Adding experimental treatment arms to multi-arm multi-stage platform trials in progress.

Multi-arm multi-stage (MAMS) platform trials efficiently compare several treatments with a common control arm. Crucially MAMS designs allow for adjustment for multiplicity if required. If for example, the active treatment arms in a clinical trial relate to different dose levels or different routes of administration of a drug, the strict control of the family-wise error rate (FWER) is paramount. Suppose a further treatment becomes available, it is desirable to add this to the trial already in progress; to access both the practical and statistical benefits of the MAMS design. In any setting where control of the error rate is required, we must add corresponding hypotheses without compromising the validity of the testing procedure.To strongly control the FWER, MAMS designs use pre-planned decision rules that determine the recruitment of the next stage of the trial based on the available data. The addition of a treatment arm presents an unplanned change to the design that we must account for in the testing procedure. We demonstrate the use of the conditional error approach to add hypotheses to any testing procedure that strongly controls the FWER. We use this framework to add treatments to a MAMS trial in progress. Simulations illustrate the possible characteristics of such procedures.

Advancing Metallic Lithium Anodes: A Review of Interface Design, Electrolyte Innovation, and Performance Enhancement Strategies.

Lithium (Li) metal is one of the most promising anode materials for next-generation, high-energy, Li-based batteries due to its exceptionally high specific capacity and low reduction potential. Nonetheless, intrinsic challenges such as detrimental interfacial reactions, significant volume expansion, and dendritic growth present considerable obstacles to its practical application. This review comprehensively summarizes various recent strategies for the modification and protection of metallic lithium anodes, offering insight into the latest advancements in electrode enhancement, electrolyte innovation, and interfacial design, as well as theoretical simulations related to the above. One notable trend is the optimization of electrolytes to suppress dendrite formation and enhance the stability of the electrode-electrolyte interface. This has been achieved through the development of new electrolytes with higher ionic conductivity and better compatibility with Li metal. Furthermore, significant progress has been made in the design and synthesis of novel Li metal composite anodes. These composite anodes, incorporating various additives such as polymers, ceramic particles, and carbon nanotubes, exhibit improved cycling stability and safety compared to pure Li metal. Research has used simulation computing, machine learning, and other methods to achieve electrochemical mechanics modeling and multi-field simulation in order to analyze and predict non-uniform lithium deposition processes and control factors. In-depth investigations into the electrochemical reactions, interfacial chemistry, and physical properties of these electrodes have provided valuable insights into their design and optimization. It systematically encapsulates the state-of-the-art developments in anode protection and delineates prospective trajectories for the technology's industrial evolution. This review aims to provide a detailed overview of the latest strategies for enhancing metallic lithium anodes in lithium-ion batteries, addressing the primary challenges and suggesting future directions for industrial advancement.

Adaptive designs in clinical trials: why use them, and how to run and report them.

Adaptive designs can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial's course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials. The pace of the uptake of adaptive designs in clinical research, however, has remained well behind that of the statistical literature introducing new methods and highlighting their potential advantages. We speculate that one factor contributing to this is that the full range of adaptations available to trial designs, as well as their goals, advantages and limitations, remains unfamiliar to many parts of the clinical community. Additionally, the term adaptive design has been misleadingly used as an all-encompassing label to refer to certain methods that could be deemed controversial or that have been inadequately implemented.We believe that even if the planning and analysis of a trial is undertaken by an expert statistician, it is essential that the investigators understand the implications of using an adaptive design, for example, what the practical challenges are, what can (and cannot) be inferred from the results of such a trial, and how to report and communicate the results. This tutorial paper provides guidance on key aspects of adaptive designs that are relevant to clinical triallists. We explain the basic rationale behind adaptive designs, clarify ambiguous terminology and summarise the utility and pitfalls of adaptive designs. We discuss practical aspects around funding, ethical approval, treatment supply and communication with stakeholders and trial participants. Our focus, however, is on the interpretation and reporting of results from adaptive design trials, which we consider vital for anyone involved in medical research. We emphasise the general principles of transparency and reproducibility and suggest how best to put them into practice.

Numerical investigation on the wear characteristics of hip implant under static loading.

Modern hip arthroplasty still faces the issue of wear in the articulating surface and wear induced debris. Thus, the design of hip implant is highly important for its longevity. Experimental demonstration of wear in hip implant involves both time and cost and, in this regard, finite element analysis acts as a suitable alternative. In this work, the wear characteristics of design modified and surface modified femoral head is studied. Femoral head is assumed to be made of Ti6Al4V and liner material is taken as UHMWPE. Design of the femoral head is modified by providing grooves on the femoral head as well as by providing an additional liner on the femoral head surface. Surface of the femoral head is modified with square or circular dimples. This work involves the development of femoral head model and its simulation using ANSYS under static load condition to get the contact pressure and sliding distance. Modified Archard's wear equation uses the contact stress and sliding distance to determine the wear volume produced per year and the obtained results are compared with that in the available literature. The study shows that the wear rate reduced up to 10% by surface modification and 3% by design modifications.

Comprehensive review on ideas, designs and current techniques in solar dryer for food applications.

Due to the expansion of residents, the consumption of non-renewable energy increased enormously, thus indirectly increasing pollution and affecting the surroundings. To reduce pollutions in the surroundings, it is recommended to choose non-conventional energy sources. By satisfying this, we can probably decrease the non-renewable sources of energy, by consuming the solar power in day-to-day life in the application of food drying process. In this review article, we have discussed the classification of solar dryer and the impact of design modifications performed in the components of solar dryer and assessed the various types of solar dryer performance, cost estimations and designs performed in solar dryer of food applications which were not discussed in the earlier research. The primary and critical task in designing the solar dryer is to achieve higher efficiency at minimum cost. Hence, proper analysis of drying application, selection of suitable components and suitable design must be carried out to attain efficient dryer. Considering these characteristics, this paper primarily focuses on the effective design parameters incorporated with various efficiency enhancement processes of the solar dryer in the applications of food drying techniques. Thus, this review paper delivers the various classifications, design parameters, performance enhancement methods, properties and valuable assets of solar dryer, which helps to develop the sustainable green eco-friendly environment most primarily, in the application of food drying process. This review article concreted the way for upcoming considerations and provided the techniques for the studies to convey the work for promoting method enhancements.

Knowledge-Based Design Algorithm for Support Reduction in Material Extrusion Additive Manufacturing.

Although additive manufacturing (AM) enables designers to develop products with a high degree of design freedom, the manufacturing constraints of AM restrict design freedom. One of the key manufacturing constraints is the use of support structures for overhang features, which are indispensable in AM processes, but increase material consumption, manufacturing costs, and build time. Therefore, controlling support structure generation is a significant issue in fabricating functional products directly using AM. The goal of this paper is to propose a knowledge-based design algorithm for reducing support structures whilst considering printability and as-printed quality. The proposed method consists of three steps: (1) AM ontology development, for characterizing a target AM process, (2) Surrogate model construction, for quantifying the impact of the AM parameters on as-printed quality, (3) Design and process modification, for reducing support structures and optimizing the AM parameters. The significance of the proposed method is to not only optimize process parameters, but to also control local geometric features for a better surface roughness and build time reduction. To validate the proposed algorithm, case studies with curve-based (1D), surface-based (2D), and volume (3D) models were carried out to prove the reduction of support generation and build time while maintaining surface quality.