The increase in population growth and demand is rapidly depleting natural resources. Irrigation plays a vital role in the productivity and growth of agriculture, consuming no less than 75% of fresh water utilization globally. Irrigation, being the largest consumer of water across the globe, needs refinements in its process, and because it is implemented by individuals (farmers), the use of water for irrigation is not effective. To enhance irrigation management, farmers need to keep track of information such as soil type, climatic conditions, available water resources, soil pH, soil nutrients, and soil moisture to make decisions that resolve or prevent agricultural complexity. Irrigation, a data-driven technology, requires the integration of emerging technologies and modern methodologies to provide solutions to the complex problems faced by agriculture. The paper is an overview of IoT-enabled modern technologies through which irrigation management can be elevated. This paper presents the evolution of irrigation and IoT, factors to be considered for effective irrigation, the need for effective irrigation optimization, and how dynamic irrigation optimization would help reduce water use. The paper also discusses the different IoT architecture and deployment models, sensors, and controllers used in the agriculture field, available cloud platforms for IoT, prominent tools or software used for irrigation scheduling and water need prediction, and machine learning and neural network models for irrigation. Convergence of the tools, technologies and approaches helps in the development of better irrigation management applications. Access to real-time data, such as weather, plant and soil data, must be enhanced for the development of effective irrigation management applications.

Precise quantification of evaporation has a vital role in effective crop modelling, irrigation scheduling, and agricultural water management. In recent years, the data-driven models using meta-heuristics algorithms have attracted the attention of researchers worldwide. In this investigation, we have examined the performance of models employing four meta-heuristic algorithms, namely, support vector machine (SVM), random tree (RT), reduced error pruning tree (REPTree), and random subspace (RSS) for simulating daily pan evaporation (EP_d) at two different locations in north India representing semi-arid climate (New Delhi) and sub-humid climate (Ludhiana). The most suitable combinations of meteorological input variables as covariates to estimate EP_d were ascertained through the subset regression technique followed by sensitivity analyses. The statistical indicators such as root mean square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), Willmott index (WI), and correlation coefficient (r) followed by graphical interpretations, were utilized for model evaluation. The SVM algorithm successfully performed in reconstructing the EP_d time series with acceptable statistical criteria (i.e., NSE = 0.937, 0.795; WI = 0.984, 0.943; r = 0.968, 0.902; MAE = 0.055, 0.993 mm/day; and RMSE = 0.092, 1.317 mm/day) compared with the other applied algorithms during the testing phase at the New Delhi and Ludhiana stations, respectively. This study also demonstrated and discussed the potential of meta-heuristic algorithms for producing reasonable estimates of daily evaporation using minimal meteorological input variables with applicability of the best candidate model vetted in two diverse agro-climatic settings.

Strategies for designing remarkable nonlinear optical materials using excess electron compounds are well recognized in literature to enhance the applications of these compounds in nonlinear optics. In this study, density functional theory simulations are performed to study alkali and alkaline earth metal-doped benzocryptand using the B3LYP/6-31G+(d, p) level of theory. Vertical ionization energies (VIEs), reactivity parameters, interaction energies, and binding energies exposed the thermodynamic stability of these complexes. FMO analysis revealed that HOMO is located on alkali metals having polarized electrons, which are easy to excite. The doping strategy enhanced the charge transfer with low bandgap energy in the range of 0.68–2.23 eV, which is lower than that of the surface BC (5.50 eV). Also, the lower transition energies and higher oscillator strength indicate that these complexes exhibit excellent electronic and optical properties. Non-covalent interaction analysis suggested the presence of van der Waals interactions between dopants and surface. IR analysis provided information about the frequencies of stretching vibrations present in the complexes due to different bonds. UV-vis analysis revealed that all the newly designed excess electron complexes are transparent in the UV region and possessed maximum absorption in the visible and NIR region, ranging from 753.6 to 2150 nm, which is higher than the surface (244 nm). Thus, these complexes have a potential for high-performance NLO materials in the applications of optics. Natural bond orbital analysis (NBO), transition density matrix (TDM), electron density difference map (EDDM), and density of state (DOS) analyses were also performed to study the charge transfer properties. Moreover, these complexes possessed remarkable optoelectronic properties due to a significant increase in the isotropic linear polarizability (α_iso) in the range of 629.59–1423.23 au. Further, these systems demonstrated an extraordinary large total first hyperpolarizability (β_tl) in the range of 3695.55–910 706.43 au. The rationalization of hyperpolarizability by the two-level model reflected a noteworthy increase in β_tl because of low transition energies (ΔE) and high transition dipole moment (Δμ). Thus, our results showed that alkali and alkaline earth metal-doped BC might be a competitor for efficient nonlinear optical properties with practical applications in the area of optoelectronics.

The reduction of chemical oxygen demand (COD) from palm oil mill effluent (POME) is very significant to ensure aquatic protection and the environment. Continuous adsorption of COD in a fixed bed column can be an effective treatment process for its reduction prior to discharge. Adsorption capacity of bone derived biocomposite synthesized from fresh cow bones, zeolite, and coconut shells for the reduction in the organic pollutant parameter was investigated in this study in a fixed bed column. The effect of influent flow rate (1.4, 2.0, and 2.6 mL/min) was determined at an influent pH 7. The optimum bed capacity on the fabricated composite of surface area of 251.9669 m²/g was obtained at 1.4 mL/min at breakthrough time of 5.15 h influent POME concentration. The experimental data were fitted to Thomas, Adams–Bohart, and Yoon–Nelson models fixed bed adsorption models. It was revealed that the results fitted well to the Adams Bohart model with a correlation coefficient of R² > 0.96 at different influent concentration. Adsorption rate constant was observed to increase at lower flow rate influent concentration, resulting in longer empty bed contact time (EBCT) for the mass transfer zone of the column to reach the outlet of the effluent concentration. In general, the overall kinetics of adsorption indicated that the reduction in COD from POME using a bone-biocomposite was effective at the initial stage of adsorption. The pore diffusion model better described the breakthrough characteristics for COD reduction with high correlation coefficient. Shorter breakthrough time compared to EBCT before regeneration indicated that the bone composite was suitable and effective for the reduction in COD from POME using fixed bed column adsorption.

The worldwide spread and increasing prevalence of carbapenem-resistant Enterobacteriaceae (CRE) is of utmost concern and a problem for public health. This resistance is mainly conferred by carbapenemase production. Such strains are a potential source of outbreaks in healthcare settings and are associated with high rates of morbidity and mortality. In this study, we aimed to determine the dominance of NDM-producing Enterobacteriaceae at a teaching hospital in Karachi. A total of 238 Enterobacteriaceae isolates were collected from patients admitted to Jinnah Postgraduate Medical Centre (Unit 4) in Karachi, Pakistan, a tertiary care hospital. Phenotypic and genotypic methods were used for detection of metallo-β-lactamase. Out of 238 isolates, 52 (21.8%) were CRE and 50 isolates were carbapenemase producers, as determined by the CARBA NP test; two isolates were found negative for carbapenemase production by CARB NP and PCR. Four carbapenemase-producing isolates phenotypically appeared negative for metallo-β-lactamase (MBL). Of the 52 CRE isolates, 46 (88.46%) were bla_NDM positive. Most of the NDM producers were Klebsiella pneumoniae, followed by Enterobacter cloacae and Escherichia coli. In all the NDM-positive isolates, the bla_NDM gene was found on plasmid. These isolates were found negative for the VIM and IPM MBLs. All the CRE and carbapenem-sensitive isolates were sensitive to colistin. It is concluded that the NDM is the main resistance mechanism against carbapenems and is dominant in this region.

A series of hydrazone derivatives of 2-(benzamido) benzohydrazide was designed, synthesized, and characterized utilizing FTIR, NMR and UV spectroscopic techniques along with mass spectrometry. Compound 10 was also characterized through X-ray crystallography. These synthesized compounds were assessed for their potential as anti-Alzheimer's agents by checking their AChE and BChE inhibition properties by in vitro analysis. The synthesized derivatives were also evaluated for their antioxidant potential along with cytotoxicity studies. The results clearly indicated that dual inhibition of both the enzymes acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) was achieved by most of the compounds (03–13), showing varying IC₅₀values. Remarkably, compound 06 (IC₅₀ = 0.09 ± 0.05 for AChE and 0.14 ± 0.05 for BChE) and compound 13 (IC₅₀ = 0.11 ± 0.03 for AChE and 0.10 ± 0.06 for BChE) from the series showed IC₅₀ values comparable to the standard donepezil (IC₅₀ = 0.10 ± 0.02 for AChE and 0.14 ± 0.03 for BChE). Moreover, the derivative 11 also exhibited selective inhibition against BChE with IC₅₀ = 0.12 ± 0.09. Meanwhile, compounds 04 and 10 exhibited good anti-oxidant activities, showing % scavenging of 95.06% and 82.55%, respectively. Cytotoxicity studies showed that the synthesized compounds showed cell viability greater than 80%; thus, these compounds can be safely used as drugs. DFT and molecular docking studies also supported the experimental findings.