During the present investigation, two new sulfonamide-based Schiff base ligands,
4-{(2-hydroxy-3-methoxyphenyl)methylideneamino}-N-(1,3-thiazol-2-yl)benzene-1-sulfonamid
e (
L
1
) and
...4-{1-(2-hydroxyphenyl)ethylideneamino}-N-(1,3-thiazol-2-yl)benzene-1-sulfonamide
(
L
2
), have been synthesized and coordinated with the transition metals (V, Fe, Co, Ni, Cu and Zn). The ligands were characterized by their physical (color, melting point, yield and solubility), spectral (UV–Vis, FT-IR, LC–MS,
1
H NMR and
13
C NMR) and elemental data. The structures of the metal complexes (
1
)–(
12
) were evaluated through their physical (magnetic and conductance), spectral (UV–Vis, FT-IR and LC–MS) and elemental data. The molecular geometries of ligands and their selected metal complexes were optimized at their ground state energies by B3LYP level of density functional theory (DFT) utilizing 6-311+G (d, p) and LanL2DZ basis set. The first principle study has been discussed for the electronic properties, the molecular electrostatic possibilities as well as the quantum chemical identifiers. An obvious transition of intramolecular charge had been ascertained from the occupied to the unoccupied molecular orbitals. The UV–Vis analysis was performed through time-dependent density functional theory (TD-DFT) by CAM-B3LYP/6-311+G (d, p) function. The in vitro antimicrobial activity was studied against two fungal (
Aspergillus niger
and
Aspergillus flavus
) and four bacterial (
Staphylococcus aureus
,
Klebsiela pneumoniae, Escherichia coli
and
Bacillus subtilis
) species. The antioxidant activity was executed as antiradical DPPH scavenging activity (%), total iron reducing power (%) and total phenolic contents (mg GAE g
−1
). Additionally, enzyme inhibition activity was done against four enzymes (
Protease, α-Amylase, Acetylcholinesterase
and
Butyrylcholinesterase
). All the synthetic products exhibited significant bioactivity which were found to enhance upon chelation due to phenomenon of charge transfer from metal to ligand.
Graphic abstract
Single-cell sequencing enables the inference of tumor phylogenies that provide insights on intra-tumor heterogeneity and evolutionary trajectories. Recently introduced methods perform this task under ...the infinite-sites assumption, violations of which, due to chromosomal deletions and loss of heterozygosity, necessitate the development of inference methods that utilize finite-sites models. We propose a statistical inference method for tumor phylogenies from noisy single-cell sequencing data under a finite-sites model. The performance of our method on synthetic and experimental data sets from two colorectal cancer patients to trace evolutionary lineages in primary and metastatic tumors suggests that employing a finite-sites model leads to improved inference of tumor phylogenies.
Democracy is generally associated with governmental accountability, better public policy choices and public health. However, there is limited evidence about how political regime
transition
impacts ...public health. We use two samples of the states around the world to trace the impact of regime transition on public health: the first sample comprises 29 post-communist states, along with 20 consolidated democracies, for the period of 1970–2014; the second sample is a subsample of the same 29 post-communist states but only for the period of transition, 1990–2014. We find that the post-communist states experienced some
decline
in life expectancy in the first few years of transition (1990–1995). Yet, with a steady increase in the measure of democracy from 1995 onwards, life expectancy significantly improved and infant mortality decreased. Therefore, in the long run, democratization has had a positive impact on both the life expectancy and infant mortality of citizens of the post-communist states.
Salinity stress is considered the most devastating abiotic stress for crop productivity. Accumulating different types of soluble proteins has evolved as a vital strategy that plays a central ...regulatory role in the growth and development of plants subjected to salt stress. In the last two decades, efforts have been undertaken to critically examine the genome structure and functions of the transcriptome in plants subjected to salinity stress. Although genomics and transcriptomics studies indicate physiological and biochemical alterations in plants, it do not reflect changes in the amount and type of proteins corresponding to gene expression at the transcriptome level. In addition, proteins are a more reliable determinant of salt tolerance than simple gene expression as they play major roles in shaping physiological traits in salt-tolerant phenotypes. However, little information is available on salt stress-responsive proteins and their possible modes of action in conferring salinity stress tolerance. In addition, a complete proteome profile under normal or stress conditions has not been established yet for any model plant species. Similarly, a complete set of low abundant and key stress regulatory proteins in plants has not been identified. Furthermore, insufficient information on post-translational modifications in salt stress regulatory proteins is available. Therefore, in recent past, studies focused on exploring changes in protein expression under salt stress, which will complement genomic, transcriptomic, and physiological studies in understanding mechanism of salt tolerance in plants. This review focused on recent studies on proteome profiling in plants subjected to salinity stress, and provide synthesis of updated literature about how salinity regulates various salt stress proteins involved in the plant salt tolerance mechanism. This review also highlights the recent reports on regulation of salt stress proteins using transgenic approaches with enhanced salt stress tolerance in crops.
PurposeThe primary objective of the present study is to figure out the relative effectiveness of alternate public expenditure with regard to agricultural development particularly in the context of ...input subsidies vis-a-vis investment. Besides, the authors also endeavour to test the applicability of crowding-out hypothesis in the present context.Design/methodology/approachInitially, unit root tests are applied for checking stationarity of the underlying data using Augmented Dickey-Fuller (ADF) and Kwiatkowski–Phillips–Schmidt–Shin (KPSS) tests. Further, the highly celebrated autoregressive distributive lag (ARDL) model is applied on annual time series data for the period 1991–2020 to investigate the long-run and short-run impact of the said relationship.FindingsThe authors observe that public investment is more productive than input subsidies for overall agricultural development. Besides, the findings document the existence of crowding-in hypothesis, i.e. complementarity between public investment and private investment in case of the agricultural sector in India.Research limitations/implicationsThe outcome of the research recommends to reprioritize state expenditure and reformulate agricultural policy regarding the public financing of agriculture. More to invest and less to subsidize seems a better policy intervention to achieve desirable outcomes from the Indian agriculture in the long run.Originality/valueThis study is novel in the sense that the subsidies vs investment debate is revisited in the current scenario of agricultural development so that resource allocation be optimized. To ensure robustness of the study, the authors specifically took four proxies of agricultural development, namely, productivity growth, private investment, food security and farmers’ income.
Over the years, the development of nanofluids has created new possibilities for research in the field of renewable energy. There has been rapid progress in the study of the optical characteristics of ...nanofluids for their potential use in Direct Absorption Solar Collectors (DASCs). Nanofluids may significantly improve photothermal conversion because of their enhanced optical properties. This study introduces a numerical model aimed at assessing the performance of DASC using mono and hybrid nanofluids. The model achieves this goal by solving the coupled radiation transfer equations in a participating medium together with the thermal energy equations. The realistic incident solar spectrum and effective optical properties of copper and alumina nanoparticles are also considered. The mathematical model is validated with experimental results from the literature. A parametric study is then carried out to study the sensitivity of the DASC performance on some design and operation parameters, such as the aspect ratio, heat transfer coefficient, and incident angle. The influence of copper and alumina nanoparticles on the DASC efficiency is also studied and compared. Due to their optical characteristics, it is established that the useful gain in copper-based nanofluid is much higher than in alumina-based nanofluid. Moreover, the use of Cu–Al2O3 hybrid nanofluid is studied at different combinations of volume fractions to understand the techno-economic impact on the DASC technology. The use of response surface methodology allows studying how modifications in the concentration of individual nanoparticles used in DASC can influence both its cost and performance. A multi-objective optimization is then performed at various loadings of the nanoparticles to maximize the DASC efficiency and minimize the total cost of the working fluid. Finally, Pareto front solutions are obtained as a guide for selecting the optimum combinations of nanoparticles that optimize the cost and performance of the DASC.
•Improve photo-thermal conversion using nanofluids due to enhanced optical properties.•A numerical model is proposed and validated with experimental results to investigate nanofluid filled DASC.•Sensitivity of DASC performance to various design and operation parameters with different volume fractions is examined.•Nanoparticle combination for maximum DASC efficiency and minimum cost is optimized.
Sulfuric acid was used to investigate the dissolution of bauxite ore. It was found that the dissolution rate increased with an increase in the acid concentration, liquid/solid ratio, stirring speed ...and temperature along with a decrease in the particle size of the sample. The dissolution curves were evaluated in order to test the validity of kinetic models for liquid/solid systems. The results were analyzed by graphical and statistical methods and it was found that the dissolution of the bauxite ore was controlled by shrinking core model, i.e., 1
−
(1
−
α)
1/3
2
=
7.6495
×
10
2
D
−1.0114
C
0.9105(
L/
S)
0.5969SS
0.3032e
−65.0436/RT
t
. The apparent activation energy of the process was found to be 65043.61367
Jmol
−1 over the reaction temperature range from 358 to 398
K. The cumulative effect of parameters on the dissolution process was investigated. The results indicated that the parametric cumulative effect (PCE) on the Arrhenius parameters was controlled by an exponential relation, i.e.
A
o
=
f
(
E
a
)
=
A
e
Z
iz
E
o
, where
A (=9.65595
×
10
−42
min
−1) is pre-exponential factor and
Z
iz (=1.5582
mol
kJ
−1
min
−1) is energy sensitivity coefficient of the parameters.
In recent times, a phishing attack has become one of the most prominent attacks faced by internet users, governments, and service-providing organizations. In a phishing attack, the attacker(s) ...collects the client’s sensitive data (i.e., user account login details, credit/debit card numbers, etc.) by using spoofed emails or fake websites. Phishing websites are common entry points of online social engineering attacks, including numerous frauds on the websites. In such types of attacks, the attacker(s) create website pages by copying the behavior of legitimate websites and sends URL(s) to the targeted victims through spam messages, texts, or social networking. To provide a thorough understanding of phishing attack(s), this paper provides a literature review of Artificial Intelligence (AI) techniques: Machine Learning, Deep Learning, Hybrid Learning, and Scenario-based techniques for phishing attack detection. This paper also presents the comparison of different studies detecting the phishing attack for each AI technique and examines the qualities and shortcomings of these methodologies. Furthermore, this paper provides a comprehensive set of current challenges of phishing attacks and future research direction in this domain.
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