Learning EOQ Model with Trade-Credit Financing Policy for Imperfect Quality Items under Cloudy Fuzzy Environment

An imprecise demand rate creates problems in profit optimization in business scenarios. The aim is to nullify the imprecise nature of the demand rate with the help of the cloudy fuzzy method. Traditionally, all items in an ordered lot are presumed to be of good quality. However, the delivered lot may contain some defective items, which may occur during production or maintenance. Inspection of an ordered lot is indispensable in most organizations and can be treated as a type of learning. The learning demonstration, a statistical development expressing declining cost, is necessary to achieve any cyclical process. Further, defective items are sold immediately after the screening process as a single lot at a discounted price, and the fraction of defective items follows an S-shaped learning curve. The trade-credit policy is adequate for suppliers and retailers to maximize their profit during business. In this paper, an inventory model is developed with learning and trade-credit policy under the cloudy fuzzy environment where the demand rate is treated as a cloudy fuzzy number. Finally, the retailer’s total profit is maximized with respect to order quantity. Sensitivity analysis is presented to estimate the robustness of the model.

Virtual-Ligand-Assisted Screening Strategy to Discover Enabling Ligands for Transition Metal Catalysis

The ligand screening process, in which an optimal ligand for a reaction of interest is identified from an enormous and diverse set of candidate molecules, is of particular importance in the development of transition metal catalysis. Conventionally, this process has been performed by experimental trial-and-error cycles, which require significant time and resources. Herein, we report a novel strategy called “virtual-ligand-assisted (VLA) screening” that enables practical in silico ligand screening based on the transition state theory. We developed a virtual ligand, PCl*3, which parameterizes both the electronic and steric effects of monodentate phosphorus(III) ligands in quantum chemical calculations, and used it to assess how these effects perturb the energy profile of a reaction. This parameter-based ligand screening approach allowed us to identify the optimal electronic and steric effects for a reaction of interest, thereby affording guiding principles for rational ligand design. The VLA screening strategy was demonstrated for the selectivity-determining step of the rhodium-catalyzed hydroformylation of a terminal olefin, and phosphorus(III) ligands with potentially high linear or branched selectivities were designed. These findings indicate that VLA screening is a promising approach for streamlining the ligand screening process.

Resveratrol Nanocrystal Incorporated into Mesoporous Material: Rational Design and Screening through Quality-by-Design Approach

Bioflavonoids from grape seeds feature powerful antioxidant and immunostimulant activities, but they present problems related to solubility and bioavailability. Nanocrystal (NC) incorporated into a mesoporous carrier is a promising strategy to address these issues. However, the preparation of this formulation involves the selection of factors affecting its critical quality attributes. Hence, this study aimed to develop an NC formulation incorporating resveratrol into a soluble mesoporous carrier based on rational screening design using a systematic and continuous development process, the quality-by-design paradigm. A mesoporous soluble carrier was prepared by spray-drying mannitol and ammonium carbonate. The NC was obtained by introducing the evaporated solvent containing a drug/polymer/surfactant and mesoporous carrier to the medium. A 26−2 fractional factorial design (FFD) approach was carried out in the screening process to understand the main effect factors. The type and concentration of polymer and surfactant, resveratrol loading, and solvent were determined on the NC characteristics. The results indicated that drug loading, particle size, and solubility were mainly affected by RSV loading, PEG concentration, and Kolliphor EL concentration. The polymer contributed dominantly to reducing the particle size and enhancing solubility in this screening design. The presence of surfactants in this system made it possible to prolong the supersaturation process. According to the 26−2 FFD, the factors selected to be further developed using a statistical technique according to the quality-by design-approach, Box Behnken Design, were Kolliphor EL, PEG400, and RSV loading.

Impact of Surgical Smoke on the Surgical Team and Operating Room Nurses and its Reduction Strategies: A Systematic Review

Background: Surgical smoke is an integral part of surgical operations that the surgical team has been exposed to for so long. This study aimed to investigate the effects of smoke, on members of the surgical team. Methods: A systematic review was conducted focusing on the complexity of surgical smoke. PubMed, Scopus and web of science databases were searched until May 2020 without any time or language limitation. All documents were reviewed by title or abstract according to the search strategy. The screening process of articles was performed by two independent authors. The articles were selected according to the inclusion and exclusion criteria. Results: Overall, 37 studies in this systematic study were investigated. The effects of many surgical smokes were found in a nutshell including complications such as carcinogenic, toxicity, mutation, irritant, transmission of tumor cells, virus transmission, headaches, dizziness, sleepiness, headache, the bad odor in head hair, the tearing of the eye on the surgical team and staff. Conclusion: Surgical smoke, produced during surgical operations, is one of the risks and threats to which the surgical team and operating room staff are at risk then can affect the organs of different bodies from the body of all operating room staff and surgical team.

A systematic review of behaviour change techniques used in interventions to increase physical activity among breast cancer survivors

Background Despite evidence that physical activity (PA) can help reduce recurrence and mortality, many breast cancer survivors are less active than recommended levels. The aim of this systematic review is to advance our understanding of which behaviour change techniques (BCTs) have been used in interventions promoting breast cancer survivors’ PA and to evaluate their potential to increase PA. Methods A systematic search was conducted in five databases (Medline; PsycInfo; Embase; CINAHL and Scopus) for studies published between 2005 and 2019. Following a rigorous screening process, 27 studies were retained. These were reviewed and analysed for quality, coded for BCTs (k = 0.65) and interventions categorised according to their potential to increase PA using an established methodology. Results The majority of studies were moderate quality (64%). Demonstration on how to perform the behaviour was the most commonly used BCT (n = 23). Adding objects to the environment, (pedometer or accelerometer) was the BCT with the highest potential to increase PA. This was followed by, goal setting and self-monitoring of behaviour. A theory-based approach to evaluation was used in only 59% (n = 16) of the studies. Conclusions The results of this review inform which BCTs have the potential to increase PA for breast cancer survivors and inform intervention development. Future research, is encouraged to properly report intervention procedures around dose and frequency of intervention components to allow for review and replication.

Impact of Patient Health Education on the Screening for Disease Test-Outcomes

Screening for diseases is a medical process to predict, prevent, detect, and cure a disease in people at high risk. However, it is limited in the quality and accuracy of the outcomes. The reason for this is the lack of long-term data about the health condition of the patient. Launching modern information and communication technology in the screening process has shown promise of improving the screening outcomes. A previous study has shown that patient education can positively impact the patient behavior face to a disease and can empower the patient to adopt a healthy lifestyle and thus avoid certain diseases. Offering medical education to the patient can positively impact screening outcomes since educated and empowered patients are more aware of certain diseases and can collect significant information. This can minimize the rate of false positive as well as false negative screening results. This chapter analyzes how medical education can contribute to improving screening outcomes.

Efficiency of hybrid algorithm for COVID-19 online screening test based on its symptoms

The coronavirus COVID-19 is affecting 196 countries and territories around the world. The number of deaths keep on increasing each day because of COVID-19. According to World Health Organization (WHO), infected COVID-19 is slightly increasing day by day and now reach to 570,000. WHO is prefer to conduct a screening COVID-19 test via online system. A suitable approach especially in string matching based on symptoms is required to produce fast and accurate result during retrieving process. Currently, four latest approaches in string matching have been implemented in string matching; characters-based algorithm, hashing algorithm, suffix automation algorithm and hybrid algorithm. Meanwhile, extensible markup language (XML), JavaScript object notation (JSON), asynchronous JavaScript XML (AJAX) and JQuery tehnology has been used widelfy for data transmission, data storage and data retrieval. This paper proposes a combination of algorithm among hybrid, JSON and JQuery in order to produce a fast and accurate results during COVID-19 screening process. A few experiments have been by comparison performance in term of execution time and memory usage using five different collections of datasets. Based on the experiments, the results show hybrid produce better performance compared to JSON and JQuery. Online screening COVID-19 is hopefully can reduce the number of effected and deaths because of COVID.

Mathematical modeling for a multiproduct manufacturing system featuring postponement, external suppliers, overtime, and scrap

Manufacturing firms operating in today’s competitive global markets must continuously find the appropriate manufacturing scheme and strategies to effectively meet customer needs for various types of quality of merchandise under the constraints of short order lead-time and limited in-house capacity. Inspired by the offering of a decision-making model to aid smooth manufacturers’ operations, this study builds an analytical model to expose the influence of the outsourcing of common parts, postponement policies, overtime options, and random scrapped items on the optimal replenishment decision and various crucial system performance indices of the multiproduct problem. A two-stage fabrication scheme is presented to handle the products’ commonality and the uptime-reduced strategies to satisfy the short amount of time before the due dates of customers’ orders. A screening process helps identify and remove faulty items to ensure the finished lot’s anticipated quality. Mathematical derivation assists us in finding the manufacturing relevant total cost function. The differential calculus helps optimize the cost function and determine the optimal stock-replenishing rotation cycle policy. Lastly, a simulated numerical illustration helps validate our research result’s applicability and demonstrate the model’s capability to disclose the crucial managerial insights and facilitate manufacturing-relevant decision making.

Article 25: The Right to Periodic Review of Treatment and All Other Circumstances of Placement

Abstract‘More in-depth screening process for foster parents to ensure the housing placement will be safe before the follow-up.’ (Western Europe/Other)