional theory (DFT) and time-dependent-density functional theory (TD-DFT) have been employed to investigate the alignment of frontier molecular orbitals (FMOs), optical properties, density of states along with transition density matrix, binding and excitation energy, reorganizational energies and for open-circuit voltages of all newly designed molecules. Red-shifting in absorption spectrum offers high power conversion efficiencies, and our tailored molecules exhibit red-shifting in absorption spectrum (λmax = 391–429 nm) as compared to R (λmax = 396 nm). In addition, our all designed molecules expressed better hole transport ability (λh = 0.0056–0.0089 eV) as compared to R (λh = 0.0101 eV). Similarly, DM1–DM5 disclosed narrow HOMO–LUMO energy gap which causes maximum charge transfer from excited HOMO to excited LUMO. The theoretical study of DM3/PC61BM and DM3/Y6 complexes is also performed in order to understand the shifting of charge between donor and acceptor molecules. Results of all analysis clearly show the efficient designing of dopant-free (DM1–DM5) molecules and their possible potential to fabricate a high performance and stable organic solar cells devices. Therefore, the theoretical proposed molecules are recommended to experimentalists for future highly efficient organic solar cells.
Journal Article
Preliminary Study on the Distribution, Source, and Ecological Risk of Typical Microplastics in Karst Groundwater in Guizhou Province, China
Karst groundwater is one of the important drinking water sources in karst areas, and it has an important role in maintaining the regional ecosystem and human health. The study of microplastics (MPs) in karst groundwater has rarely been reported, and the occurrence and migration behavior of MPs under the unique environmental conditions of karst is unclear. This study selected cave groundwater and common MPs in karst areas to explore the occurrence characteristics of MPs in groundwater to clarify the factors affecting the distribution and migration of MPs. The results showed that the abundance of MPs in karst groundwater was between 2.33 and 9.50 items·L−1, with an average abundance of 4.50 items·L−1. The microplastic size, type, color, and chemical composition were primarily 1~5 mm, film and fiber, color and transparent, and PS and PE, respectively. The risk characterization ratio (RCR) index results indicated that 80% of the samples were at a low ecological risk level, whereas 60% of the sampling points after concentrated rainfall in June were a medium ecological risk. The study showed that rainfall events significantly changed the abundance and migration of MPs in karst groundwater. The Pearson analysis showed a positive correlation between microplastic distribution and suspended particles (SP), total organic carbon (TOC), and water velocity (WV) in water. The study indicated that strong soil erosion in karst areas may also be one of the main sources of MPs in karst groundwater, and that karst groundwater microplastic pollution is an environmental problem that should not be ignored.
Journal Article
Adoption of mobile food ordering apps for O2O food delivery services during the COVID-19 outbreak
PurposeThe purpose of this paper is to develop a model to examine how different technological and cognitive cues related to mobile food ordering applications (MFOAs) impact diners' intentions to use MFOAs continuously. The moderating role of national household demographics was also assessed in the online-to-offline (O2O) food delivery services (FDS) context.Design/methodology/approachDrawing insights from the uses and gratification (U&G) theory, an online sample survey of 968 valid respondents who had ordered or purchased food through delivery apps during the COVID-19 outbreak in China was used for the analysis. The proposed model was empirically tested using structural equation modeling.FindingsThe results revealed that cues in MFOAs (i.e. ease of use, convenience, price saving orientation, the listing of various food choices, exploring restaurant patterns, and compatibility) directly influenced diners' e-satisfaction and that intention to use continuously is triggered by e-satisfaction during the COVID-19 crisis. Moreover, this study found that collectivist household diners emphasized ease of use, convenience, and compatibility. Comparatively, individualistic household diners placed more importance upon price saving orientation and listing of various food choices during the pandemic.Originality/valueThe authors offer a new insight into customers' dining choices by extending the scope of O2O services in the food industry. The findings contribute to understanding diners' purchase decision-making processes regarding MFOAs' O2O-FDS during the COVID-19 crisis. The multi-group comparison via national household demographics also provides a new perspective regarding different dining preferences toward O2O-FDS.
Journal Article
Prevalence of Type 2 Diabetes Mellitus in Adult Population of Pakistan: A Meta-Analysis of Prospective Cross-Sectional Surveys
The clinical and methodological diversity observed in national and regional diabetes surveys, emphasized on the need of the weighted average prevalence of diabetes.
To measure the pooled prevalence of type 2 diabetes mellitus in the adult population of Pakistan.
The prospective cross-sectional studies reporting adult diabetes in Pakistan and published on any date were retrieved from PubMed, ScienceDirect and PakMediNet databases. In the meta-analysis, PRISMA guidelines were used for reporting; the AXIS tool for assessing quality and risk of bias within studies; I
statistics for measuring heterogeneity between studies and subgroups; and Tableau Public 10.4 for geographic mapping of included studies. Using Meta-Analyst 3.13 βeta, overall and subgroup pooled estimates were measured by random effects model.
The pooled sample of twelve studies included 42,051 adults (≥20 years) comprised of both sexes from urban and rural Pakistan. The pooled prevalence of diabetes was 13.7% (95% CI, 10.7-17.3). None of the twelve studies was of poor quality (<10 scores). Ten studies were published in ISI indexed journals, and nine of them were indexed for Medline. The level of heterogeneity observed across studies and between subgroups was moderate (<50%). The subgroup analysis revealed a higher pooled estimate of diabetes in males than in females (13.1 vs. 12.4%). It was also higher in urban than in rural patients (15.1 vs. 1.6%), and in HbA1c than in OGTT tests (23.9 vs. 14.4%). However, pooled estimates of the WHO and the ADA criteria were similar (13.8 vs. 13.5%).
The prevalence of diabetes is on the rise in the adult population of Pakistan. The heterogeneity across studies observed in the meta-analysis suggested that the design of future diabetes surveys should be efficient and purposeful, and that valid tools and methods should be used to generate more precise data. Moreover, harmony between the stakeholders is much needed to seek a true picture of the diabetes burden in the country.
Journal Article
Aridity-driven shift in biodiversity–soil multifunctionality relationships
Relationships between biodiversity and multiple ecosystem functions (that is, ecosystem multifunctionality) are context-dependent. Both plant and soil microbial diversity have been reported to regulate ecosystem multifunctionality, but how their relative importance varies along environmental gradients remains poorly understood. Here, we relate plant and microbial diversity to soil multifunctionality across 130 dryland sites along a 4,000 km aridity gradient in northern China. Our results show a strong positive association between plant species richness and soil multifunctionality in less arid regions, whereas microbial diversity, in particular of fungi, is positively associated with multifunctionality in more arid regions. This shift in the relationships between plant or microbial diversity and soil multifunctionality occur at an aridity level of ∼0.8, the boundary between semiarid and arid climates, which is predicted to advance geographically ∼28% by the end of the current century. Our study highlights that biodiversity loss of plants and soil microorganisms may have especially strong consequences under low and high aridity conditions, respectively, which calls for climate-specific biodiversity conservation strategies to mitigate the effects of aridification.
Biodiversity-ecosystem functioning relationships may vary with climate. Here, the authors study relationships of plant and soil microbial diversity with soil nutrient multifunctionality in 130 dryland sites in China, finding a shift towards greater importance of soil microbial diversity in arid conditions.
Journal Article
In silico analysis of epitope-based vaccine candidate against tuberculosis using reverse vaccinology
Tuberculosis (TB) kills more individuals in the world than any other disease, and a threat made direr by the coverage of drug-resistant strains of
Mycobacterium tuberculosis
(Mtb). Bacillus Calmette–Guérin (BCG) is the single TB vaccine licensed for use in human beings and effectively protects infants and children against severe military and meningeal TB. We applied advanced computational techniques to develop a universal TB vaccine. In the current study, we select the very conserved, experimentally confirmed Mtb antigens, including Rv2608, Rv2684, Rv3804c (Ag85A), and Rv0125 (Mtb32A) to design a novel multi-epitope subunit vaccine. By using the Immune Epitopes Database (IEDB), we predicted different B-cell and T-cell epitopes. An adjuvant (Griselimycin) was also added to vaccine construct to improve its immunogenicity. Bioinformatics tools were used to predict, refined, and validate the 3D structure and then docked with toll-like-receptor (TLR-3) using different servers. The constructed vaccine was used for further processing based on allergenicity, antigenicity, solubility, different physiochemical properties, and molecular docking scores. The in silico immune simulation results showed significant response for immune cells. For successful expression of the vaccine in
E. coli
, in-silico cloning and codon optimization were performed. This research also sets out a good signal for the design of a peptide-based tuberculosis vaccine. In conclusion, our findings show that the known multi-epitope vaccine may activate humoral and cellular immune responses and maybe a possible tuberculosis vaccine candidate. Therefore, more experimental validations should be exposed to it.
Journal Article