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Feature selection is a major challenge in data mining which involves complex searching procedure to acquire relevant feature subset. The effectiveness of classification approaches is greatly susceptible to data dimensionality. The Higher dimensionality intricate numerous problems like higher computational costs and over fitting problem. The essential key factor to mitigate the problem is feature selection. The main motive is to minimize the number of features through eliminating noisy, insignificant, and redundant features from the original data. The Metaheuristic algorithm attains excellent performance for solving this kind of problems. In this paper, the grading based binary salp swarm optimization has been proposed to solve various complex problems with lesser computational time. The grading system has been used to maintain the balance among exploitation and exploration. The proposed method is examined using ten benchmark real datasets. The comparative result exhibits the promising performance of our proposed method and surpasses with other optimization interms of investigating evaluation measures.

This article presents a generalized novel iterative technique for obtaining the approximate solution of systems of linear equations(ABBT0)(xy)=(pq). Parameters involved in the scheme play a vital role to obtain the rapid and best approximate solution. The technique is applied to some important problems and the results are presented in detail. The article compares the effectiveness of the new presented iterative scheme with modified SOR-like method, generalized SOR and SOR-like method for solving large systems of linear equations. The convergence criteria for the iterative scheme are also analysed and it can be observed in the article that the theoretical derivation is supported by numerical calculations and graphical exhibition. Overall, the article provides a new and effective method with a detailed analysis of its performance and convergence criteria for solving systems of linear equations of the form presented. The newly derived technique has potential applications in various fields of science and engineering where systems of linear equations arise and need to be solved.

Given the escalating apprehensions regarding climate change and environmental risks, the construction industry is confronted with the crucial task of guaranteeing the enduring structural robustness of buildings. Building Information Modeling (BIM) has emerged as an innovative tool to tackle these challenges effectively and enhance the performance of building structures processes by developing intelligent and sustainable structures. A comprehensive methodology was utilized to assess the relationships between the BIM factors and their impacts on smart and sustainable structure development by conducting a literature overview, quantitative analysis, exploratory factorial analysis (EFA), structural equation modeling (SEM), and predictive relevance findings. The findings show positive correlations between the implementation of BIM and the elements integral to smart and sustainable structure development. This study investigates the effects of BIM-driven environmental risk assessment, BIM-enabled energy efficiency, environmental performance, climate change adaptation strategies with BIM, and real-time monitoring and maintenance on the effectiveness of smart and sustainable structures development. The BIM-driven environmental risk assessment significantly impacts the sustainable and smart structures development with B = 0.360, followed by the real-time monitoring and maintenance with BIM with 0.316. This study provides the contemporary knowledge base by providing insights into BIM's transformative abilities in shifting sustainable and smart construction practices. The outcomes offer widespread insights to enterprise specialists interested in enhancing task effects and organizing sustainable and environmentally aware built surroundings. The growing popularity of BIM has implications for the future growth of the construction industry in phrases of ecologically smart and sustainable structure development.

The study aims to identify the effect of the CEO and audit committee characteristics on financial performance. To achieve the study's goal, panel data was adopted for 43 private Iraqi banks from 2018 to 2022 with 215 observations. The data was analyzed using Stata. Three models were used to analyze the data, and the preferred model was chosen by following several confirmation steps. The findings indicated that CEO education, CEO ownership, and CEO experience all influenced financial success. The audit committee's characteristics also played an essential role in the link between the characteristics of the CEO and financial performance. This study is added to critical studies for regulatory authorities and decision-makers, especially since shareholders and decision-makers always seek to appoint CEOs with the capabilities and talents to enable them to achieve shareholders' goals and enhance banks' competitiveness in different environments.

Recently, several memory-type mean estimators (including ratio, product, and logarithmic) have been developed. These estimators rely on exponentially weighted moving average (EWMA), which incorporate both historical and present sample data. In this article, we propose EWMA type calibrated estimators under single and double stratified random sampling (StRS). Because calibration method enhances the estimates by modifying the stratification weight, taking advantage of supplementary information. To evaluate the performance of estimators, various real-world time-scaled data sets pertaining to stock market and weather are taken into account. Additionally, we also conduct a simulation study using a bivariate symmetric data set. The numerical results show the superiority of proposed estimators (y¯TM,y¯TaM) over the adapted ones (y¯PM,y¯PaM).

Implementing Internet of things (IoT) technology in the context of intelligent buildings and infrastructure development has garnered significant attention within the construction sector. Nonetheless, the implementation of IoT could be improved by assessing various barriers. The purpose of this study was to examine the obstacles related to the adaptation of IoT techniques within the construction sector, as well as the effects on the advancement of intelligent building and infrastructure systems. The study employed a mixed-method approach involving exploratory factor analysis (EFA) and structural equation modeling (SEM) to determine six types of barriers: knowledge, technical, standardization, creativity, complexity, and economics. The study revealed that the implementation of IoT for developing smart construction and infrastructure in the construction sector was significantly influenced by all six constructs. The results of this study offer significant ramifications for the field. The study underscores the necessity for heightened consciousness and instruction regarding the advantages of implementing IoT. The study posits that the technical barriers, including interoperability, modernization of legacy infrastructure, and coordination and collaboration difficulties, require attention from the industry. The study highlights the significance of establishing industry-wide standards and protocols for implementing IoT and regulatory and legal frameworks. Finally, the study underscores the necessity for augmented funding and financing options for IoT endeavors. Subsequent study endeavors may expand upon the present findings by delving into the barriers encountered by alternative sectors and nations and assessing the efficacy of the suggested measures in this investigation.

Drawing inspiration from recent advancements in robust mean estimation within finite sampling theory, we introduce a novel dual-type class of mean estimators in a design-based framework. The dual-type class is based on quantile regression and is specifically designed to be effective in the presence of extreme observations. Significantly, it integrates the averages of both sampled observations and non-sampled observations of auxiliary variable. In the initial discussion of this class, it is presumed that the target variable is non-sensitive, signifying its relevance to subjects that respondents do not consider embarrassing when queried directly. In this standard setting, we present specific estimators within the class and determine their theoretical properties. The class's scope broadens to include scenarios where the target variable incorporates sensitive topics, giving rise to nonresponse rates and inaccurate reporting. To alleviate these errors, one can promote respondent cooperation by employing scrambled response methods that obscure the actual value of the sensitive variable. Accordingly, the article delves into discussions on additive methods. Subsequently, a numerical study is conducted using asymmetric data to evaluate the effectiveness of the dual-type class by comparing it with several existing estimators, both in the absence and presence of scrambled responses.

The present work gives generalized form of the class of estimators if unit non-response is acquired in small domains. We have obtained indirect method like synthetic. It has provided specific instances where the proposed estimators are unbiased. It has also given a generalized form of the synthetic estimators. The four estimators were investigated with coefficient of variation and kurtosis constants. Because, these are obtained from the available variable. We conducted atheoretical comparison between traditional and proposed calibration estimators for estimating the domain totals. It found that the proposed estimators are more efficient than traditional estimators for investigate small domains.

Survey sampling has wide range of applications in social and scientific investigation to draw inference about the unknown parameter of interest. In complex surveys, the sample information about the study variable cannot be expressed by a precise number under uncertain environment due fuzziness and indeterminacy. Therefore, this information is expressed by neutrosophic numbers rather than the classical numbers. The neutrosophic statistics, which is generalization of classical statistics, deals with the neutrosophic data that has some degree of indeterminacy and fuzziness. In this study, we investigate the compromise optimum allocation problem for estimating the population means of the neutrosophic study variables in a multi-character stratified random sampling under uncertain per unit measurement cost. We proposed the intuitionistic fuzzy cost function, modeling the fuzzy uncertainty in stratum per unit measurement cost. The compromise optimum allocation problem is formulated as a multi-objective intuitionistic fuzzy optimization problem. The solution methodology is suggested using neutrosophic fuzzy programming and intuitionistic fuzzy programming approaches. A numerical study includes the means estimation of atmospheric variables is presented to explore the real-life application, explain the mathematical formulation, and efficiency comparison with some existing methods. The results show that the suggested methods produce more precise estimates with less utilization of survey resources as compared to some existing methods. The Python is used for statistical analysis, graphical designing and numerical optimization problems are solved using GAMS.

This study delves into the complex interplay of environmental accounting, sustainable production, and financial performance within the textile industry in Bangladesh. The background highlights the growing importance of sustainable practices in the business landscape and the need for empirical insights in the context of textile companies. The purpose of the study is to uncover the impact of environmental accounting practices, such as environmental cost accounting, carbon accounting, and sustainability reporting, on financial performance. Employing a comprehensive methodology that combines Partial Least Squares Structural Equation Modeling (PLS-SEM), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Necessity Condition Analysis (NCA), the research provides a nuanced understanding of the intricate relationships among these variables. The results reveal that environmental accounting positively influences financial outcomes, and sustainable production acts as both a direct enhancer of financial performance and a mediator in the relationship between environmental accounting initiatives and financial success. Practical and managerial implications emphasize the strategic integration of environmental accounting practices, prioritization of sustainable production, and the role of transparency in sustainability reporting for long-term financial success. Thus, the study offers a roadmap for businesses navigating the intersection of sustainability and financial performance, contributing valuable insights for both academia and industry practitioners.

Introduction: Traumatic head injury THI is a Neurosurgical condition in which brain function is interrupted as a result of blunt (motor vehicle accidents MVA, falls, and assaults) or penetrating trauma. Nearly half of all injuries are caused by head trauma. Head traumas are a leading cause of death and organ loss in young people, where this population accounts for the vast majority of TBI patients. Methodology: This retrospective cohort study was conducted at Asir Central Hospital, KSA with data from 2015 to 2019. Records of bacterial cultures and outcomes such as length of stay in the hospital were analyzed. In addition, treatment outcomes were also analyzed. Results: A total of 300 ICU patient samples (69 patients) were included. Patients’ ages ranged from 13 to 87 years with a mean age of 32.4 ± 17.5 years old. The most frequently reported diagnosis was RTA (71 %), followed by SDH (11.6 %), The most isolated organisms from the recovered samples were Klebsiella pneumoniae (27 %), followed by Pseudomonas aeruginosa (14.7 %). Regarding susceptibility, Tigecycline was the most sensitive (44 %), followed by Gentamicin (43.3 %). A total of 36 (52.2 %) patients stayed for less than one month, 24 (34.8 %) stayed for 1–3 months, and 7 (10.1 %) stayed for 3–6 months. The mortality rate in our study population was (40.6 %) as 28 patients died. Conclusion: The prevalence of pathogens in TBI needs to be determined in different institutions for the establishment of effective empiric antibiotic treatment following infections in traumatic brain injuries. This will ultimately help to improve treatment outcomes. In neurosurgical patients undergoing cranial procedures after trauma, a hospital-standardized antibiotic policy is effective in achieving low rates of bacterial infections especially MDR infections.

Estimation of population mean is a determined subject issue in sampling surveys and many efforts have been paid by various researchers to enhance the precision of the estimates by utilizing the correlated auxiliary information. In connection with this, we suggest an improved exponential ratio-cum-ratio estimator using transformed auxiliary variables under ranked set sampling scheme. Theoretical comparison between estimators is made in terms of mean square errors (MSEs), percentage relative efficiencies (PREs), and percentage relative root mean squared error (PRRMSE). The numerical expression for the bias and MSE of the suggested estimator is derived up to first order of approximation. Based on the results of actual data sets and a simulation study, it is found that the suggested estimator perform well as compared to its existing counterparts.

In recent times, there has been a notable increase in the focus on the use of Building Information Modelling (BIM) within the Architecture, Engineering, and Construction (AEC) industry. This study aims to fill a notable void in the current body of literature by examining the connections between the implementation of BIM and the factors that influence it. Additionally, it investigates the resulting effects on collaboration, continuous improvement, data management, gradual adoption, standardisation, and the various dimensions of society, economy, politics, and technology. This study examines the impact of BIM adoption within the AEC sector, focusing on its external environment by using a Political, Economic, Social, and Technological (PEST) approach. Using a quantitative approach, data was gathered by means of a survey questionnaire that was delivered to a sample of 216 professionals in the AEC business, who were chosen using purposive selection. The results suggest that the deployment of BIM cooperation, continuous improvement, effective data management, gradual acceptance, and standardisation, leading to positive outcomes in several areas such as social, economic, political, and technical. These findings have significant consequences for professionals working in the field.

Non-small cell lung cancer (NSCLC) is a pervasive and challenging global health concern. This research delves into the intricate relationship between NSCLC and ACE2 expression, exploring the potential impact of COVID-19 history on this interaction. Tissue samples were meticulously gathered from a cohort of 32 NSCLC patients, 18 of whom had a documented history of COVID-19 infection. The methodology included extensive investigations, such as cell dissociation, histopathological analysis, immunohistochemistry, cell culture, adhesion assays, immunocytochemistry, RNA isolation, and RT-PCR analysis. The results of this comprehensive study unearthed intriguing findings regarding ACE2 expression patterns within NSCLC tissues. Notably, variations were observed in ACE2 profiles between individuals with and without a prior record of COVID-19 infection, hinting at a dynamic interplay. These discoveries carry profound implications for both the understanding of NSCLC progression and the response to COVID-19 in patients with pre-existing NSCLC. The interrelationship between ACE2 expression, NSCLC, and COVID-19, as revealed in this study, may significantly influence patient outcomes and, potentially, therapeutic strategies. In summary, this research serves as an essential contribution to the growing body of knowledge on NSCLC, offering unique insights into the intricate connections between ACE2, COVID-19, and NSCLC. This information may open new avenues for tailored treatment approaches and clinical management strategies, ultimately benefiting patients grappling with NSCLC in the background of the current COVID-19 pandemic.

The removal of dyes from wastewater that are released during industrial processes has become a significant concern in the environmental science in recent years. To tackle this issue, researchers are exploring the use of nanomaterials for designing new adsorbents. Another promising approach is to grow polymer brushes with high density functional groups via surface-initiated atom transfer radical polymerization (SI-ATRP), which can significantly enhance their ability to absorb dyes. The presence of carboxylic acid groups on the adsorbent material significantly contributes to its efficacy in dye removal by enhancing adsorption capacity, enabling selective adsorption, pH-dependent behavior, chelation, or complexation, and providing stability for repeated usage. In this work, a nanomaterial of carboxylic functionalized poly (methacrylic acid 2-(tert-butylamino)ethyl ester)-coated mesoporous silica nanoparticles (MSNPs–PMATBAE–COOH) was synthesized by the growth of PTBAEMA via surface-initiated atom-transfer radical polymerization, then reacted with succinic anhydride reaction. The chemical structure of MSNPs–PMATBAE–COOH was confirmed using multiple methods, including FT-IR and DLS, and the core-brush morphology was observed clearly using TEM. MSNPs–PMATBAE–COOH were subsequently employed to adsorb hazardous dyes efficiently. The anionic polymer brushes enabled the adsorption of methylene blue (MB) and tetraethylrhodamine (TER) at optimum pH value of 3. The results also indicated that MSNPs–PMATBAE–COOH possessed significant adsorption capacity (263.4 and 212.9 mg g−1 for MB and TER, respectively) and fast adsorption rate (within 15 min), which can be explained by the abundance of adsorptive polymer brushes and the small size of the nanoparticles. Overall, the findings indicate that MSNPs-PMATBAE-COOH is a highly effective adsorbent material for eliminating dye pollutants from wastewater.

This study examines the antecedents and consequences of credit risk (CR) in Iraqi banks' context from 2011 to 2020. POLS, FEM, and REM regression estimators were used to test the hypotheses after obtaining an appropriate model. The hypotheses test findings on CR antecedents reveal that the board's financial expertise, risk management committee, and foreign ownership have a negative impact on CR. Meanwhile, the results show an insignificant effect on CR of board independence, audit committee, institutional ownership, governmental ownership, and managerial ownership. Concentrating on the consequence of CR, the results stated that CR influenced financial distress (FD) positively. Finally, ownership concentration (OC) as moderating interacts with the association between CR and financial distress. The study enhances the knowledge and implications of the theory used for corporate governance dimensions. It provides feedback to regulators and policymakers on the effectiveness of corporate governance mechanisms regarding CR control. The study also offers the Iraqi regulators and policymakers evidence of the harmful impact of CR on financial distress, necessitating their protection of bank investors from such situations by improving established credit rules and laws. This study contributes to the existing body of knowledge by investigating the antecedents and consequences of credit risk in the banking sector. This study also took a further step by examining the moderating role of ownership concentration between CR and FD.

Statistical modeling is a crucial phase for decision-making and predicting future events. Data arising from engineering-related fields have most often complex structures whose failure rate possesses mixed state behaviors (i.e., non-monotonic shapes). For the data sets whose failure rates are in the mixed state, the utilization of the traditional probability models is not a suitable choice. Therefore, searching for more flexible probability models that are capable of adequately describing the mixed state failure data sets is an interesting research topic for researchers. In this paper, we propose and study a new statistical model to achieve the above goal. The proposed model is called a new beta power very flexible Weibull distribution and is capable of capturing five different patterns of the failure rate such as uni-modal, decreasing-increasing-decreasing, bathtub, decreasing, increasing-decreasing-increasing shapes. The estimators of the new beta power very flexible Weibull distribution are obtained using the maximum likelihood method. The evaluation of the estimators is assessed by conducting a simulation study. Finally, the usefulness and applicability of the new beta power very flexible Weibull distribution are shown by analyzing two engineering data sets. Using four information criteria, it is observed that the new beta power very flexible Weibull distribution is the best-suited model for dealing with failure times data sets.

Based on the Stimulus Organism Response theory, this study develops and tests an integrative model that examines, for the first time in the consumer revenge literature, how online acts of revenge influence other consumers present on social media to do the same. This study examines the mediating role of message trustworthiness to better explain the adoption of an online avenger message by other consumers. The study also investigates the moderating effect of avenger expertise on this mediated relationship. Moreover, the moderating role of online activation in triggering other consumers’ desire for revenge is also examined. Using SmartPLS on 211 Jordanian consumers, support for the mediating role of online message trustworthiness in post adoption is found. In addition, this indirect effect of message trustworthiness on the likelihood of other consumers adopting an online revenge post left by a dissatisfied customer is also stronger when avenger expertise is perceived to be high. In addition, it was found that online activation moderated the transition from a desire for revenge to the act of committing online revenge.

Employing low quality feedstocks for biodiesel production can present cost reduction opportunities due to its wide availability and cost effectiveness. However, most low quality feedstocks have high free fatty acid (FFA) content which is not feasible for biodiesel production through direct transesterification due to soap formation. Thus, a pre-treatment step through FFA esterification could reduce the FFA content while simultaneously yielding fatty acid methyl esters (FAME). In this study, the catalytic activity of ten ionic liquids (ILs) were screened for the esterification of FFA in acidic crude palm oil (ACPO). 1‑butyl‑3-methylimidazolium hydrogen sulfate as IL exhibited the highest catalytic activity and was further investigated to determine the optimum operating parameters such as IL dosage, molar ratio, reaction temperature and time. Single factor optimization was employed for the laboratory scale batch esterification reaction. The FFA content was reduced from 10.77% to less than 1% using the following optimum conditions: 4% IL to oil, molar ratio of 10:1 (methanol to oil), 120 min reaction time and 60 °C reaction temperature. Under optimum conditions, the IL can be recycled five times with minimal loss in catalytic activity, highlighting its feasibility as an industrial catalyst for esterification of acidic oils and fats.

The substituted-9-bromo-9,10-dihydro-9,10-ethanoanthracenes ortho 8a-12a and meta 8b-13b have been synthesized via Diels-Alder reaction under microwave conditions. The cycloadduct isomers ortho 8a-11a and meta 8b-11b, with priority to ortho 8a-11a, were obtained from the reaction of 9-bromoanthracene 1 with acrylonitrile 2, 2-chloroacrylonitrile 3, methacryloyl chloride 4 and acrylic acid 5, while ortho 12a and meta 12b, with priority to meta 12b, was obtained from the reaction of 9-bromoanthracene 1 with 1-cynao vinyl acetate 6. Interestingly, the only isomer meta 13b was obtained from the reaction of 9-bromoanthracene 1 with phenyl vinyl sulfone 7. The results proved that the steric or/and electronic nature of the dienophile substituent is/are playing significant roles in the regioselectivity and isomers ratio.

Chloramine-T (CAT), the sodium salt of N-chloro-p-toluenesulfonamide, is a low-cost mild oxidizing agent with a wide range of uses. Most importantly, it can be used in acidic, neutral, and basic conditions. As a result, it’s been widely used in chemistry, particularly in organic synthesis and analytical chemistry. Chloramine-T acts as a source of halonium cation and nitrogen anion and thus acts as base and nucleophile. It reacts with a wide range of functional groups and carries different molecular transformations. This paper thoroughly summarises and highlights the synthetic and analytical effectiveness of CAT. This study focuses on current developments as well as some older techniques in which CAT has been employed as an oxidizing agent. This review article stretches a comprehensive profile of the CAT reagent in organic synthesis and analytical chemistry, which will be very useful for further research exploration in this field.

Chemotherapy is an important therapeutic approach for the treatment of cancer. Currently, many anticancer drugs are available in the market that plays an important role in cancer treatment, but concerns such as, drug resistance and side effects create an urgent need for the development of new anti-tumor drugs with high potency and less side effects. Heterocycles are of great interest due to their fascinating anticancer activity. Among them, 1,3,4-oxadiazoles showed attracting anti-tumor activity and its derivatives are under clinical trials for the treatment of cancer. Hybridization of 1,3,4-oxadiazole moiety with other heterocyclic pharmacophoresis a promising approach to overcome various disadvantages of current anticancer drugs such as drug resistance, toxicity, and other side effects. Thus, 1,3,4-oxadiazole-heterocycle hybrids occupy a significant position in the discovery of anti-tumor drugs. Among the reported oxadiazole-based hybrids reviewed here, compounds 45i, 59j, and 62x showed the highest anticancer activity with IC50 values in the nanomolar range. This review summarizes the recent developments in the anticancer potential, structure–activity relationships, and mechanisms of actions of 1,3,4-oxadiazole-heterocycle hybrids.

The present work includes a numerical study of natural convection heat transfer in symmetrical and unsymmetrical corrugated annuli filled with H2O-Al2O3 nanofluid. In this study, higher and lower temperatures were kept constant at inner and outer cylinders of the annulus; respectively. Eight mathematical models with an aspect ratio of 1.5 were developed to find the best model giving the highest heat transfer rates. The stream-vorticity formulation in curvilinear coordinates was used to solve the governing equations of heat transfer and fluid motion. The influences of Rayleigh number. ((103≤ Ra ≤106) and volume fraction of nanoparticles. (0≤ϕ≤0.25) on isotherms, streamlines, local and average Nusselt numbers on the inner and outer cylinder were investigated. The results show that the heat transfer rate is significantly increased with an increase in nanoparticles volume fraction and Rayleigh number. The activity of the heated surface is increased with an increase in the undulation number, but the flow motion tends to be most difficult in the spaces between active undulation walls. Moreover, the heat transfer rates in unsymmetrical annuli are relatively higher than the rates in the symmetrical annuli. There are no evident changes in isotherms with an increase in the nanofluid volume fraction. Correlations for the mean Nusselt number on the inner and outer walls of annulus were deduced as a function of Rayleigh number and nanoparticles volume fraction for eight models with an accuracy range of 8–15 %.

This paper contains data on Performance Prediction for Cloud Service Selection. To measure the performance metrics of any system you need to analyze the features that affect these performance, these features are called '' workload parameters''. The data described here is collected from the KSA Ministry of Finance that contains 28,147 instances from 13 cloud nodes. It was recorded during the period from March 1, 2016, to February 20, 2017, in continuous time slots. In this article we selected 9 workload parameters: Number of Jobs in a Minute, Number of Jobs in 5 min, Number of Jobs in 15 min, Memory Capacity, Disk Capacity,: Number of CPU Cores, CPU Speed per Core, Average Receive for Network Bandwidth in Kbps and Average Transmit for Network Bandwidth in Kbps. Moreover, we selected 3 performance metrics: Memory utilization, CPU utilization and response time in milliseconds. This data article is related to the research article titled ''An Automated Performance Prediction Model for Cloud Service Selection from Smart Data” (Al-Faifi et al., 2018) [1]. Keywords: Performance metrics, Workload parameters, Cloud computing

Diethylamine catalyzed tandem Knoevenagel–Michael reactions have been carried out in aqueous medium as an efficient, greener and cost effective process for the simple one-pot synthesis of bis-dimedone derivatives. Reaction of substituted aromatic aldehyde (1 equiv.) and dimedone (2 equiv.), in the presence of aqueous diethylamine medium at room temperature provides bis-dimedone derivatives 3a–n in excellent yields (87–95%) within a very short reaction time (15–60 min). All the bis-dimedone derivatives were obtained in high purity and the products were fully characterized by physical and spectroscopic data. The structures of compounds 3b,c were elucidated by single crystal X-ray diffraction technique. Compound 3b crystallizes in the monoclinic space group P 21/n with a = 10.2895(9) Å, b = 18.0995(15) Å, c = 15.8615(13) Å, α = 90°, β = 107.975(2)°, γ = 90°, V = 2809.8(4) Å3, and Z = 4. Compound 3c crystallizes in the monoclinic space group P 21/n with a = 10.2816(16) Å, b = 18.080(3) Å, c = 15.637(2) Å, α = 90°, β = 107.076(4)°, γ = 90°, V = 2778.6(7) Å3, and Z = 4. The use of inexpensive, eco-friendly and readily available reagents, easy work-up, and high purity products makes the procedure a convenient and robust method for the synthesis of tandem Knoevenagel–Michael adducts.

The nitrogen containing spiro-heterocycle is one of the privileged synthetic motif that constitutes various naturally occurring molecules and displays a broad range of pharmaceutical and biological activities. A new methodology was developed for the synthesis of 2,4-diazaspiro[5.5]undecane-1,3,5,9-tetraones spiro-heterocyclic derivatives via cascade cyclization of [5+1] double Michael addition reaction of N,N-dimethylbarbituric acid with the derivatives of diaryldivinylketones in the presence of diethylamine at ambient temperature. The developed protocol is highly capable of furnishing diazaspiro[5.5]undecane derivatives 3a–m in excellent yields (up to 98%), from easily accessible symmetric and non-symmetric divinylketones 2a–m, containing aryl and heteroaryl substituents. The diazaspiro-heterocyclic structure was mainly elucidated by NMR and X-ray crystallographic techniques. The single-crystal X-ray studies revealed that, the cyclohexanone unit of spirocycles often prefers a chair conformation rather than twisted conformation. The intermolecular hydrogen bonding and CArH⋯π, π–π stacking interactions driving forces are mainly responsible for the crystal packing.

Two simple and sensitive kinetic methods for the determination of ampicillin (AMP) are described. The first method is based on kinetic investigation of the oxidation reaction of the drug with alkaline potassium permanganate at room temperature for a fixed time of 25 min. The absorbance of the colored manganate ions is measured at 610 nm. The second method is based on the reaction of AMP with 1-chloro-2,4-dinitrobenzene (CDNB) in the presence of 0.1 mol L−1 sodium bicarbonate. Spectrophotometric measurement was achieved by recording the absorbance at 490 nm for a fixed time of 60 min. All variables affecting the development of the color were investigated and the conditions were optimized. Plots of absorbance against concentration in both procedures were rectilinear over the ranges 5–30 and 50–260 μg mL−1, with mean recoveries 99.80 and 99.91, respectively. The proposed methods were successfully applied for the determination of AMP in bulk powder and in capsule dosage form. The determination of AMP by the fixed concentration method is feasible with the calibration equations obtained, but the fixed time method proves to be more applicable.