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Real-world data have become increasingly important in medical science and healthcare. A new, effective, and practically feasible statistical design is needed to unlock the potential of real-world data that decision-makers and practitioners can use to meet people's healthcare needs. In the first half of the study, we validated our proposed new method by simulation, and in the second half, we conducted a clinical study on actual real-world data. We proposed the "Exact Matching Algorithm Using Administrative Health Claims Database Equivalence Factors (AHCDEFs)" using a target trial emulation framework. The simulation trials were conducted 500 times independently, considering the misclassification and chance errors of all variables and competing events of outcome. Two conventional methods, multivariate and propensity score analyses, were compared. Next, we estimated the effect of specific health guidance provided in Japan on the prevention of diabetes onset and medical expenditures. Our proposed novel method for real-world data returns improved estimates and fewer type I errors (the probability of erroneously determining that there is a difference when, in fact, there is no difference) than conventional methods. We quantitatively demonstrated the effectiveness of specific health guidance in Japan in preventing the onset of diabetes and reducing medical expenditures during five years. We proposed a new method for analyzing real-world data and an exact-matching algorithm using AHCDEFs. The larger the number of patients available for analysis, the more the AHCDEFs that can be matched, thereby removing the influence of confounding factors. This method will generate significant evidence when applied to real-world data. [ABSTRACT FROM AUTHOR]

This article is concerned with sample size determination methodology for prediction models. We propose to combine the individual calculations via learning‐type curves. We suggest two distinct ways of doing so, a deterministic skeleton of a learning curve and a Gaussian process centered upon its deterministic counterpart. We employ several learning algorithms for modeling the primary endpoint and distinct measures for trial efficacy. We find that the performance may vary with the sample size, but borrowing information across sample size universally improves the performance of such calculations. The Gaussian process‐based learning curve appears more robust and statistically efficient, while computational efficiency is comparable. We suggest that anchoring against historical evidence when extrapolating sample sizes should be adopted when such data are available. The methods are illustrated on binary and survival endpoints. [ABSTRACT FROM AUTHOR]

Despite its use in one form or another for at least four decades, HALT and related techniques [e.g., highly accelerated‐stress screening (HASS) and stress audits (HASA)] are not well understood within the statistical community and remain controversial. This largely reflects a conflict in motivation between engineers, testing under harsh conditions to discover and eliminate failure modes, and statisticians, taking a more cautious approach to develop quantitative estimates of parameters such as mean time between failures (MTBF). This review article will clarify HALT concepts and methods and explain where it fits within the universe of methods that involve the application of accelerating factors to compress the time required to evaluate or enhance product reliability. A major distinction is between methods such as HALT, a high‐stress test‐analyze‐fix‐test iterative process directed at improving reliability by discovering and fixing weak points in a design, and quantitative accelerated life testing (QALT), whose goal is the estimation of product life for a fixed design. We discuss methods such as physics of failure that offer some hope of bridging the gap between the qualitative nature of HALT, and purely quantitative statistical methods. We present a variety of engineering applications of HALT including metal fatigue, piping and pressure vessels, structural damage, radiation damage, and rotating machinery. We also discuss potential synergies between HALT and QALT, such as rapid identification, through HALT, of failure modes requiring quantitative analysis. For further study, extensive references to the applicable literature are provided as well as an appendix that describes related methods. This article is categorized under:Statistical and Graphical Methods of Data Analysis > Reliability, Survivability, and Quality Control [ABSTRACT FROM AUTHOR]

Vigorous discussions are ongoing about future efficacy trial designs of candidate human immunodeficiency virus (HIV) prevention interventions. The study design challenges of HIV prevention interventions are considerable given rapid evolution of the prevention landscape and evidence of multiple modalities of highly effective products; future trials will likely be 'active-controlled', i.e., not include a placebo arm. Thus, novel design approaches are needed to accurately assess new interventions against these highly effective active controls. To discuss active control design challenges and identify solutions, an initial virtual workshop series was hosted and supported by the International AIDS Enterprise (October 2020-March 2021). Subsequent symposia discussions continue to advance these efforts. As the non-inferiority design is an important conceptual reference design for guiding active control trials, we adopt several of its principles in our proposed design approaches. We discuss six potential study design approaches for formally evaluating absolute prevention efficacy given data from an active-controlled HIV prevention trial including using data from: 1) a registrational cohort, 2) recency assays, 3) an external trial placebo arm, 4) a biomarker of HIV incidence/exposure, 5) an anti-retroviral drug concentration as a mediator of prevention efficacy, and 6) immune biomarkers as a mediator of prevention efficacy. Our understanding of these proposed novel approaches to future trial designs remains incomplete and there are many future statistical research needs. Yet, each of these approaches, within the context of an active-controlled trial, have the potential to yield reliable evidence of efficacy for future biomedical interventions. [ABSTRACT FROM AUTHOR]

Co-amorphous systems are an evolving strategy to stabilize the amorphous form of a drug molecule with the aim of overcoming its poor water-solubility. With research focussing on the molecular level of co-amorphous systems, little is known about their downstream processing. In this study, tablets of co-amorphous carvedilol and aspartic acid (CAR-ASP) with calcium hydrogen phosphate and croscarmellose sodium as excipients were produced using a compaction simulator. The amorphous form of spray dried CAR-ASP and the subsequently produced tablets was confirmed with XRPD. Over the storage time of 12 weeks, no recrystallization of the amorphous material was observed. A central composite face-centred design with three factors was set up to investigate the interplay of formulation and processing variables with the tablet characteristics elastic work, tensile strength and disintegration time. As a result, increasing the amount of co-amorphous material led to a decrease in elastic work and an increased tensile strength. These effects were beneficial for tablet properties, namely harder tablets and reduced elasticity. Disintegration time was prolonged by amounts of up to 25–30% co-amorphous material, while larger amounts induced faster tablet disintegration. While showing the feasibility of compacting co-amorphous material with calcium hydrogen phosphate, this study also gives insight into how tablet characteristics are affected by co-amorphous material and relevant process parameters. [ABSTRACT FROM AUTHOR]

Since the release of ICH E6(R2), multiple efforts have been made to interpret the requirements and suggest ways of implementing quality tolerance limits (QTLs) alongside existing risk-based quality management methodologies. While these efforts have contributed positively to developing a common understanding of QTLs, some uncertainty remains regarding implementable approaches. In this article, we review the approaches taken by some leading biopharmaceutical companies, offering recommendations for how to make QTLs most effective, what makes them ineffective, and several case studies to illustrate these concepts. This includes how best to choose QTL parameters and thresholds for a given study, how to differentiate QTLs from key risk indicators, and how QTLs relate to critical-to-quality factors and the statistical design of the trials. [ABSTRACT FROM AUTHOR]

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In 2020, the whole planet was plagued by the extremely deadly COVID-19 pandemic. More than 83 million people had been infected with COVID-19 while more than 1.9 million people around the planet had died from this virus in the first year of the pandemic. From the first moment, the medical community started working to deal with this pandemic. For this reason, many clinical trials have been and continue to be conducted to find a safe and efficient cure for the virus. In this paper, we review the 96 clinical trials, registered in the ClinicalTrials.gov database, that had been completed by the end of the first year of the pandemic. Although the clinical trials contained significant heterogeneity in the main methodological features (enrollment, duration, allocation, intervention model, and masking) they seemed to be conducted based on an appropriate methodological basis. [ABSTRACT FROM AUTHOR]

A thermally bonded biodegradable fabric has been developed using mesta and polylactic acid fibers. The central composite rotatable design has been adapted to understand the effects of the independent variables, that is polylactic acid content, roller temperature and roller pressure on useful functional properties such as bursting strength, bending load, tensile stress relaxation, tensile creep, rate of absorption, absorption capacity, porosity, abrasion resistance, and surface friction. Considering the linear, quadratic, and two-way interactive effects of independent variables, the second-order polynomial has been suggested for each property which proves good association except for absorption capacity and abrasion resistance. The effect of independent parameters has been studied and optimized from contour diagrams. The optimized process parameters for 140 g/m2 fabric are polylactic acid content 30%, mesta content 70%, roller temperature 170°C, and roller pressure 150 N/cm2, which can be used successfully as a shopping bag. The shopping bag was prepared from developed fabric. Its performance test shows no deformation for up to 14 days in the hanging test, resistance up to 10 wetting-drying cycles proves reusability, it sustains up to four drops, and has a slight strength loss in 30 days of atmospheric exposure. [ABSTRACT FROM AUTHOR]

Bayesian statistics is an approach for learning from evidences as it accumulates, combining prior distribution with current information on a quantity of interest, in which posterior distribution and inferences are being updated each time new data become available using Bayes’ Theorem. Though frequentist approach has dominated medical studies, Bayesian approach has been more and more widely recognized by its flexibility and efficiency. Research and development (R&D) on anti-cancer new drugs have been so hot globally in recent years in spite of relatively high failure rate. It is the common demand of pharmaceutical enterprises and researchers to identify the optimal dose, regime and right population in the early-phase R&D stage more accurately and efficiently, especially when the following three major changes have been observed. The R&D on anticancer drugs have transformed from chemical drugs to biological products, from monotherapy to combination therapy, and the study design has also gradually changed from traditional way to innovative and adaptive mode. This also raises a number of subsequent challenges on decision-making of early R&D, such as inability to determine MTD, flexibility to deal with delayed toxicity, delayed response and dose-response changing relationships. It is because of the above emerging changes and challenges that the Bayesian approach is getting more and more attention from the industry. At least, Bayesian approach has more information for decision-making, which could potentially help enterprises achieve higher efficiency, shorter period and lower investment. This study also expounds the application of Bayesian statistics in the early R&D on anticancer new drugs, and compares and analyzes its idea and application scenarios with frequentist statistics, aiming to provide macroscopic and systematic reference for all related stakeholders.

The purpose of this article is to optimize the power supply subsystem of the satellite based on mass and power production. For this purpose, the satellite orbit is to determine the time of placement in the shadow in Satellite Tool kit (STK) software, and the design of the satellite energy supply subsystem of existing analytical equations are done, and these main design parameters have been optimized to achieve the minimum weight of system. Then, the beginning of the target satellite, the Orsted satellite, the orbital and mission operational modes of this satellite has been compiled and the statistical information of its power supply subsystem has also been determined. Then, the design of the power supply sub-system is based on the parametric analysis and processing of statistical information and also based on the simulation and orbital analysis of the satellite. Finally, in order to model the design problem, the objective functions of design and optimization, the weight of the power supply subsystem has been considered, and the main design parameters affecting the objective function are capacity, depth of discharge, efficiency and density of the battery and the area of the arrays. It is worth mentioning that the type of battery itself is also very effective on the objective function, but considering the type of satellite battery considered (nickelcadmium), the variable battery type is not considered. Finally, this problem has been optimized using genetic algorithm. The obtained results show the accuracy of the method and implementation compared to the values of the existing satellite power supply subsystem. [ABSTRACT FROM AUTHOR]

A sustainable flexible nonwoven fabric has been developed using jute (Corchorus olitorius) and polylactic acid (PLA) fibres. The thermal bonding technique has been used to soften the PLA component which behaves as the matrix in jute fibre reinforcement. The central composite rotatable design has been adapted to understand the effects of the independent variables, such as PLA content, roller temperature and roller pressure on mechanical properties, such as tenacity, breaking elongation, initial modulus, energy-at-break, bursting strength and tear strength. Considering the linear, quadratic and two-way interactive effects of independent variables, the second-order polynomial has been suggested which proves good association. The optimised process parameters are PLA content 30%, jute content 70%, roller temperature 170°C and roller pressure 150 N/cm2. The property comparison with commercial bag fabric shows that the developed jute-PLA fabric is better in many useful aspects. Three types of bags with carrying capacity of 2.5, 5 and 10 kg have been prepared. The results of the hanging test, wetting test, drop resistance test and atmospheric resistance test of the developed bag in comparison to the commercial bag show that the developed bag from jute-PLA performs better. No significant change is found after 10 wetting-drying cycles and hence, the bags are reusable. The fabric can be used successfully as a carry bag or shopping bag. As the process and components of developed fabric are ecofriendly, it will be sustainable and ecofriendly. [ABSTRACT FROM AUTHOR]

Pigments of natural origin have become a research trend, and fungi provide a readily available alternative source. Moreover, developing novel processes that increase yields, reduce process time and simplify downstream processing is of increased interest. In this sense, this work proposes an alternative for Talaromyces atroroseus GH2 biomass re-utilization to produce pigments through consecutive batches using immobilized mycelium. Different support materials were evaluated for pigment production and immobilization capacity. Then, Taguchi's method was applied to determine the effect of four factors related to fungal immobilization and pigment production (inoculum concentration, support density, working volume and support volume). Afterward, process kinetics for pigment production using immobilized cells of T. atroroseus GH2 in consecutive batches were evaluated. All evaluated factors were significant and affected pigment production and microorganism growth differently. At improved conditions, immobilization capacity reached 99.01 ± 0.37% and the pigment production was 30% higher than using free cells. Process kinetics showed that the production could continue for three batches and was limited by excessive microorganism growth. Indeed, more studies are still needed, but the immobilization of Talaromyces atroroseus GH2 represents a promising strategy for allowing downstream-processing intensification since immobilized biomass is easily removed from the fermentation media, thus paving the way for the further development of a continuous process. [ABSTRACT FROM AUTHOR]

Vigorous discussions are ongoing about future efficacy trial designs of candidate human immunodeficiency virus (HIV) prevention interventions. The study design challenges of HIV prevention interventions are considerable given rapid evolution of the prevention landscape and evidence of multiple modalities of highly effective products; future trials will likely be 'active-controlled', i.e., not include a placebo arm. Thus, novel design approaches are needed to accurately assess new interventions against these highly effective active controls. To discuss active control design challenges and identify solutions, an initial virtual workshop series was hosted and supported by the International AIDS Enterprise (October 2020-March 2021). Subsequent symposia discussions continue to advance these efforts. As the non-inferiority design is an important conceptual reference design for guiding active control trials, we adopt several of its principles in our proposed design approaches. We discuss six potential study design approaches for formally evaluating absolute prevention efficacy given data from an active-controlled HIV prevention trial including using data from: 1) a registrational cohort, 2) recency assays, 3) an external trial placebo arm, 4) a biomarker of HIV incidence/exposure, 5) an anti-retroviral drug concentration as a mediator of prevention efficacy, and 6) immune biomarkers as a mediator of prevention efficacy. Our understanding of these proposed novel approaches to future trial designs remains incomplete and there are many future statistical research needs. Yet, each of these approaches, within the context of an active-controlled trial, have the potential to yield reliable evidence of efficacy for future biomedical interventions. [ABSTRACT FROM AUTHOR]

This paper presents a probabilistic study of anchor–soil bond stress performance in a post-grouted anchor wall. The variability of geotechnical shear strength parameters will be described by a probability density function (PDF) and as a linear and squared shear strength function with depth based on widely available standard penetration test (SPT) data on two geologies (mudflows and residual soils). Monte Carlo simulation was carried out to evaluate the mean and standard deviation of ultimate anchor strength. The study allows the factor of safety (FS) to be determined to achieve a target probability of failure (pf). The first analyses consist of a probabilistic analysis without considering the shear strength varying with depth (SSVD), while the second one includes SSVD. Probabilistic analyses (without SSVD) show that a reduction of the pf depends only on the design FS. The probabilistic SSVD analyses showed that the N-value at the surface (N0), and the function gradient (ρ) had an important influence on the anchor pf. It is shown that the use of an overall FS can be considered as a high-risk design for soils with a high N0 variability and low ρ. Therefore, the target pf shows that the top anchors are the most critical, so higher FS values are required (FS > 2.5), especially for mudflow soils. [ABSTRACT FROM AUTHOR]

Developing a plan for data analysis at the beginning of a study is an important practice that is underutilized in many scientific fields. Several funding agencies and journals now require submission of statistical analysis plans in advance of scientific studies, particularly in the clinical sciences. Even when a plan is not required, it can be advantageous to the scientific process by improving reproducibility. An analysis plan allows researchers to organize their knowledge about their research questions and experimental design to more easily recognize and choose the appropriate statistical analyses. An analysis plan provides a roadmap for the analyses: Researchers can think through potential statistical decisions (e.g. to transform or not to transform? how to handle missing or censored data?) in advance and thoroughly document the justifications and trade‐offs for their intended analyses. Such decisions are not influenced by data when made before data collection, thus preventing pitfalls like p‐hacking, HARKing and non‐replicability of results. We describe a general framework for crafting an analysis plan—including essential components of any plan—and provide an example template that can be used by researchers. The analysis plan framework is presented for broad appeal to experienced statisticians, quantitative researchers and everyone in between. [ABSTRACT FROM AUTHOR]

Background: WHO acclaims superiority of levofloxacin for the treatment of drug-resistant tuberculosis. Purpose: The purpose of this research was to develop levofloxacin-loaded solid lipid nanoparticles (LEV-SLN) for use in tuberculosis treatment. The goal was to make LEV-SLN with a mean particle size of less than 300 nm, a drug release duration of more than 12 h, and an LEV-SLN MMAD of less than 5 µm. Methods: LEV-SLN was made using a single emulsification process, followed by solvent evaporation and lyophilization. A Plackett–Burman screening design and a 32 full factorial design were employed sequentially to explore the impact of various formulation and process parameters on mean particle size, % entrapment efficiency, and in vitro drug release. Results: According to the Pareto chart from the Plackett–Burman screening design, the amount of poloxamer and homogenization speed had a significant influence on the mean particle size (p < 0.05). LEV-SLN had a minimum inhibitory concentration of 0.7 µg/ml, whereas pure drug had a minimum inhibitory value of 1.0 µg/ml. The F-ratio for each model developed was higher than the theoretical value (p < 0.05) in a follow-up analysis employing 32 full factorial design, showing that each model was significant. Conclusion: The best formulation had a mean particle size of 79.70 nm, lasted 12 h in simulated lung fluid, and had an MMAD of 3.71 µm, confirming that the drug may reach up to deep lungs. In the future, preclinical study is needed to develop a realistic dosing regimen and determine the pharmacokinetics and pharmacodynamics of LEV-SLN. [ABSTRACT FROM AUTHOR]

Ophiorrhiza mungos (O. mungos) , a significant medicinal plant belonging to the Rubiaceae family, is native to the Indian subcontinent and predominantly found in countries like India, Nepal, Bhutan, Bangladesh, and Sri Lanka. Recently, it has gained recognition as a promising alternative source of anticancer compounds. The presence of camptothecin (CPT), a modified monoterpene indole alkaloid, in notable quantities has sparked interest in researching O. mungos. This present study is focused on enhancing the synthesis of CPT through in vitro shoot growth of O. mungos using a half-strength Murashige and Skoog growth medium supplemented with specific precursors. Among the precursors tested, L-tryptophan and geraniol exhibited the most significant increase in CPT levels, with a 33 % enhancement compared to the untreated shoots. The researchers employed response surface methodology to explore the combined effect of these precursors on CPT production. In the study, in vitro plantlets were treated with L-tryptophan and geraniol at a concentration of 1.5 mM each, resulting in the highest CPT levels ranging from 1658.52 to 1747.63 µg/g. The validity of the experimental approach was confirmed by the close agreement between the experimental value and the predicted value of 1702.00 µg/g, demonstrating a 99.3 % validity of the model. This study underscores the significance of utilizing a combination of precursors to enhance the production of secondary metabolites, specifically CPT, in O. mungos shoot cultures. Furthermore, it identifies L-tryptophan and geraniol, along with their respective doses, as effective precursors for improved CPT synthesis. Notably, this research employed response surface methodology to investigate the potential of L-tryptophan and geraniol as precursors for CPT production in the in vitro shoot growth of O. mungos , marking a significant contribution in this field of study. Top of Form [Display omitted] • Precursor feeding of Ophiorrhiza mungos in vitro shoots to enhance camptothecin production. • The potential of L-tryptophan and geraniol as precursors for camptothecin production. • L-tryptophan and geraniol at a concentration of 1.5 mM each, for increased camptothecin levels in Ophiorrhiza mungos in vitro shoots. [ABSTRACT FROM AUTHOR]

Solid state fermentation (SSF) simulates the natural conditions fungal growth, where the amount of water in the reaction medium must be restricted, thus limiting the use of liquid substrate. An analytical strategy to deal with this limitation is the design of blending with constraints. Thus, the objective of the work was to optimize two constrained waste mixtures for the production of lipase by Penicillium roqueforti ATCC 10110 under SSF, using different substrates that combine solid and liquid waste. For this, the best fermentation time was determined through a fermentative profile, afterwards a restricted-mix design with lower and upper limits of the components of mixture I (cocoa residue, solid palm oil residue and liquid palm oil residue) and II (cocoa residue, mango residue and palm oil residue liquid palm) was applied. By means of Pareto and contour graphs, the maximum production points of lipase in mixtures I (6.67 ± 0.34 U g−1) and II (6.87 ± 0.35 U g−1) were obtained. The restricted mixture design proved to be a promising tool in the production of lipase by P. roqueforti ATCC 10110 under SSF since the use of restrictions is useful when intending to combine solid and liquid residues in fermentation processes. [ABSTRACT FROM AUTHOR]

Oil shale must have a large quantity of kerogen to be of economic benefit, but oil shale with about 30% kerogen is a low-quality ore. Thus, the column flotation technique has been utilized to increase its quality, and the results were analyzed by a reduced two-level factorial design to optimize the interaction effects of seven parameters by response surface modeling. The perturbation plots were used to identify the optimum conditions leading to a predicted maximum kerogen concentration of 53.2% and kerogen recovery of about 81% at estimated optimum conditions of 15% solid concentration, 0.36 cm/s superficial wash water flow rate, 0.28 cm/s superficial feed flow rate, 10 ppm frother concentration, 10 cm froth depth, 1.5 cm/s superficial air flow rate, and 1.5 kg/t pine oil collector dosage. Whereas, the validation experiments under these optimum values gave similar kerogen concentration and recovery of about 52.9–53.6% and 80–82%, respectively. [ABSTRACT FROM AUTHOR]

Monoacylglycerol (MAG) and diacylglycerol (DAG) are two natural components found in most edible oils and fats. Conventional synthesis of MAG and DAG is usually conducted by glycerolysis of triacylglycerol (TAG) at high temperatures (above 200°C) in the presence of an alkaline catalyst. In this work, the synthesis of MAG and DAG using enzymatic glycerolysis of olive oil was investigated using Tween 80 as surfactant, n‐butanol as co‐surfactant and the novel lipase in free/liquid formulation Lipozyme TL 100L as catalyst. Experimental design was used to evaluate the effect of enzyme load and reaction temperature on the feedstock conversion. Enzyme load and system temperature were significant variables in the statistical design and the best condition was found at 35°C, 7.5 vol% of Lipozyme TL 100L and glycerol to oil volumetric ratio of 2:1 with conversion of TAG at approximately 98% after 2 h of process. A mathematical model based on the Ping‐Pong Bi‐Bi mechanism was used to describe the reaction kinetics. The model adequately described the behavior of the system and can be a useful tool for the design of reactors in larger scales. [ABSTRACT FROM AUTHOR]

Gait data are commonly presented as an average of many trials or as an average across participants. Discrete data points (eg, maxima or minima) are identified and used as dependent variables in subsequent statistical analyses. However, the approach used for obtaining average data from multiple trials is inconsistent and unclear in the biomechanics literature. This study compared the statistical outcomes of averaging peaks from multiple trials versus identifying a single peak from an average profile. A series of paired-samples t tests were used to determine whether there were differences in average dependent variables from these 2 methods. Identifying a peak value from the average profile resulted in significantly smaller magnitudes of dependent variables than when peaks from multiple trials were averaged. Disagreement between the 2 methods was due to temporal differences in trial peak locations. Sine curves generated in MATLAB confirmed this misrepresentation of trial peaks in the average profile when a phase shift was introduced. Based on these results, averaging individual trial peaks represents the actual data better than choosing a peak from an average trial profile. [ABSTRACT FROM AUTHOR]

Evaluation possibility of a low-quality Egyptian oil shale from Wadii El-Nakhil, Red sea region as an alternative clean fuel by advanced flotation technique via column flotation was investigated. XRD analysis showed that the non-clay minerals associated with the oil shale sample include; quartz, siderite, apatite, anhydrite, and calcite. Column flotation experiments were carried out and results were analyzed according to screening designs which are used when numerous parameters would affect a particular process. Reduced three-factor interactions (3 FI) two-level factorial experimental design were employed to evaluate the effects of the seven independent parameters. Besides, the contour plots were used to summarize the optimum reaction factors leading to a predicted maximum kerogen grade of 52.35% and kerogen recovery of 78.41%. The calculated optimum parameters were 15% solid concentration, 0 cm/s superficial wash water velocity, 0.49 cm/s feed superficial velocity, 40 ppm frother concentration, 40 cm froth depth, 0.67 cm/s superficial air velocity and 0.5 kg/ton kerosene collector dosage. The confirmation tests, at optimum conditions as predicted from the contour plots, gave approximately the same grade and recovery of about 54% and 80%, respectively. [ABSTRACT FROM AUTHOR]

Background: Biopolymer based edible films have emerged as potential alternatives for conventional plastics in food packaging industry. The properties such as thickness, water vapour transmission rate (WVTR) and transparency of these films would be significantly influenced by the solution components and concentration and process conditions (pH, temperature and relative humidity of drying). Results: Control and glycerol blended pectin films were developed as per 2³ (two-level three-factor) factorial design of experiments by varying glycerol fraction (25% and 40% w/w) and solution concentration (3% and 5% w/v). The films made from 5% solution showed good moisture barrier properties. Glycerol addition reduced the moisture barrier capability of the films compared to control pectin films. Statistical analysis suggests that, the solution pH and drying temperature considerably affect film properties while the effect of relative humidity of drying is not evident enough. However, the interaction effect of relative humidity (H) with the pH and temperature appeared significant. Regression models were fitted to the data by considering the main and interaction effects, which were significantly affecting a particular property. Conclusions: Detailed analysis reveals that for obtaining pectin based films with less thickness, low WVTR and high transparency, the optimal conditions preferred are low pH = 3, high T = 48°C and low to medium humidity of drying (H = 40-50%). The fitted regression models were statistically significant at 90% confidence level, pass Lack-of-fit analysis and are adequate to describe the effects of different factors on the targeted film properties. [ABSTRACT FROM AUTHOR]

A statistical design approach of an ad-hoc fixed-structure controller in the stabilization loop of a single axis gyro-stabilized platform, that allows adjusting for main disturbances acting on the stabilization loop, was presented. A script in Python language computerizing the optimal design procedure was developed and applied to the mathematical model of the single axis gyro-stabilized platform. [ABSTRACT FROM AUTHOR]

Biological variation (BV) has multiple applications in a variety of fields of clinical laboratory. The use of BV in statistical modeling is twofold. On the one hand, some models are used for the generation of BV estimates (within- and between-subject variability). Other models are built based on BV in combination with other factors to establish ranges of normality that will help the clinician interpret serial results for the same subject. There are two types of statistical models for the calculation of BV estimates: A. Direct methods, prospective studies designed to calculate BV estimates; i. Classic model: developed by Harris and Fraser, revised by the Working Group on Biological Variation of the European Federation of Laboratory Medicine. ii. Mixed-effect models. iii. Bayesian model. B. Indirect methods, retrospective studies to derive BV estimates from large databases of results. Big data. Understanding the characteristics of these models is crucial as they determine their applicability in different settings and populations. Models for defining ranges that help in the interpretation of individual serial results include: A. Reference change value and B. Bayesian data network. In summary, this review provides an overview of the models used to define BV components and others for the follow-up of patients. These models should be exploited in the future to personalize and improve the information provided by the clinical laboratory and get the best of the resources available.

Pigments of natural origin have become a research trend, and fungi provide a readily available alternative source. Moreover, developing novel processes that increase yields, reduce process time and simplify downstream processing is of increased interest. In this sense, this work proposes an alternative for Talaromyces atroroseus GH2 biomass re-utilization to produce pigments through consecutive batches using immobilized mycelium. Different support materials were evaluated for pigment production and immobilization capacity. Then, Taguchi’s method was applied to determine the effect of four factors related to fungal immobilization and pigment production (inoculum concentration, support density, working volume and support volume). Afterward, process kinetics for pigment production using immobilized cells of T. atroroseus GH2 in consecutive batches were evaluated. All evaluated factors were significant and affected pigment production and microorganism growth differently. At improved conditions, immobilization capacity reached 99.01 ± 0.37% and the pigment production was 30% higher than using free cells. Process kinetics showed that the production could continue for three batches and was limited by excessive microorganism growth. Indeed, more studies are still needed, but the immobilization of Talaromyces atroroseus GH2 represents a promising strategy for allowing downstream-processing intensification since immobilized biomass is easily removed from the fermentation media, thus paving the way for the further development of a continuous process.

Background: Following the COVID-19 pandemic, microvascular and macrovascular thrombotic problems emerged that required anticoagulants. Apixaban (RN) is a factor Xa inhibitor that treats deep vein thrombosis and the two forms of artery diseases (coronary artery disease and peripheral artery disease)., Materials and Methods: The study objective was to create fast-disintegrating Apixaban Oral Thin Films (OTF) with the help of various super disintegrants to shorten disintegration time and enhance drug release in order to assist patients who have difficulty in swallowing conventional dosage forms and increase bioavailability. OTF was created using the solvent casting method. A 22 factorial design was employed in Design-Expert® software to develop an ideal formula., Results: The optimized film formula pH, drug content, disintegration time, folding endurance, and dissolution rate were estimated, and the film was subjected to a short-term stability study. The optimized formula exhibited a cumulative drug release of 93.47% in 60 sec., Conclusion: The drug's in vitro release pattern shows first-order kinetics and fickian diffusion was the mechanism of drug release. These findings supported that Apixaban OTFs offer a quick release of the medication from the administration site into the systemic circulation.

Background and Objectives: Nanosponges are one of the most innovative ways to use the newest developments in nanodrugs delivery. Nanosponges can catch drugs that dissolve in water or ones that don't. This work uses statistical design to find the best nanosponges for drugs that don't dissolve easily and make them., Material and Methods: It was looked into how to statistically make the most of the effects of independent factors. The ethyl cellulose ratio and stirring rate were chosen based on how they affected the dependent variables, such as particle size and how well they were trapped. FTIR, SEM, zeta potential, entrapment efficiency, and particle size data were used to test the nanosponges that were made. Using carbopol, the best lot of nanosponges was added to the gel., Results: Using ethyl cellulose and polyvinyl alcohol as stabilizers in the emulsion liquid diffusion method, it was possible to make drug-loaded nanosponges. It was possible to make the nanosponges composition work better by using Central Composite Design. It has been seen that making drug-filled nanosponges improves stability., Conclusion: The study showcased the enhanced capacity of a formulation with decreased particle size and high entrapment efficiency to disseminate effectively.

Genomic selection (GS) is becoming an essential tool in breeding programs due to its role in increasing genetic gain per unit time. The design of the training set (TRS) in GS is one of the key steps in the implementation of GS in plant and animal breeding programs mainly because (i) TRS optimization is critical for the efficiency and effectiveness of GS, (ii) breeders test genotypes in multi-year and multi-location trials to select the best-performing ones. In this framework, TRS optimization can help to decrease the number of genotypes to be tested and, therefore, reduce phenotyping cost and time, and (iii) we can obtain better prediction accuracies from optimally selected TRS than an arbitrary TRS. Here, we concentrate the efforts on reviewing the lessons learned from TRS optimization studies and their impact on crop breeding and discuss important features for the success of TRS optimization under different scenarios. In this article, we review the lessons learned from training population optimization in plants and the major challenges associated with the optimization of GS including population size, the relationship between training and test set (TS), update of TRS, and the use of different packages and algorithms for TRS implementation in GS. Finally, we describe general guidelines to improving the rate of genetic improvement by maximizing the use of the TRS optimization in the GS framework. [ABSTRACT FROM AUTHOR]

Genomic selection (GS) is becoming an essential tool in breeding programs due to its role in increasing genetic gain per unit time. The design of the training set (TRS) in GS is one of the key steps in the implementation of GS in plant and animal breeding programs mainly because (i) TRS optimization is critical for the efficiency and effectiveness of GS, (ii) breeders test genotypes in multi-year and multi-location trials to select the best-performing ones. In this framework, TRS optimization can help to decrease the number of genotypes to be tested and, therefore, reduce phenotyping cost and time, and (iii) we can obtain better prediction accuracies from optimally selected TRS than an arbitrary TRS. Here, we concentrate the efforts on reviewing the lessons learned from TRS optimization studies and their impact on crop breeding and discuss important features for the success of TRS optimization under different scenarios. In this article, we review the lessons learned from training population optimization in plants and the major challenges associated with the optimization of GS including population size, the relationship between training and test set (TS), update of TRS, and the use of different packages and algorithms for TRS implementation in GS. Finally, we describe general guidelines to improving the rate of genetic improvement by maximizing the use of the TRS optimization in the GS framework.

The biosorption potential of cost-effective and agricultural residue, Ipomoea carnea wood (ICW) was examined by the removal of cationic dye, methylene blue (MB) from aqueous solution. The surface morphology, structural and thermal properties of untreated ICW were analyzed using Scanning Electron Microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and Thermo-gravimetric Analysis (TGA), respectively. The effects of different parameters namely concentration of biosorbent, initial pH, initial MB composition and temperature on biosorption capacity and biosorption (%) were studied. The kinetic and equilibrium models were developed to fit the experimental data on MB biosorption. The maximum biosorption capacity of 39.38 mg g−1 was obtained at 40 °C using Langmuir model. The removal of MB was found to be significantly varying with temperature. Box–Behnken design was applied to optimize the biosorption parameters. The optimized condition for MB biosorption was evaluated as dosage of 3.1 g L−1, pH of 7.04, Temperature of 49.1 °C, MB concentration of 30.48 mg L−1 and maximum biosorption (%) of 83.87. The regeneration of ICW was investigated by five cycles using a suitable eluting agent. Hence, ICW without any pretreatment and chemical modification is a potential candidate for the removal of MB in terms of availability and economy of the process. Ipomoea carnea wood (ICW) without any pretreatment explored a potential biosorbent for the removal of methylene blue (MB) in terms of availability and economy of the process. The physico-chemical properties of ICW characterized using Scanning Electron Microscopy, Fourier transform infrared spectroscopy and Thermo-gravimetric Analysis showed ICW as a promising biosorbent for MB removal. Presence of heterogeneous with rugged morphological structure, cavities, irregular shape and size of large pores provide the better biosorption capability for MB molecules using ICW without any pretreatment or chemical modification. Analysis of kinetic and isotherm models was performed to examine the better fitness of experimental data with model. Thermodynamic parameters indicating feasible and endothermic MB biosorption. Statistical design of experiments is used to optimize the condition and corresponding maximum MB removal using Derringer's desired function methodology. Untreated ICW is a potential reusable biosorbents, effectively employed in successive biosorption and desorption process for the removal of MB from aqueous solutions. [ABSTRACT FROM AUTHOR]

In this study, the effects of several parameters such as the acid concentration, mixing time, temperature, solid rate, and mixing rate on the specific surface area (BET) and cation exchange capacity (CEC) of sepiolite activated by citric acid were investigated using factorial experimental design and response surface methodology. While the specific surface area and cation exchange capacity of nitric acid activated sepiolite were chosen as the responses, the acid concentration, time, temperature, solid rate, and mixing rate were the process parameters. The relationship between the process parameters and the responses was obtained and used in the determination of the optimal conditions. The result showed that the specific surface area and cation exchange capacity of the acid-activated sepiolite were strongly affected by the process parameters. The optimal conditions for achieving the maximum specific surface area and minimum cation exchange capacity were 95.73 °C, 8.64%, 4.99 N, 1 h, and 450 rpm for temperature, solid rate, acid concentration, activation time, and the mixing rate, respectively. The experimental and predicted values for the SBET and the CEC were obtained as 450.97 m2/g and 449.97 m2/g, and 6.79 meq/100 g and 6.86 meq/100 g, respectively. The results obtained from this study clearly indicated that the actual values were in good conformity with the predicted values as evidenced by small errors of 1.00% and 0.07% for the SBET and CEC, respectively. As a result, the SBET and CEC of the Sep activated by citric acid were strongly affected by the process parameters, especially the solid rate for the SBET and the temperature for CEC. It was found that citric-acid activated Sep had a SBET approximately 2.5 times higher than that of the untreated Sep while the CEC of Sep may be strongly eliminated by citric acid treatment. Thus, the mineral structure was progressively transformed into amorphous silica coming from the tetrahedral sheet of the generated fibrous silicates, whose SBET was larger than that of the raw Sep. [ABSTRACT FROM AUTHOR]

Recently, social network monitoring has attracted much attention because it helps to governments for preventing social challenges. Most of the existing papers in the literature suffer from three remarkable drawbacks: (1) applying the pre-determined parameters for the control charts while design of these parameters by an optimization procedure results in a chart with more power to detect the network changes; (2) Using the fixed-parameter control charts that are less flexible than the adaptive control charts; (3) Considering the fixed shift size for the changes whereas in the real situation the shift size within social networks are variable and stochastic. To overcome the mentioned disadvantages, this study presents a statistical design of exponentially weighted moving average control chart with variable sampling interval for monitoring the total communications among individuals in a weighted and directed social network. Also, to more adapt with the real condition of the social networks, this paper considers a probability distribution for shift size in the network communications. The particle swarm optimization algorithm determines the chart parameters in a way that the average time to signal be optimized. Eventually, a comparative study is executed to indicate efficiency of the suggested approach in comparison with the existing studies. The results demonstrate that this control chart has better performance than fixed-parameter charts in detecting the network changes. [ABSTRACT FROM AUTHOR]

[Display omitted] External lubrication is an alternative to internal lubrication and its related detrimental effects on properties of tablets like tensile strength (TS). However, to date there are hardly any systematic investigations on external lubrication of mini-tablets on rotary tablet presses. Aim of this study was the systematic investigation of the impact of parameters tableting pressure, tableting speed, dosing rate and air pressure on the TS of mini-tablets. Both studies, the Central Composite Design (CCD) with SMCC 90 and the subsequently executed D-optimal design with SMCC 50, exhibited that tableting pressure had the highest positive effect on TS. Tableting speed and dosing rate in the CCD presumably did not seem to influence the TS, air pressure represented a positive coefficient. An additional temporal factor seemed to impact the results, deduced from the negative effect of the experimental order on TS in the CCD and from the negative correlation along the execution order in the residual plots. Additional long runs support findings of a non-linear decrease of TS over time. An interplay between dosing rate level and performance of the dust extraction collector is assumed, making more magnesium stearate available in the tablet press and potentially causing gradual contamination of the powder over time. [ABSTRACT FROM AUTHOR]

Arsenic present in water bodies causes devastating effects on aquatic organisms and indirectly poses a hazardous threat to human existence. There is an urgent need to develop potential and convincing technologies to troubleshoot this problem. In the present study, an adsorbent has been prepared using the waste red mud from hazardous aluminium industry and doping it with calcium-alginate beads (ARMCB) for the effective removal of As(III) from wastewater. The concentration of As(III) was reduced from 0.101 mg/L to 0.008 mg/L after adsorption which effectively met the economic and environmental conditions imposed by WHO (>0.01 mg/L). Further, the statistical Response Surface Methodology (RSM) is adopted to analyze the combined effects of four operational parameters namely: pH, sorbent dosage, contact time and initial concentration on the adsorption of As(III) from the synthetic contaminated water samples. A high correlation coefficient (R2) value of 0.9672 projected by ANOVA confirmed the satisfactory regression of the developed model. The maximum adsorption capacity is found to be 1.807 mg/g at optimum operating conditions. The surface characterization of the adsorbent before and after adsorption by SEM, EDX, XRD, and FTIR confirms the potentiality of the adsorbent towards As(III) ions. Thermodynamic, adsorption isotherms and kinetic analysis respectively projected the endothermic Langmuir model adsorption of As(III) and the pseudo-second-order rate kinetics of the sorption mechanism. The current study aids the implementation of the developed robust technique for the successful removal of As(III) from industrial and domestic polluted water samples. [ABSTRACT FROM AUTHOR]

The objective of this article is to review the difficulties with the design and interpretation of surgical clinical trials. Few surgical procedures are evaluated in a randomized fashion. There are a number of factors that make the design of surgical trials diffiuclt, and many surgical questions cannot be answered with a clinical trial. Issues with standardization of the surgical procedure, variability of surgical skills, and changes in surgical expertise over time further complicate the design and implementation of surgical trials. Statistical methods for surgical trials often require a noninferiorty design and are more complicated to interpret than the more common superiority trial. Even when properly conducted, both superiority and noninferiority trials are often misinterpreted. Because of the relatively high success rate in surgery, trials require large numbers of patients and noninferiority trials are often inconclusive with respect to the primary outcome. Surgical trials are often misinterpreted or over interpreted, and there can be confusion in how the findings of these trials should be incorportated into clinical practice. The interpretation of the results of a surgical trial often differ significantly from the primary and secondary outcomes that were specified in the trial design. [ABSTRACT FROM AUTHOR]

Different nutritional and physicochemical conditions to obtain H 2 from Citrus Peel Waste (CPW) were evaluated. For this, a screening design was carried out using Plackett and Burman design, in order to verify the main significant conditions of this process. The variables studied were pH (5.5–8.5), temperature (30–44 °C), autochthonous inoculum (0.75–2.25 gTVS.L−1), allochthonous inoculum (1–3 gTVS.L−1) and substrate (5–15 g.L−1), headspace (40–60%) and nutritional medium components, such as yeast extract (0–1 g.L−1), CaCO 3 , NaCl and peptone (0–5 g.L−1). The most significant operational variables were pH (8.5), allochthonous inoculum (3 gTVS.L−1) and substrate concentration (15 g CPW.L−1), conditions that favored the highest H 2 (13.29 mmol.L−1) and acetic acid productions (1340 mg.L−1). Escherichia (34.5%) and Clostridium (29.93%) were the main genera identified under these conditions. Image 1 • Initial pH above 7.0 leads to acetic acid accumulation. • Acetogenesis is the main pathway related with CPW fermentation. • Yeast extract supplementation does not affect H 2 production or rate from CPW. • Clostridium and Paraclostridium are the main genera involved in CPW fermentation. • Peptone supplementation can decrease the time for H 2 production to get started. [ABSTRACT FROM AUTHOR]

Lovastatin is a drug in the statin class which acts as a natural inhibitor of 3-hydroxy-3-methylglutaryl, a coenzyme reductase reported as being a potential therapeutic agent for several diseases: Alzheimer's, multiple sclerosis, osteoporosis and due to its anti-cancer properties. Aspergillus terreus is known for producing a cholesterol reducing drug. This study sets out to evaluate the production of lovastatin by Brazilian wild strains of A. terreus isolated from a biological sample and natural sources. Carbon and nitrogen sources and the best physicochemical conditions using factorial design were also evaluated. The 37 fungal were grown to produce lovastatin by submerged fermentation. A. terreus URM5579 strain was the best lovastatin producer with a level of 13.96 mg/L. Soluble starch and soybean flour were found to be the most suitable substrates for producing lovastatin (41.23 mg/L) and biomass (6.1 mg/mL). The most favorable production conditions were found in run 16 with 60 g/L soluble starch, 15 g/L soybean flour, pH 7.5, 200 rpm and maintaining the solution at 32 °C for 7 days, which led to producing 100.86 mg/L of lovastatin and 17.68 mg/mL of biomass. Using natural strains and economically viable substrates helps to optimize the production of lovastatin and promote its use. [ABSTRACT FROM AUTHOR]

Microbial proteases, especially from Bacillus spp., have been widely exploited for a broad variety of applications, such as the improvement of the cleaning efficiency of conventional detergents. In this work, the statistical design of the experiment was used to optimize the concentrations of a threecomponent mixture: Bacillus licheniformis SMIA-2 protease, Linear Alkylbenzene Sulphate and hydrogen peroxide, in an attempt to prepare an environmentally correct cleaning formulation. The results demonstrated that the combination of 1% (w/v) protease with 1.5% (w/v) LAS and 1% (w/v) H2O2 was effective in removing blood from cloth pieces and that a protease concentration decrease from 1.0% to 0.5% (w/v) would not have a significant impact on percent blood removal if LAS concentrations between 1.5-2.0% (w/v) in combination with lower (<0.5%, w/v) concentrations of H2O2 were used. Thus, the protease from Bacillus licheniformis SMIA-2 can be effectively incorporated into cleaning formulations together with LAS and hydrogen peroxide to formulate more sustainable detergents. [ABSTRACT FROM AUTHOR]

In many applications, the quality of a process is characterized by the functional relationship between a response variable and one or more explanatory variables. This functional relationship is referred to as a profile. We extend two existing methods for monitoring the shift of slope of linear profiles. We consider the single sampling (SS) and the double sampling (DS) scheme for the economic-statistical design (ESD) model of profile monitoring in Phase II. The results of a numerical example indicate the DS β ^ 1 control chart has better performance than the DS T 2 control chart when ρ β ^ 0 , β ^ 1 is low. Comparison of the ESD of DS β 1 ^ and the SD of DS β 1 ^ control charts show that an ESD has an improvement over the pure SD. Also, we compare the ESD of the DS β 1 ^ with the ESD of the SS β 1 ^ control chart. The results show that the DS β 1 ^ control charts are more efficient in terms of minimizing the E (L). [ABSTRACT FROM AUTHOR]