Towards the design of user-centric strategy recommendation systems for collaborative Human-AI tasks.

Artificial Intelligence is being employed by humans to collaboratively solve complicated tasks for search and rescue, manufacturing, etc. Efficient teamwork can be achieved by understanding user preferences and recommending different strategies for solving the particular task to humans. Prior work has focused on personalization of recommendation systems for relatively well-understood tasks in the context of e-commerce or social networks. In this paper, we seek to understand the important factors to consider while designing user-centric strategy recommendation systems for decision-making. We conducted a human-subjects experiment (n=60) for measuring the preferences of users with different personality types towards different strategy recommendation systems. We conducted our experiment across four types of strategy recommendation modalities that have been established in prior work: (1) Single strategy recommendation, (2) Multiple similar recommendations, (3) Multiple diverse recommendations, (4) All possible strategies recommendations. While these strategy recommendation schemes have been explored independently in prior work, our study is novel in that we employ all of them simultaneously and in the context of strategy recommendations, to provide us an in-depth overview of the perception of different strategy recommendation systems. We found that certain personality traits, such as conscientiousness, notably impact the preference towards a particular type of system (𝑝 < 0.01). Finally, we report an interesting relationship between usability, alignment, and perceived intelligence wherein greater perceived alignment of recommendations with one's own preferences leads to higher perceived intelligence (𝑝 < 0.01) and higher usability (𝑝 < 0.01).

Targeting imidazole-glycerol phosphate dehydratase in plants: novel approach for structural and functional studies, and inhibitor blueprinting.

The histidine biosynthetic pathway (HBP) is targeted for herbicide design with preliminary success only regarding imidazole-glycerol phosphate dehydratase (IGPD, EC 4.2.1.19), or HISN5, as referred to in plants. HISN5 catalyzes the sixth step of the HBP, in which imidazole-glycerol phosphate (IGP) is dehydrated to imidazole-acetol phosphate. In this work, we present high-resolution cryoEM and crystal structures of Medicago truncatula HISN5 (MtHISN5) in complexes with an inactive IGP diastereoisomer and with various other ligands. MtHISN5 can serve as a new model for plant HISN5 structural studies, as it enables resolving protein-ligand interactions at high (2.2 Å) resolution using cryoEM. We identified ligand-binding hotspots and characterized the features of plant HISN5 enzymes in the context of the HISN5-targeted inhibitor design. Virtual screening performed against millions of small molecules not only revealed candidate molecules but also identified linkers for fragments that were experimentally confirmed to bind. Based on experimental and computational approaches, this study provides guidelines for designing symmetric HISN5 inhibitors that can reach two neighboring active sites. Finally, we conducted analyses of sequence similarity networks revealing that plant HISN5 enzymes derive from cyanobacteria. We also adopted a new approach to measure MtHISN5 enzymatic activity using isothermal titration calorimetry and enzymatically synthesized IGP.

Effect of Prebiotics Supplements on Salivary pH and Salivary Buffer Capacity in Children with Early Childhood Caries: An In Vivo Study.

Streptococcus mutans (S. mutans) is the major pathogen involved in caries development during the first few years of life. Prebiotics represent a breakthrough approach to maintaining oral health by utilizing naturally beneficial bacteria against harmful bacteria. Aim: To assess the effects of prebiotics supplements on salivary pH and salivary buffer capacity in children with early childhood caries (ECC). Materials and methods: This study was performed on 23 samples, aged 3-6 years who received prebiotics supplements for 14 days, followed up to 3 and 6 months. Unstimulated saliva samples were collected to assess salivary pH and salivary buffer capacity using salivary check buffer kit. Statistical analysis used: The data showed normal distribution; hence, parametric tests were applied. Repeated measures of analysis of variance were applied to compare the mean at the three different time intervals, followed by paired t-test for pairwise comparison. Results: There was a highly significant difference on comparing the different parameters. Salivary pH was lowest at baseline with a mean value of 6.65 which increased at the 3-6-month follow-up to 7.00 and 7.33. Similarly, salivary buffer capacity which was 4.73 at baseline, increased at 3 months to 8.17, and at 6 months to 10.34. Conclusion: It can be suggested that prebiotics supplements can be adopted as a novel approach in children with ECC as a form of preventive measure to facilitate a better lifestyle. Clinical significance: These prebiotics when taken for a period of 2 weeks increased the salivary pH as well as salivary buffer capacity when the data was compared at different time intervals emphasizing its importance, especially in children with ECC. How to cite this article: Fernandes VA, Mata DB, Nadig B, et al. Effect of Prebiotics Supplements on Salivary pH and Salivary Buffer Capacity in Children with Early Childhood Caries: An In Vivo Study. Int J Clin Pediatr Dent 2024;17(1):54-58.

The effect of core competencies of university students on employment and first year salary level based on school activity log.

Deciding on a career and securing employment at an ideal company represent significant challenges for students. Employment is not only a personal achievement but also a measure of success for universities and governments. To transform students into competitive applicants, various activities are provided by universities, governments, and companies. These activities may leave students either excited about the prospects or overwhelmed by the experience. The aim of this study is to explore the relationship between college experiences and post-graduation employment through an analysis of a five-year activity log. Specifically, students' diverse activities were categorized into six core competencies: skill reinforcement, leadership and teamwork, globalization, organizational commitment, job exploration, and autonomous implementation. We used logistic regression to examine how these competencies relate to employment status, and ANOVA analysis to assess their impact on initial salaries. The findings reveal that while competencies in skill improvement, job exploration, and organizational commitment were not statistically significant, those in leadership and teamwork, globalization, and autonomous implementation were crucial for securing employment. Additionally, globalization, job exploration, and autonomous implementation competencies influenced annual salary levels. Furthermore, a comparison of students completing either a single major or a convergent major revealed that job exploration competency significantly impacts the annual salary level.

Fixed-point algorithms for solving the critical value and upper tail quantile of Kuiper's statistics.

Kuiper's statistic is a good measure for the difference of ideal distribution and empirical distribution in the goodness-of-fit test. However, it is a challenging problem to solve the critical value and upper tail quantile, or simply Kuiper pair, of Kuiper's statistics due to the difficulties of solving the nonlinear equation and reasonable approximation of infinite series. In this work, the contributions lie in three perspectives: firstly, the second order approximation for the infinite series of the cumulative distribution of the critical value is used to achieve higher precision; secondly, the principles and fixed-point algorithms for solving the Kuiper pair are presented with details; finally, finally, a mistake about the critical value cnα for (α,n)=(0.01,30) in Kuiper's distribution table has been labeled and corrected where n is the sample capacity and α is the upper tail quantile. The algorithms are verified and validated by comparing with the table provided by Kuiper. The methods and algorithms proposed are enlightening and worth of introducing to the college students, computer programmers, engineers, experimental psychologists and so on.

Markov decision process design: A framework for integrating strategic and operational decisions.

We consider the problem of optimally designing a system for repeated use under uncertainty. We develop a modeling framework that integrates the design and operational phases, which are represented by a mixed-integer program and discounted-cost infinite-horizon Markov decision processes, respectively. We seek to simultaneously minimize the design costs and the subsequent expected operational costs. This problem setting arises naturally in several application areas, as we illustrate through examples. We derive a bilevel mixed-integer linear programming formulation for the problem and perform a computational study to demonstrate that realistic instances can be solved numerically.

Identifying app components that promote physical activity: a group concept mapping study.

Background: Digital interventions are a promising avenue to promote physical activity in healthy adults. Current practices recommend to include end-users early on in the development process. This study focuses on the wishes and needs of users regarding an a mobile health (mHealth) application that promotes physical activity in healthy adults, and on the differences between participants who do or do not meet the World Health Organization's recommendation of an equivalent of 150 minutes of moderate intensity physical activity. Methods: We used a mixed-method design called Group Concept Mapping. In a first phase, we collected statements completing the prompt "In an app that helps me move more, I would like to see/ do/ learn the following…" during four brainstorming sessions with physically inactive individuals (n = 19). The resulting 90 statements were then sorted and rated by a new group of participants (n = 46). Sorting data was aggregated, and (dis)similarity matrices were created using multidimensional scaling. Hierarchical clustering was applied using Ward's method. Analyses were carried out for the entire group, a subgroup of active participants and a subgroup of inactive participants. Explorative analyses further investigated ratings of the clusters as a function of activity level, gender, age and education. Results: Six clusters of statements were identified, namely 'Ease-of-use and Self-monitoring', 'Technical Aspects and Advertisement', 'Personalised Information and Support', 'Motivational Aspects', 'Goal setting, goal review and rewards', and 'Social Features'. The cluster 'Ease-of-use and Self-monitoring' was rated highest in the overall group and the active subgroup, whereas the cluster 'Technical Aspects and Advertisement' was scored as most relevant in the inactive subgroup. For all groups, the cluster 'Social Features' was scored the lowest. Explorative analysis revealed minor between-group differences. Discussion: The present study identified priorities of users for an mHealth application that promotes physical activity. First, the application should be user-friendly and accessible. Second, the application should provide personalized support and information. Third, users should be able to monitor their behaviour and compare their current activity to their past performance. Fourth, users should be provided autonomy within the app, such as over which and how many notifications they would like to receive, and whether or not they want to engage with social features. These priorities can serve as guiding principles for developing mHealth applications to promote physical activity in the general population.

Pushing the Limits of Heat Conduction in Covalent Organic Frameworks Through High-Throughput Screening of Their Thermal Conductivity.

Tailor-made materials featuring large tunability in their thermal transport properties are highly sought-after for diverse applications. However, achieving `user-defined' thermal transport in a single class of material system with tunability across a wide range of thermal conductivity values requires a thorough understanding of the structure-property relationships, which has proven to be challenging. Herein, large-scale computational screening of covalent organic frameworks (COFs) for thermal conductivity is performed, providing a comprehensive understanding of their structure-property relationships by leveraging systematic atomistic simulations of 10,750 COFs with 651 distinct organic linkers. Through the data-driven approach, it is shown that by strategic modulation of their chemical and structural features, the thermal conductivity can be tuned from ultralow (≈0.02 W m-1 K-1) to exceptionally high (≈50 W m-1 K-1) values. It is revealed that achieving high thermal conductivity in COFs requires their assembly through carbon-carbon linkages with densities greater than 500 kg m-3, nominal void fractions (in the range of ≈0.6-0.9) and highly aligned polymeric chains along the heat flow direction. Following these criteria, it is shown that these flexible polymeric materials can possess exceptionally high thermal conductivities, on par with several fully dense inorganic materials. As such, the work reveals that COFs mark a new regime of materials design that combines high thermal conductivities with low densities.

In Vitro Simulation of the Fasted Gastric Conditions and Their Variability to Elucidate Contrasting Properties of the Marketed Dabigatran Etexilate Pellet-Filled Capsules and Loose Pellets.

Variability of the gastrointestinal tract is rarely reflected in in vitro test protocols but often turns out to be crucial for the oral dosage form performance. In this study, we present a generation method of dissolution profiles accounting for the variability of fasted gastric conditions. The workflow featured 20 biopredictive tests within the physiological variability. The experimental array was constructed with the use of the design of experiments, based on three parameters: gastric pH and timings of the intragastric stress event and gastric emptying. Then, the resulting dissolution profiles served as a training data set for the dissolution process modeling with the machine learning algorithms. This allowed us to generate individual dissolution profiles under a customizable gastric pH and motility patterns. For the first time ever, we used the method to successfully elucidate dissolution properties of two dosage forms: pellet-filled capsules and bare pellets of the marketed dabigatran etexilate product Pradaxa. We showed that the dissolution of capsules was triggered by mechanical stresses and thus was characterized by higher variability and a longer dissolution onset than observed for pellets. Hence, we proved the applicability of the method for the in vitro and in silico characterization of immediate-release dosage forms and, potentially, for the improvement of in vitro-in vivo extrapolation.

Validating claims-based definitions for deprescribing: Bridging the gap between clinical and administrative data.

BACKGROUND: Limited research has evaluated the validity of claims-based definitions for deprescribing. OBJECTIVES: Evaluate the validity of claims-based definitions of deprescribing against electronic health records (EHRs) for deprescribing of benzodiazepines (BZDs) after a fall-related hospitalization. METHODS: We used a novel data linkage between Medicare fee-for-service (FFS) and Part D with our health system's EHR. We identified patients aged ≥66 years with a fall-related hospitalization, continuous enrollment in Medicare FFS and Part D for 6 months pre- and post-hospitalization, and ≥2 BZD fills in the 6 months pre-hospitalization. Using a standardized EHR abstraction tool, we adjudicated deprescribing for a sub-sample with a fall-related hospitalization at UNC. We evaluated the validity of claims-based deprescribing definitions (e.g., gaps in supply, dosage reductions) versus chart review using sensitivity and specificity. RESULTS: Among 257 patients in the overall sample, 44% were aged 66-74 years, 35% had Medicare low-income subsidy, 79% were female. Among claims-based definitions using gaps in supply, the prevalence of BZD deprescribing ranged from 8.2% (no refills) to 36.6% (30-day gap). When incorporating dosage, the prevalence ranged from 55.3% to 65.8%. Among the validation sub-sample (n = 47), approximately one-third had BZDs deprescribed in the EHR. Compared to EHR, gaps in supply from claims had good sensitivity, but poor specificity. Incorporating dosage increased sensitivity, but worsened specificity. CONCLUSIONS: The sensitivity of claims-based definitions for deprescribing of BZDs was low; however, the specificity of a 90-day gap was >90%. Replication in other EHRs and for other low-value medications is needed to guide future deprescribing research.

Integration of electronic project management software in an investigational drug service pharmacy within an academic medical center.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: An investigational drug services (IDS) pharmacy plays a vital role in supporting clinical trial research by ensuring the safe and efficient management of investigational products. This article describes the implementation of an electronic project management software to improve an IDS pharmacy's study protocol work. The article describes the implementation of the software and how this approach addressed specific challenges, including project oversight, process standardization, documentation, reporting, accountability, and intrateam communication. SUMMARY: We describe an electronic project management software system used to streamline and standardize the work associated with study protocols. This software provides an organized and customizable workspace to manage tasks associated with each study protocol. The software automates task creation, tracks progress, and ensures comprehensive record keeping. Additionally, the software fosters effective communication within the team and offers real-time reporting to assess team productivity and progress. We have observed improved consistency, enhanced revenue, including approximately $18,000 in additional fee capture, and increased collaboration among pharmacy team members. CONCLUSION: Implementing an electronic project management software has proven highly beneficial in the IDS pharmacy. The software has significantly improved workflow efficiency by addressing challenges in study protocol management. While initial setup and training required time and resources, the long-term benefits in project oversight, collaboration, and revenue capture justify the investment. An electronic project management software is a valuable tool in managing the complexity of study protocol activities and supports the pharmacy's crucial role in advancing clinical research.

The effects of different landscape strategies on outdoor thermal comfort in village squares: a case study in Dayuwan village in Wuhan City.

Appropriate landscape configurations significantly mitigate rural thermal degradation. However, limited research exists on seasonal thermal comfort and the interconnections among landscape elements. Using ENVI-met software and field measurements, this study analyzed the microclimate of Dayuwan Village Square in Wuhan City. Fifteen design scenarios, including tree planting, building greening, albedo adjustment, and expanded tree coverage, were quantitatively evaluated to assess their impact on outdoor thermal comfort. Additionally, synergistic interactions between mitigation strategies were explored. The study found that increasing evergreen tree coverage by 50% has minimal impact on comfort during winter and spring. However, it significantly reduces temperatures in summer and autumn, resulting in average predicted mean vote (PMV) decreases of 0.315 and 0.643, respectively. Additionally, this strategy optimizes PMV values at 18:00 on extreme days, with a 0.102 decrease in summer and a 0.002 increase in winter. This research offers practical and sustainable guidance to designers for enhancing mitigation effects through optimal landscape configuration, providing a technical framework for rural environmental improvements.

Creating a Bot-tleneck for malicious AI: Psychological methods for bot detection.

The standard approach for detecting and preventing bots from doing harm online involves CAPTCHAs. However, recent AI research, including our own in this manuscript, suggests that bots can complete many common CAPTCHAs with ease. The most effective methodology for identifying potential bots involves completing image-processing, causal-reasoning based, free-response questions that are hand coded by human analysts. However, this approach is labor intensive, slow, and inefficient. Moreover, with the advent of Generative AI such as GPT and Bard, it may soon be obsolete. Here, we develop and test various automated, bot-screening questions, grounded in psychological research, to serve as a proactive screen against bots. Utilizing hand coded free-response questions in the naturalistic domain of MTurkers recruited for a Qualtrics survey, we identify 18.9% of our sample to be potential bots, whereas Google's reCAPTCHA V3 identified only 1.7% to be potential bots. We then look at the performance of these potential bots on our novel bot-screeners, each of which has different strengths and weaknesses but all of which outperform CAPTCHAs.

Assessing patient transport conditions during ambulance transit.

Emergency ambulances play a vital role in medical rescue and patient transportation, but their transit can impact patient health due to vehicle dynamic forces and vibrations. This study evaluates patient transport conditions on a stretcher subjected to vertical vibration excitation from road unevenness. Using an eight-degree-of-freedom numerical model, we analyze the construction parameters of a medical stretcher's support and vehicle suspension. Actual experimental data from an emergency vehicle were utilized to assess the vibration conditions experienced by both the stretcher and the ambulance floor. The model is adjusted based on measurements, specifically targeting the main vibration modes. The investigation involves determining temporal responses for vertical accelerations and characterizing vibration modal parameters under various transportation conditions. Notably, several system natural frequencies fall within the range of human body frequencies, making them susceptible to mechanical excitation, particularly in the human neck, abdomen, and spine. A sensitivity analysis underscores the influence of medical stretcher support structure parameters on patient comfort. Increasing support stiffness, which alters the stretcher's natural frequency, and damping coefficient reduce vibration propagation between the vehicle and the patient. Additionally, the research predicts the model's dynamic behavior on roads with low-quality pavement, indicating vibrational amplitudes that could potentially be discomforting and unhealthy for individuals. The study illustrates a vibration exposure period on a class E road, revealing that transportation longer than 25 min may cause damage to patient health.

Social participation, loneliness, and physical inactivity over time: evidence from SHARE.

OBJECTIVES: We aimed to explore the reciprocal effects of social participation, loneliness, and physical inactivity over a period of 6 years in a representative sample of European adults over 50 years old. DESIGN: A longitudinal study with a six-year follow-up period was conducted. SETTING: Four waves of the Survey of Health, Ageing and Retirement in Europe project were used. PARTICIPANTS: This study includes 64,887 participants from Europe and Israel, who were aged 50 or older at the first time. MEASUREMENTS: The relationship between participation in social activities, loneliness and physical inactivity was analyzed, controlling for age, gender, and disability. A series of cross-lagged panel models (CLPMs) were applied to analyze the relationships among these variables. RESULTS: A CLPM with equal autoregressive cross-lagged effects across waves was the best fit to the data (χ2 = 7137.8, CFI = .972, RMSEA = .049, SRMR = .036). The autoregressive effects for the three variables showed high stability across waves, and all the cross-lagged effects in the model were statistically significant. Social activity and physical inactivity maintained a strong negative cross-lagged effect, while their cross-lagged effects on loneliness were comparatively smaller. Social activity had a positive cross-lagged effect on loneliness, while physical inactivity had a negative cross-lagged effect on loneliness. CONCLUSIONS: These findings highlight the importance of promoting physical activity and social participation and addressing loneliness through targeted interventions in older adults.

Optimizing Nurse Workflow Efficiency: An Examination of Nurse Walking Behavior and Space Accessibility in Medical Surgical Units.

OBJECTIVE: This study aimed to investigate the effect of spatial adjacencies on nurses' walking patterns and the subsequent impact on staff satisfaction with perceived accessibility and adjacency-related issues. BACKGROUND: Recognizing the crucial importance of spatial adjacencies in healthcare facilities is essential, as they significantly affect staff morale, fatigue management, operational efficiency, error reduction, and overall patient care excellence, highlighting the need for objective assessments to evaluate the impact of facility layout and space configuration on workflow patterns and staff satisfaction in patient care units. METHODS: Integrating on-site observations with survey data, we explored how spatial adjacencies affect staff walking behavior and satisfaction in two med-surgical unit floors. RESULTS: The findings highlighted a significant frequency of movements between nurse stations, patient rooms, and medication areas. Regression analysis identified several contributing factors to staff satisfaction, including the proximity of supplies, team visibility, ease of access across departments, and the location of equipment rooms. Specifically, satisfaction with the proximity of supplies was positively associated with increased provider satisfaction with workflow, quality of care, and workplace. Additionally, valuable feedback from staff revealed concerns regarding break room placement, medication area functionality, and disparities in the availability of supplies. CONCLUSION: This study highlighted the critical need for carefully planned spatial adjacency strategies to enhance workflow efficiency and raise clinical staff satisfaction within healthcare facilities. The actionable insights gleaned from this research offer valuable direction to architects, healthcare administrators, and design professionals, enabling the creation of environments that positively resonate with healthcare providers and improve healthcare operations.

Oral Health Education for Children: Development of a Serious Game with a User-Centered Design Approach.

Background: Children can learn efficiently with well-designed serious games. The use of applications to promote health has proliferated, but there is a lack of scientific studies on educational games in oral health. Materials and Methods: We developed the Brazilian version of a British and Jordanian oral health education game for children from the perspectives of Brazilian specialists and users. This descriptive study, with a qualitative and quantitative approach, comprised three phases: I-Experts' discussion of the appropriateness of the previous version of the game to Brazil; II-Development of the first Brazilian version of the game; and III-Evaluation of the first version with 15 children from 4 to 8 years of age. Results: In Phase I, the specialists agreed with the development of the Brazilian version of the game, with minor adjustments on: advice on eating; advice on oral hygiene habits, users' age group, game characters, and game purpose. Phase II: a version with a few changes in images and recommendations, written and spoken in Brazilian Portuguese. Phase III: The global average of correct answers in the game's tasks was 75.3%, ranging from 50.0% to 100%. Children reported having fun with the game, and most understood the content and its interface; their parents found the information relevant and enjoyed the gameplay with their children. Conclusions: The Oral Health Education Game offered basic information for preventing dental caries to Brazilian children aged 4-8 years old in an interactive and fun way; it could support professionals in improving oral health education.

Game design elements of serious games in the education of medical and healthcare professions: a mixed-methods systematic review of underlying theories and teaching effectiveness.

Serious games, as a learning resource, enhance their game character by embedding game design elements that are typically used in entertainment games. Serious games in its entirety have already proven their teaching effectiveness in different educational contexts including medical education. The embedded game design elements play an essential role for a game's effectiveness and thus they should be selected based on evidence-based theories. For game design elements embedded in serious games used for the education of medical and healthcare professions, an overview of theories for the selection lacks. Additionally, it is still unclear whether and how single game design elements affect the learning effectiveness. Therefore, the main aim of this systematic review is threefold. Firstly, light will be shed on the single game design elements used in serious games in this area. Second, the game design elements' underlying theories will be worked out, and third, the game design elements' effectiveness on student learning outcome will be assessed. Two literature searches were conducted in November 2021 and May 2022 in six literature databases with keywords covering the fields of educational game design, serious game, and medical education. Out of 1006 initial records, 91 were included after applying predefined exclusion criteria. Data analysis revealed that the three most common game design elements were points, storyline, and feedback. Only four underlying theories were mentioned, and no study evaluated specific game design elements. Since game design elements should be based on theories to ensure meaningful evaluations, the conceptual GATE framework is introduced, which facilitates the selection of evidence-based game design elements for serious games.

Enhanced removal of rare earth elements from aqueous media: exploring the potential of AM-3 and AM-4 titanosilicates.

This study investigates the impact of three key variables on the performance of nanoporous AM-3 and layered AM-4 titanosilicates in removing nine REEs (Y, La, Ce, Pr, Nd, Eu, Gd, Tb, and Dy) from natural mineral water and identifies optimal operational conditions using Response Surface Methodology (RSM). The experimental conditions were determined by a Box-Behnken Design of 3 factors-3 levels (pH 4, 6, and 8; sorbent dose 20, 100, and 180 mg/L; and element concentration 1, 3, and 5 µmol/L). Three-dimensional response surfaces were used to assess the linear, quadratic, and interaction influences of each factor on the REEs' removal percentage. The pH was the most significant factor in the removal process using AM-3, while the sorbent dose was more important for AM-4. The results highlighted the sorbents' strong capacity for REE removal. The optimal operating conditions obtained by RSM were applied to aqueous solutions with salinity 10 (common in coastal and transitional systems) and 30 (average seawater salinity). The results showed that AM-3 has a strong potential for removing REEs in solutions with salinity 10 and 30, while AM-4 was less efficient due to competition between REEs and other ions present in the solution.

A two-stage group-sequential design for delayed treatment responses with the possibility of trial restart.

Common statistical theory applicable to confirmatory phase III trial designs usually assumes that patients are enrolled simultaneously and there is no time gap between enrollment and outcome observation. However, in practice, patients are enrolled successively and there is a lag between the enrollment of a patient and the measurement of the primary outcome. For single-stage designs, the difference between theory and practice only impacts on the trial duration but not on the statistical analysis and its interpretation. For designs with interim analyses, however, the number of patients already enrolled into the trial and the number of patients with available outcome measurements differ, which can cause issues regarding the statistical analyses of the data. The main issue is that current methodologies either imply that at the time of the interim analysis there are so-called pipeline patients whose data are not used to make a statistical decision (like stopping early for efficacy) or the enrollment into the trial needs to be at least paused for interim analysis to avoid pipeline patients. There are methods for delayed responses available that introduced error-spending stopping boundaries for the enrollment of patients followed by critical values to reject the null hypothesis in case the stopping boundaries have been crossed beforehand. Here, we will discuss other solutions, considering different boundary determination algorithms using conditional power and introducing a design allowing for recruitment restart while keeping the type I error rate controlled.