Many-objective optimization (MaO) deals with a large number of conflicting objectives in optimization problems to acquire a reliable set of appropriate non-dominated solutions near the true Pareto front, and for the same, a unique mechanism is essential. Numerous papers have reported multi-objective evolutionary algorithms to explain the absence of convergence and diversity variety in many-objective optimization problems. One of the most encouraging methodologies utilizes many reference points to segregate the solutions and guide the search procedure. The above-said methodology is integrated into the basic version of the Moth Flame Optimization (MFO) algorithm for the first time in this paper. The proposed Many-Objective Moth Flame Optimization (MaOMFO) utilizes a set of reference points progressively decided by the hunt procedure of the moth flame. It permits the calculation to combine with the Pareto front yet synchronize the decent variety of the Pareto front. MaOMFO is employed to solve a wide range of unconstrained and constrained benchmark functions and compared with other competitive algorithms, such as non-dominated sorting genetic algorithm, multi-objective evolutionary algorithm based on dominance and decomposition, and novel multi-objective particle swarm optimization using different performance metrics. The results demonstrate the superiority of the algorithm as a new many-objective algorithm for complex many-objective optimization problems.

In this study, the adulteration of Moroccan Picholine extra virgin olive oil with Arbequina virgin olive oil was monitored using the Fourier transform mid-infrared (FT-MIR) spectroscopy technique and chemometrics methodologies. To discriminate between olive oil that has been adulterated and unadulterated, principal component analysis (PCA) was utilized for qualitative analysis. We created the best calibration models for quantitative analysis using principal component regression (PCR) and partial least-squares regression (PLS). The first three principal components account for 95% of the overall variability, according to PCA analysis. PCA allows for the classification of the dataset into two groups: adulterated and unadulterated Moroccan Picholine olive oil. The application of the PLS and PCR calibration models for the quantification of adulteration demonstrates high-performance capabilities, as indicated by high values of correlation coefficients R2 greater than 0.999 and 0.995 and lower values of root mean square error (RMSE) less than 0.767 and 2.16 using PLS and PCR, respectively. According to our results, FT-MIR spectroscopy combined with chemometrics approaches can be used successfully as a simple, quick, and non-destructive method for the quantification and discrimination of adulterated olive oil.

In this work, we have reported a synthesis of some novel pyrazol-pyrimidine derivatives (3a-f) obtained by the reaction of substituted pyrazole aldehydes and barbituric acid derivatives in presence of L-proline as a catalyst via Knoevengal condensation reaction. The structures of the synthesized compounds were characterized by spectral methods. From antibacterial activity, compounds 3d and 3f exhibited highest zone of inhibition as compared to standard drug gentamicin. Cytotoxicity results revealed that compound 3e exhibited a promising IC50 value against both the cell lines (A549 and MCF-7) as compared to the standard drug doxorubicin. Docking study discloses that, all the newly synthesized compounds displayed promising binding energies with the protein receptor EGFR kinase domain.

A nation's health status can be determined by the availability of healthcare services, which is a crucial part of human life. Since 2011, health facilities in Indonesia have been acknowledged as an important health indicator. This study uses correspondence analysis and spatial visualization to look at the primary healthcare facilities in each region of Indonesia. The analysis makes use of information from Indonesia's province-level data on the number of Regions with health facilities in 2021, along with six different types of medical facilities: hospitals, maternity hospitals, polyclinics, health centers, sub-district health centers, and pharmacies. To show the spread of medical facilities in Indonesia, a spatial representation is also produced. In comparison to provinces on other islands, the analysis reveals that the provinces on Java Island have a more varied and adequate distribution of healthcare facilities. Health facilities on other islands' provinces, however, are only focused on public health and sub-district public health. The spatial representation gives a clear picture of the distribution of medical services and draws attention to the distinctions across Indonesia's regions and islands. The geographical visualization offers a thorough perspective of the distribution of health care facilities, and this study delivers insightful information about how health care facilities are distributed in Indonesia. Future research and policy decisions targeted at enhancing Indonesia's healthcare system can be informed by these findings.

In our work we study the toxic effects of the prepared pyridine and pyradazine derivatives. Five compounds have been synthesized in pure state as reported procedures, and their toxicity as potential insecticidal agents against adult and nymphs of Aphis nerii were screened. The toxicity data in adults, exhibited that compound 6a is more toxic than other synthesized compounds, which LC50 was1.04 ppm while, in nymph compound 4a is more toxic than other synthesized compounds, which LC₅₀ was 0.02 ppm. The other screened compounds showed weak to strong toxicological activity. The structure-activity relationships (SAR) for these compounds were also discussed.

Big Data Analytics (BDA) provides an important resource for businesses seeking to enhance their performance and gain a competitive advantage, although not all organizations are adopting BDA techniques, and small and medium-sized enterprises (SMEs) in Jordan have been slow in this regard, despite being key players in any healthy economy, and the fact that BDA adoption can be facilitated by using the Technology Acceptance Model (TAM). The purpose of this study is to investigate the drivers of behavioral intention among managerial-level employees in Jordanian ICT SMEs to adopt BDA through a quantitative correlational research approach. The TAM questionnaire was used to gather data from 271 online survey participants in Jordan using Google Forms. The target group included management level staff working in small and medium-sized ICT firms (SMEs). Confirmatory factor analysis (CFA) was used to evaluate the research instrument's reliability and validity, and structural equation modeling (SEM) was utilized to test the study's hypotheses. The findings revealed that perceived usefulness, perceived ease of use, and perceived “privacy and security” significantly influenced managerial-level employees' behavioral intention to use BDA in their organizations. The research findings also supported the application of TAM, and the results of the investigation indicated that managerial-level employees would be willing to use BDA techniques providing they were perceived to be useful, user-effortless, and posed little concern about privacy and security. Overall, the current study's results demonstrate that the suggested model had good predictive power, 51% of the variance in behavioral intention, and was therefore capable of predicting managers' intentions to use BDA.

A new salicylaldehyde-based sensor N'-(5-bromo-2-hydroxybenzylidene)-4-methylbenzohydrazide (P4) was designed, and its sensing ability towards various metal ions was assessed using UV-visible spectroscopy. The structure of P4 was spectroscopically characterized by UV-Visible, Infrared, ¹H-NMR, ¹³C-NMR spectroscopy and mass spectrometry. UV-Visible absorption spectral study showed selective sensing ability of P4 for Cd²⁺ and Ni²⁺ ions in presence of diverse transition metal ions. The results revealed that the detection limit for Cd²⁺ and Ni²⁺ was 3.14 µM and 0.92 µM, respectively. Moreover, the compound P4 was fully implemented for detection of Cd²⁺ and Ni²⁺ in simulated samples.

The present includes the synthesis of pyrazoline derivatives using chalcones and phenyl hydrazine in the presence of ethanol. It also reveals that 2-pyrazoline complexes are physiologically active and may be used in a variety of therapeutic functions. FT-IR, ¹H-NMR, ¹³C-NMR, LC-MS, and elemental analyses were used to characterise newly synthesised phenyl-pyrazoline derivatives. The antimicrobial activity of the synthesised compounds was assessed using the agar well diffusion assay and the Minimum Inhibition Concentration (MIC). Compounds 4b, 4f, and 4h have exhibited remarkable antibiotic action against bacterial strains such as Staphylococcus aureus, Bacillus subtilis, Salmonella. Typhi, and Shigella sp. On the other hand, compound 4h had significant antifungal activity against Candida albicans and Aspergillus fusarium and was a highly promising agent when compared to standard nystatin.

The construction of smart villages has begun in many Indonesian villages, along with the advancement of technology and local economic growth. Villagers must participate in constructing the smart economy-smart village by becoming familiar with the characteristics of the village's inhabitants using the citizen science model. This study intends to categorize villagers so that researchers can assess and decide their level of readiness for a smart economy in an ecosystem based on a smart village. Clustering is required to find communities of residents who are ready based on their traits. Using fuzzy C-Means with a Davied Bouldin Index value of 0.129, the data were divided into 4 clusters. The most important variables were chosen using information from the test's 300 responders, and the Kaiser Mayer Olkin assumption of 0.975 was used to validate the results. Our paper provides new information on how smart village readiness is assessed by the citizen science cluster. It was decided to divide residents into four groups: those who are less prepared (24.33%), those who are somewhat prepared (29.33%), those who are ready ( 25.67%) %), those who are ready (level of participatory knowledge), and those who are very ready for the smart economy (20.67%) based on the cluster model.

Parabens are chemicals that are frequently used as preservatives in numerous cosmetic products. In recent years, the safety concern over these compounds has grown due to their endocrine-disrupting activity. In this research, a novel green magnetic molecularly imprinted polymer (GMMIP) was synthesised using propylparaben as a template and then applied as an adsorbent to selectively recognise and remove parabens from cosmetic samples. The green strategies were introduced by using Persicaria odorata or Kesum leaf extract as a reducing agent to synthesise green magnetic nanoparticles (MNP) as a magnetic core, and deep eutectic solvent (DES) has been designed as an environmentally friendly functional monomer that was used in the preparation of GMMIP. The GMMIP was characterised using Fourier transform infrared spectroscopy (FTIR), field emission scanning electron microscopy (FESEM), and Brunauer-Emmett-Teller (BET). The results of FESEM and BET indicated that the GMMIP exhibited an irregular spherical shape and mesoporous characteristics with a pore size of 17.74 nm. The adsorption pH, kinetics, isotherms, and thermodynamics parameters were performed to investigate the interactions that take place between GMMIP and propylparaben. The adsorption processes appeared to best fit the pseudo-second-order kinetic and Freundlich isotherm models at an optimum pH of 12. Findings from a thermodynamics study revealed the adsorption process was exothermic, spontaneous, and more favourable at 298 K. The optimised GMMIP was applied as an adsorbent to remove the parabens from cosmetic samples. When compared to methylparaben and ethylparaben, the GMMIP had the highest selectivity and effectively removed propylparaben, with recoveries ranging from 75.6% to 113.3%. It was found that the limits of detection (LOD) and quantification (LOQ) were between 0.03 and 0.05 mg/L and 0.11 and 0.16 mg/L, respectively. The synthesised GMMIP proved to be a convenient and effective adsorbent to remove parabens from cosmetic products.