Fused pyrimidines play an imperative role in our life due to their biological importance in the struggle of microorganisms. A series of 4-aryl-3-methyl-1-phenyl-1,4,6,7-tetrahydropyrazolo[3,4-d] thiazolo[3,2-a]pyrimidine (4a-j) were synthesized by cyclization of 3-methyl-1-phenyl-4-aryl-1,4,5,7-tetrahydro-6H-pyrazolo[3,4-d]pyrimidine-6-thiones (3a-j) with 1,2-dibromoethane in presence of anhydrous potassium carbonate. Earlier, compounds (3a-j) were synthesized by the condensation of 5-methyl-2-phenyl-2,4-dihydro-3H-pyrazol-3-one (2), different substituted benzaldehyde and thiourea with catalytic amount of con. HCl in methanol. Compound 2 was synthesized by condensation of ethyl acetoacetate (1) and phenylhydrezine in presence of a catalytic amount of acetic acid at reflux temperature. The constitution of the synthesized products has been characterized by using elemental analysis, Infrared, ¹H-NMR spectroscopy and further supported by Mass spectroscopy. All the products have been screened for their in-vitro biological assay like antibacterial and antifungal activity at concentration of 500 μg/ml. It was exposed that most of the compounds displayed inspiring antibacterial and antifungal activity compared to the used reference standard.

New Product Development Process (NPD) is a key aspect of launching new and innovative products in the market. Many products fail in the market because of technical risks, financial risks and product development time risks. It is very important to understand the overall risk factors associated with different stages of product development so that risks can be mitigated effectively. This paper presents a methodology to understand the risk associated with the initial stages of NPD. Design flexibility is higher in initial design stages requiring minimum redesign efforts and costs. It is a great opportunity to deal with risk factors and uncertainties in initial design stages than the later design stages. Product development costs in initial stages are around 5 to 10 percent but impact is 70 to 80 percent so exploration assessment in initial stages of NPD can be hugely beneficial. Stage-wise risk assessment will also provide the details of risk associated with each stage, which will be helpful in implementing appropriate mitigation strategies. Since transition from one stage to another stage of NPD is independent of the previous stage, different NPD stages can be easily expressed by the transition state of the Markov process. In this paper, the Markov process has been used for the risk assessment of initial stages of NPD, keeping mitigation strategies in mind. The three initial stages of NPD considered in this study include the concept design, detailed design and integration & testing stages. This paper also explores a method by integration of quality function deployment (QFD) and Markov process, to understand risk patterns associated with several complete design solutions (CFDs). By using QFD, the mapping between customer requirements can be reflected into risk assessment of complete design solutions (CFDs). This methodology has been demonstrated by a case study on Coffee Maker.

Connection designs are established to ensure the stability of joined cut sections, the joints so designed should be based on the optimal performance as per the requirements. The connection joints so established should not be based on just strength but reliability and durability as well. This study focuses on tackling one of the major issues faced when using Glass Fibre Reinforced Polymers (GFRPs) as construction materials, which is based on the abrupt failure of the material under critical or maximum loading. Connection designs are established in GFRP short column H-sections based on Bolted Splicing connections by Eurocode 3 for steel splicing connections. A total of seven Connection designs are established using bearing and non-bearing splicing connections. A total of five models for each connection is established for manual testing and Finite Element Analysis (FEA) is used to simulate and analyze these connection designs. Parameters such as ultimate load, displacement at ultimate load, stiffness, compressive strength, failure mode, load versus displacement behavior graph, and percentage compressive strength compared to the un-cut section are provided in this study. The strongest specimen in this study displaced 128% and 127.7% compressive strength compared to an un-cut GFRP H-section when tested using manual testing and FEA accordingly.

Metals play a crucial role in the metabolic pathways during the growth of vegetable plants. The presence of heavy metals or trace metals also takes a vital role in the nutrient quality of a vegetable. The vegetables are an inevitable part of the human diet and provide essential nutrients to maintain the normal functioning of human health and growth. The application of fertilizers and pesticides facilitates the accumulation of heavy metals by the vegetables grown in the fields. Consumption of heavy metals beyond the permissible limit along with vegetables may impact human health. Moreover, the production of nutritious food and its safety is an important aspect of the measure of any nation’s economy. Considering all these points, the present work was undertaken to analyze the heavy metal contents in the six mostly produced and consumed vegetables grown in Bodoland Territorial Region (BTR), a tribal-dominated region of the state Assam, India. The vegetables analyzed were fern leaves (Diplazium esculentum), jute leaves (Corchorus olitorius), green arum leaves (Colocasia esculenta), pointed gourd (Trichosanthes dioica), yard long bean (Vigna unguiculata ssp. Sesquipedalis) and spiny gourd (Momordica dioica). The metals analyzed were Cu, Fe, Ni, and Zn. The presence of heavy metals was detected in all the vegetable samples.

Application of the Molecular Electron Density Theory (MEDT) for the exploration of the [3+2] cycloaddition processes between methyl propynoate 1 and difluoromethyldiazomethane T-1, have been implemented using the DFT/B3LYP/6-311(d,p) level of theory. According to an examination of conceptual DFT indices, difluoromethyldiazomethane (T-1) participates in this reaction as a nucleophile, while methyl propynoate (1) should be considered as an electrophile. This cyclization is regiospecific, as evidenced by the activation and reaction energies, this agrees with the experiment's findings. It was discovered throughout ELF analysis that analyzed [3+2] cycloaddition is realised by a two-step mechanism. In addition, study of interactions of the products studied in this paper with the protein protease Covid-19 (PDB ID: 7R98) were carried out, by means of molecular docking study). The results indicate that the occurrence of the transfer of the proton to the nitrogen atom, increases the affinity of these products to the protein (CA32-F1 and CA32-F2).

In this communication, condensation from different aromatic, aliphatic and heteroaromatic aldehydes, hydroxyl amine, and sodium azide in toluene reflux was used to produce electronically and structurally distinct tetrazoles with a range of yields 5-94%. Zn(OAc)2•2H2O (10 mol%) was used as a catalyst in the synthesis, which was eco-friendly, readily available, and affordable. The IR, NMR, and mass spectral studies were utilized in order to carry out a comprehensive characterization for all the 5-aryl tetrazole derivatives. This approach contributes to the current chemical synthesis of 5-substituted-1H-tetrazoles in an appealing and convenient manner thanks to its quick reaction times, good to exceptional yields, safe process, and straightforward workup.

Uncertainty is an important factor in the decision-making process. Hesitant Pythagorean fuzzy sets (HPFS), a combination of Pythagorean and hesitant fuzzy sets, proved as a significant tool to handle uncertainty. Well-defined operational laws and attribute weights play an important role in decision-making. Thus, the paper aims to develop new Trigonometric Operational Laws, a weight determination method, and a novel score function for group decision-making (GDM) problems in the HPF environment. The approach is presented in three phases. The first phase defines new operational laws with sine trigonometric function incorporating its special properties like periodicity, symmetricity, and restricted range hence compared with previously defined aggregation operators they are more likely to satisfy the decision maker preferences. Properties of trigonometric operational laws (TOL) are studied and various aggregation operators are defined. To measure the relationship between arguments, the operators are combined with the Generalized Heronian Mean operator. The flexibility of operators is increased by the use of a real parameter λ to express the risk preference of experts. The second phase defines a novel weight determination method, which separately considers the membership and non-membership degrees hence reducing the information loss and the third phase conquers the shortcomings of previously defined score functions by defining a novel score function in HPFS. To further increase the flexibility of defined operators they are extended in the environment with unknown or incomplete attribute weights. The effectiveness of the GDM model is verified with the help of a supplier selection problem. A detailed comparative analysis demonstrates the superiority, and sensitivity analysis verifies the stability of the proposed approach.

Extensive research work has been published on Tetrahydro and Dihydropyrimidine derivatives. Pyrimidine-5-Carbonitrile and its analogs have demonstrated a large number of activities. Some 6-Halogenosubstituted pyrimidine analogs have also been reported to be biologically active to a certain extent, but the literature survey reveals not much report on 6-alkylated pyrimidine derivatives. Targeting enhancement in biologically useful properties of a lead molecule through the association of it with active pharmacophoric groups or molecules is a conventional method in pharmaceutical research. With an aim to explore a better useful Dihydropyrimidine derivative, a newer 4-Alkylated-1,6-dihydropyrimidine analog (1) has been prepared. The lead molecule (1) has further been converted to amine derivative (2), hydrazino derivative (3) tri substituted s-triazinyl derivative (4), sulphonamide (5), Schiff’s base (6), a thiazolidinones (7), and 2-Azetidinones (8) respectively using various methods. Compounds 2, 4, 5, and 7 showed 50% and 8 showed 100% bacterial inhibition at 32μg/mL in single-point bacterial inhibition against various bacterial strains.

In the current study, the compound 4,4-dimethoxychalcone (DMC) was structurally studied and analyzed by in silico approach against M^pro to investigate its inhibitory potential. The molecular structure of the compound was confirmed by the single crystal X-ray diffraction studies. The crystal structure packing is characterized by various hydrogen bonds, C-H…π and π…π stacking. Intermolecular interactions are quantified by Hirshfeld surface analysis and the electronic structure was optimized by DFT calculations; results are in agreement with the experimental studies. Further, DMC was virtually screened against SARS-CoV-2 main protease (PDB-ID: 6LU7) using molecular docking, and molecular dynamics (MD) simulations to identify its inhibitory potential. A significant binding affinity exists between DMC and M^pro with a -6.00 kcal/mol binding energy. A MD simulation of 30ns was carried out; the results predict DMC possessing strong binding affinity and hydrogen-bonding interactions within the active site during the simulation period. Therefore, based on the results of the current investigation, it can be inferred that a DMC molecule may be able to inhibit M^pro of COVID-19.

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.