Distribution-free (or nonparametric) monitoring schemes are needed in industrial, chemical and biochemical processes or any other analytical non-industrial process when the assumption of normality fails to hold. The Mann-Whitney (MW) test is one of the most powerful tests used in the design of these types of monitoring schemes. This test is equivalent to the Wilcoxon rank-sum (WRS) test. In this paper, we propose a new distribution-free generally weighted moving average (GWMA) monitoring scheme based on the WRS statistic. The performance of the proposed scheme is investigated using the average run-length, the standard deviation of the run-length, percentile of the run-length and some characteristics of the quality loss function through extensive simulation. The proposed scheme is compared with the existing parametric and nonparametric GWMA monitoring schemes and other well-known control schemes. The effect of the estimated design parameters as well as the effect of the Phase I sample size on the Phase II performance of the new monitoring scheme are also investigated. The results show that the proposed scheme presents better and attractive mean shifts detection properties, and therefore outperforms the existing monitoring schemes in many situations. Moreover, it requires a reasonable number of Phase I observations to guarantee stability and accuracy in the Phase II performance.

Flibanserin (Addyi) is a medication used to treat women who have not gone through menopause who have low sexual desire. Specific and simple stability indicating method was developed and validated by high-performance liquid chromatography (RP-HPLC) for the determination of Flibanserin. Separation was carried out by using a mobile phase consisting of 0.01M Potassium phosphate monohydrate buffer (KH₂PO₄) pH 3.50 buffer: Acetonitrile in the ratio of 60:40. The column used was Agilent C18, (150×4.6) mm, 5µm with a flow rate of 1.0ml/min and temperature at 30°C. The detection was carried out at 248 nm and Flibanserin was eluted at around 2.8min. This method was validated as per ICH guidelines and validation included specificity, precision, linearity, accuracy, forced degradation, and robustness. Forced degradation was conducted under the conditions of hydrolysis, oxidation, thermal, acid, base, and peroxide hydrolysis. The calibration curve was linear over the concentration range from 20 to 200µg/mL and the coefficient of determination (r²) was observed as 0.9998. The precision and accuracy of the method were within the acceptable range. The results of this study showed that the validated method is simple and accurate, which confirmed that the method is suitable for the determination of Flibanserin.

The present manuscript describes an in-depth analysis of various interactions present in the crystal structure of formyl coumarins using Crystal explorer 17.0. Element based interactions were quantified by the decomposition of generated 3D surfaces into 2D fingerprint regions. DFT methods were used to explore electrostatic parameters, global and local reactivity descriptors. Electrophilicity based charge transfer (ECT) analysis was done to explore the probability of charge transfer between formyl coumarins and DNA base pairs. The reactivity and selectivity of different formyl coumarins have been accessed using Fukui functions in their reduced form. Non-bonding orbital (NBO) analysis revealed the presence of various hyperconjugative interactions and their stabilization energy in formyl coumarins. Non-linear optical properties are presented in terms of first order hyperpolarizibility (β₀), where maximum β₀ is observed for C4 (1.64 × 10-30esu.) which is found to be 2 times greater than that of p-nitroaniline. Molecular electrostatic potential (MEP) plots are mapped in terms of electron density.

The Vehicle Routing Problem with Loading Constraints (VRPLC) is strongly related to real life applications in distribution logistics. It addresses the simultaneous loading and routing of vehicles, which are two crucial activities in transportation. Since treating these operations separately may result in impractical solutions, the development of applications for VRPLCs has gained the attention of researchers in recent years. Several heuristic methods have been proposed, but they consider only a limited group of practical characteristics that arise in real world situations. This study proposes a hybrid heuristic method based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic and the Clarke and Wright Savings algorithm, to solve a VRPLC with several loading and routing constraints that have not been considered simultaneously before. Experimental results show that the proposed procedure produces competitive solutions in short processing times. Lastly, the impact of the added operational constraints is also analyzed.

The literature on flow shop scheduling has extensively analyzed two classes of problems: permutation and non-permutation ones (PFS and NPFS). Most of the papers in this field have been just devoted on comparing the solutions obtained in both approaches. Our contribution consists of analyzing the structure of the critical paths determining the makespan of both kinds of schedules for the case of 2 jobs and m machines. We introduce a new characterization of the critical paths of PFS solutions as well as a decomposition procedure, yielding a representation of NPFS solutions as sequences of partial PFS ones. In structural comparisons we find cases in which NPFS solutions are dominated by PFS solutions. Numerical comparisons indicate that a wider dispersion of processing times improves the chances of obtaining optimal non-permutation schedules, in particular when this dispersion affects only a few machines.

This paper is interested in pharmaceuticals distribution which is one of the most important activities and ensures the availability of drug products to a set of customers (pharmacies). The study introduces the Disrupted Vehicle Routing problem with Soft Time Windows since pharmaceutical distributors should respond to increased demands for products to ensure timely and efficient delivery to dynamic demands. We also propose an improved multiobjective local search (IMOLS), which uses methods of neighborhood search such as large neighborhood search (LNS) and variable neighborhood search (VNS) based on a hybrid approach in the optimization of vehicle routes. The algorithm is expected to achieve competitive results compared with previously published studies.

Most of the organizations today look forward to streamlining their business with the rapid needs of the society. However, they do not consider the holistic view of various digital driving factors. The paper aimed to develop a structural framework using the enablers of Digital Transformation (DT) by applying qualitative and rational approaches to develop a conceptual model of DT adoption for various industries. The assimilated approach of Delphi and Interpretive Structural Modelling demonstrated the qualitative data-driven theoretical structure by identifying fourteen enablers of DT and developed a logical model in nine levels. The driving and dependency powers of each enabler were portrayed in MIC MAC analysis. The government regulation and market pressure found as key drivers with strong driving and low dependency powers occupying the lowest level which influences customer demand, behavior and expectations and process, performance improvement of the business. The model demonstrates a deep understanding of global firms to leverage various dimensions while taking transformation decisions in their business process and gain a competitive edge. Further, any organization that looks for adopting digital transformation can consider these factors or models in deciding the implementation process. It recommends researchers to validate the model or may prioritize the factors and sub-factors for multi-criterion based decision making process for unique findings.

Cement & material sector is instrumental in infrastructural development of any economy. The same holds about Saudi cement sector which has contributed substantially to the economic and construc-tion boom in Kingdom of Saudi Arabia (KSA). The cement sector of KSA holds the highest place among other GCC countries. Though, during the last couple of years, the sector seems to be grap-pled with capacity and weighted down due to certain reasons. Nevertheless, almost all of the cement companies in KSA are underplaying their actual capacities. Still, plenty of untapped growth oppor-tunities for cement sector are available in KSA and other GCC countries. Henceforth, considering the growth potential and taking cue from the current scenario of KSA cement sector, the current study endeavors to measure the efficiency of listed cement companies in KSA. The study endeavors to be engrossed in identifying a set of companies which plays on efficiency frontier. Therefore, the technical efficiency performance of fourteen listed cement companies in KSA was measured using Data Envelopment Analysis (DEA) methodology. Two basic models of DEA methodology (i.e. CRS & VRS) were used to estimate the pure and technical efficiency of identified DMUs over a pe-riod of four years from 2016 to 2019. The study reveals that over a period of four years and on an average efficiency scale, only 23% of the firms were purely technically efficient on a CRS scale, while 46% of the firms were technically efficient. Only 23% of the firms were scale and technically efficient. Though, companies in the sector have a vast potential to outperform on efficiency front. Yet, the overall efficiency level among Saudi cement companies are remained depressing. Moreo-ver, the study has noticed that the companies which are inefficient did not have a considerable dis-tance from the efficiency frontier. The study also provided significant insights on the input factors causing inefficiency and suggestion to achieve the total technical efficiency. Furthermore, the effi-ciency analysis also provided benchmarking firms, which are efficient under several criteria for oth-ers to imitate their best practices for becoming a significant player on efficiency frontier.

Success key elements are crucial for the improvement and preservation of competitiveness in the ho-tel sector. Hotels thus need efficient employees with best possible quality of work life to remain competitive. This paper investigated the impact of organisational structure (OS) and leadership style (LS) on quality of work life (QWL) among five-star hotels employees in Jordan with job satisfac-tion (JS) as mediator. Questionnaires were distributed among 430 five-star hotel employees to ob-tain the study data. The levels of relationships among the constructs (OS, LS, JS, and QWL) were analysed using partial least squares structural equation modelling (PL-SEM). The results showed a positive relationship of JS and OS with QWL, while JS showed a partial mediating role on the rela-tionship among LS, OS and QWL. Similar studies should be carried out on other sectors in Jordan and in other settings using different perspectives.

The purpose of this research is to develop a conceptual model to explain the relationship between the uniqueness of higher education, student experience and university image. Structural Equation Modeling (SEM) is an analytical technique used to test the model. Data collection is conducted on 268 active students from 49 private universities in Java West. Research findings report the uniqueness of tertiary institutions influences student experience; uniqueness of tertiary institutions influences the image of the University. Moreover, experience of students influences the image of the University.