In-Depth Molecular Dynamics Study of All Possible Chondroitin Sulfate Disaccharides Reveals Key Insight into Structural Heterogeneity and Dynamism

GAGs exhibit a high level of conformational and configurational diversity, which remains untapped in terms of the recognition and modulation of proteins. Although GAGs are suggested to bind to more than 800 biologically important proteins, very few therapeutics have been designed or discovered so far. A key challenge is the inability to identify, understand and predict distinct topologies accessed by GAGs, which may help design novel protein-binding GAG sequences. Recent studies on chondroitin sulfate (CS), a key member of the GAG family, pinpointing its role in multiple biological functions led us to study the conformational dynamism of CS building blocks using molecular dynamics (MD). In the present study, we used the all-atom GLYCAM06 force field for the first time to explore the conformational space of all possible CS building blocks. Each of the 16 disaccharides was solvated in a TIP3P water box with an appropriate number of counter ions followed by equilibration and a production run. We analyzed the MD trajectories for torsional space, inter- and intra-molecular H-bonding, bridging water, conformational spread and energy landscapes. An in-house phi and psi probability density analysis showed that 1→3-linked sequences were more flexible than 1→4-linked sequences. More specifically, phi and psi regions for 1→4-linked sequences were held within a narrower range because of intra-molecular H-bonding between the GalNAc O5 atom and GlcA O3 atom, irrespective of sulfation pattern. In contrast, no such intra-molecular interaction arose for 1→3-linked sequences. Further, the stability of 1→4-linked sequences also arose from inter-molecular interactions involving bridged water molecules. The energy landscape for both classes of CS disaccharides demonstrated increased ruggedness as the level of sulfation increased. The results show that CS building blocks present distinct conformational dynamism that offers the high possibility of unique electrostatic surfaces for protein recognition. The fundamental results presented here will support the development of algorithms that help to design longer CS chains for protein recognition.

Quadrant Mapping Artificial Lift Concept

This paper outlines a concept for monitoring performance of artificial lift performance such as electrical submersible pump (ESP), hydraulic pumping unit (HPU), sucker rod pump (SRP) and progressive cavity pump (PCP), for a large number of wells. The objective is to generate simplified monitoring performance of artificial lift with a huge number of wells on one page by creating quadrant mapping consisting of two coordinates with x axis representing pump efficiency and y axis showing pump submergence. We made a four-quadrant limit by pump efficiency (50%) and submergence (200 m). Optimum wells will show on range pump efficiency above 50% and submergence below 200 m, and 3 other quadrants are classified as artificial lift problems, well potential and sizing/design problems. By using the quadrant mapping concept, we can generate performance of artificial lift for 1500++ wells in one page, and this mapping consists of four quadrants (quadrant 1, quadrant 2, quadrant 3 and quadrant 4), quadrant 1 (Submergence above 200 meter and lifting efficiency below 50%) showing wells which have artificial lift problem, quadrant 2 (Submergence is above 200 meters and efficiency is above 50%) showing well which have potential to increased production, quadrant 3 (Submergence is below 200 meters and efficiency is above 50%) showing the optimum wells operation and quadrant 4 (Submergence is below 200 meters and efficiency is below 50%) showing the wells which required to re-sizing/re-design artificial lift. This quadrant mapping can be shown to Engineers, manager's and shareholder to show overall performance and classification detailed problems to create a troubleshooting, optimization program to increased oil production, run life artificial and result in better production performance. This mapping also helps petroleum engineers to get a better field view and create priorities and program optimization based on the quadrant mapping result and classification.

Input Quantity Decision and Coordination Mechanism with Two Production Chances and Yield Uncertainty

Conducting a second production run can improve the company’s capability of meeting the market demand. Few works examine optimal input quantity decisions under the mode with two production chances considering demand and yield uncertainty. We propose a vendor-managed inventory (VMI) supply chain with one supplier and one retailer. The supplier has two production chances and faces yield uncertainty in each production run. It is necessary for the supplier to make trade-offs between the cost and benefit of the second production run, then decide whether to conduct the second production run. We investigate the supplier’s optimal input quantity decision in each production run and obtain the supply chain members’ expected profits. As a comparison, the mode with one production chance is also developed. We find that two production chances can help improve the performance of the supply chain under yield uncertainty. A revenue-sharing contract is introduced to coordinate the supply chain with two production chances, and efficient profit allocation is achieved through adjusting the revenue-sharing ratio and the wholesale price. An extension is conducted for a sensitivity analysis of unit punishment cost on the supplier’s input quantity decisions.

The Human Performance Impact on OEE in the Adoption of New Production Technologies

The initial adoption phase of new production technologies is the period between the first production run or technology reconfiguration and the achievement of a stable target output. This time frame is generally characterized by productivity unsteadiness, quality performance variability, and unexpected machine failures together with increasing production volumes due to the process setup and instability, which inevitably affects production output. In this context, human performance represents an additional source of variability and process instability that is dependent on the workers’ productivity, learning curve and related training activities. Hence, to effectively assess the ramp-up phase of new production technologies, an appropriate evaluation of human performance is required. This paper proposes a comprehensive framework and criteria to perform a consistent assessment of the initial adoption phase of new production technologies by introducing two OEE measurement methodologies that distinguish between human performance, process configuration and technical features of the production technology. The proposed framework is then applied to and validated by a case study concerning the introduction of a semi-automatic packaging machine in a primary multinational company in the logistics industry. This case study shows the difference between the two OEE measures, along with the values interpretation and useful insights for achieving a stable production output.

An Imperfect Production–Inventory Model with Mixed Materials Containing Scrap Returns Based on a Circular Economy

The implementation of scrap recovery activities has been shown to improve the financial performance of many firms, and this kind of circular economy (CE) is particularly evident in industries with green manufacturing (GM). In this paper, we consider an imperfect multiple-stage production system that manufactures paired products made from mixed materials containing scrap returns, in which the scrap returns are converted from defective products. The feed rates of scrap returns for two products are different, and the product with the higher feed rate is placed in the second order of the process to avoid unlimited accumulation of scrap returns. The proposed problem is formulated as a joint economic order quantity (EOQ) and economic production quantity (EPQ) model aimed at cost minimization. The decision variables of the proposed model include the production run time of two products, order quantity of new material, and the extent of investment in converted equipment. We also prove that the optimal solution exists uniquely and provide an algorithm for the computation of the optimal solution. Finally, a numerical example involving the pulp and paper manufacturing industry is provided to illustrate the solution process, and the results of its sensitivity analysis are also presented to show some managerial implications.

A Pollution Sensitive Fuzzy EPQ Model With Endogenous Reliability and Product Deterioration Under Lock Fuzzy Game Theoretic Approach

This article deals with a cost minimization objective function of an economic production quantity (EPQ) inventory model with production breakdown and deterioration. The process reliability and the environmental pollution due to over production have also been considered. The model has been split into two different scenarios according to the breaking time before and after the production period. In scenario 1, no machinery failure occurs during production run time and that of scenario 2 the failure occurs during production run time. We develop a deterministic cost minimization problem first then we fuzzify the model by considering the production rate, the demand rate and all the cost components as lock fuzzy numbers. We convert the fuzzy model into equivalent game problem by considering Gaussian normal strategic probabilities. The model has been solved with the help of different key vectors employed by the decision maker. We have shown that the value of the game might be changed with the change of different key vectors. A comparative study has been made with the numerical results of the general fuzzy and crisp models. Finally, graphical illustrations and sensitivity analysis have been done followed by a conclusion.

Studying Equilibria of Polymers in Solution by Direct Molecular Dynamics Simulations: Poly(N-isopropylacrylamide) in Water as a Test Case

It is well known that studying equilibria of polymers in solution by atomistic simulations is computationally demanding as a large phase space has to be adequately sampled. Nevertheless, direct molecular dynamics (MD) simulations are often used for this purpose in the literature. To assess whether such approach is adequate, we have conducted a case study for a polymer+solvent system that has been commonly studied with direct MD simulations by many authors: poly(N-isopropylacrylamide) (PNIPAM) in water. The total simulation time of the present study is much longer than that typically used in MD simulations of that system. A NIPAM chain of 30 monomers was studied in explicit water at 295K. Three initial configurations were used. For each configuration, five replicas were run for 1000ns. The statistical analysis of our data shows that the equilibration time is of the order of 600-700ns and that the remaining time for the production run is not sufficient to sample the equilibrium state adequately. These results underpin the well-known difficulty of sampling equilibrium states of polymers in solution with direct MD simulations and the need for a careful interpretation of results of such studies. The problem with the unsatisfactory sampling persists despite the increasing available computing power. Therefore, enhanced sampling techniques and workarounds, such as simplified scenarios or coarse-graining, remain important.

Higher Productivity In Forming High-alloyed Steel By Temperature Insensitive Friction Behavior

Like in many other production technologies, a broad process window for metal forming is desired. The goal is always a stable process chain. One of the key aspects for metal forming are stable tribological conditions. Instabilities can be caused by, amongst others, different material batches, change in temperature during the production process, different lubricant amounts and different stroke rates. At the beginning of a production run, the tribological stability suffers from transient temperature effects caused by plastic and frictional work and a viscosity drop of the lubricant. To control the tribology, different strategies are suitable: changing the oil type, the oil amount, the blank holder force or the stroke rate. Within the EU-project ASPECT, control strategies on blank holder forces are developed as well as lubricants with improved stability on their behaviour as a function of temperature. This paper will focus on the latter. In preliminary ball on plate test the friction and wear of lubricant formulations were investigated and compared to a Reference lubricant. Followed by strip drawing and forming tests. Finally, the concept is proven in trials on a demonstrator line, which is close to serial production.

Adjustment of credit period and stock-dependent demands in a supply chain model with variable imperfectness

In this model, a supply chain model has been developed where a manufacturer continuously transports perfect quality items at no cost to a distribution center to maintain the market demand. At the beginning of the process, the production process is in an "in-control" state, but after a random time, it goes to an "out-of-control" state. Thus the production process produces perfect as well as imperfect items in this state. The rate of imperfect production depends on production rate and production-run length in the "out-of-control" state. The unit production cost of the manufacturer depends on the production rate which indicates that the higher production rate is the cause of higher production cost if it exceeds the normal production rate set by the manufacturer. The manufacturer provides a credit period to the distributor to increase his sales growth. In the competitive business world, credit period affects the demand rate of a retailer/buyer due to its late payment facility. So, here, credit period dependent demand function is introduced for the distributor. During the festive season, demand factor of products is usually affected by stock level. Also, for some types of products (such as clothing), the demand factor depends on its stock level. Thus we have considered stock-dependent demand function for the customers. Now, in an infinite time horizon, the problem is how they adjust their demands to sustain the whole system's financial flow. The novelty of this model is to analyze the compatibility of this two-type of demand in their businesses so that both can maintain their profits. Also, there is another credit length which is offered by the distributor. The proposed model has been discussed in type-2 fuzzy environment due to the uncertainty of the credit period. The purpose of this model is to optimize the integrated profit of the system by optimizing production rate and production-run time. Finally, numerical examples have been provided to illustrate the feasibility of both crisp and fuzzy model and some conclusions are derived conducting a sensitivity analysis of different parameters.

Development, manufacturing, and preliminary validation of a reusable half-face respirator during the COVID-19 pandemic

Introduction The COVID-19 pandemic has led to widespread shortages of N95 respirators and other personal protective equipment (PPE). An effective, reusable, locally-manufactured respirator can mitigate this problem. We describe the development, manufacture, and preliminary testing of an open-hardware-licensed device, the “simple silicone mask” (SSM). Methods A multidisciplinary team developed a reusable silicone half facepiece respirator over 9 prototype iterations. The manufacturing process consisted of 3D printing and silicone casting. Prototypes were assessed for comfort and breathability. Filtration was assessed by user seal checks and quantitative fit-testing according to CSA Z94.4–18. Results The respirator originally included a cartridge for holding filter material; this was modified to connect to standard heat-moisture exchange (HME) filters (N95 or greater) after the cartridge showed poor filtration performance due to flow acceleration around the filter edges, which was exacerbated by high filter resistance. All 8 HME-based iterations provided an adequate seal by user seal checks and achieved a pass rate of 87.5% (N = 8) on quantitative testing, with all failures occurring in the first iteration. The overall median fit-factor was 1662 (100 = pass). Estimated unit cost for a production run of 1000 using distributed manufacturing techniques is CAD $15 in materials and 20 minutes of labor. Conclusion Small-scale manufacturing of an effective, reusable N95 respirator during a pandemic is feasible and cost-effective. Required quantities of reusables are more predictable and less vulnerable to supply chain disruption than disposables. With further evaluation, such devices may be an alternative to disposable respirators during public health emergencies. The respirator described above is an investigational device and requires further evaluation and regulatory requirements before clinical deployment. The authors and affiliates do not endorse the use of this device at present.