Diverse Pipeline Research Articles

Forging Futures, Building a Pipeline: Testimonios From a Collective of Diverse MFP Alums in the Southwest

ABSTRACT For 50 years, the Minority Fellowship Program (MFP) has supported social workers in serving diverse communities at risk of mental health issues and substance misuse, training over 1,000 masters and doctoral-level fellows, and preparing them for meaningful community engagement. Through testimonios, we explore the career paths, collaborations, and community involvement of five doctoral-level MFP alums working at a large public R1 university in the Southwest. Reflecting as MFP alums and diverse faculty of color, our testimonios bear witness to MFP’s influence on our antiracist, antioppressive, and decolonial work, our mentorship and recruitment of graduate students of color, and our efforts to build a diverse student pipeline to address mental health and substance misuse within marginalized racial and ethnic communities.

Diversity and impact of single-stranded RNA viruses in Czech Heterobasidion populations.

Heterobasidion annosum sensu lato comprises some of the most devastating pathogens of conifers. Exploring virocontrol as a potential strategy to mitigate economic losses caused by these fungi holds promise for the future. In this study, we conducted a comprehensive screening for viruses in 98 H. annosum s.l. specimens from different regions of Czechia aiming to identify viruses inducing hypovirulence. Initial examination for dsRNA presence was followed by RNA-seq analyses using pooled RNA libraries constructed from H. annosum and Heterobasidion parviporum, with diverse bioinformatic pipelines employed for virus discovery. Our study uncovered 25 distinct ssRNA viruses, including two ourmia-like viruses, one mitovirus, one fusarivirus, one tobamo-like virus, one cogu-like virus, one bisegmented narna-like virus and one segment of another narna-like virus, and 17 ambi-like viruses, for which hairpin and hammerhead ribozymes were detected. Coinfections of up to 10 viruses were observed in six Heterobasidion isolates, whereas another six harbored a single virus. Seventy-three percent of the isolates analyzed by RNA-seq were virus-free. These findings show that the virome of Heterobasidion populations in Czechia is highly diverse and differs from that in the boreal region. We further investigated the host effects of certain identified viruses through comparisons of the mycelial growth rate and proteomic analyses and found that certain tested viruses caused growth reductions of up to 22% and significant alterations in the host proteome profile. Their intraspecific transmission rates ranged from 0% to 33%. Further studies are needed to fully understand the biocontrol potential of these viruses in planta.IMPORTANCEHeterobasidion annosum sensu lato is a major pathogen causing significant damage to conifer forests, resulting in substantial economic losses. This study is significant as it explores the potential of using viruses (virocontrol) to combat these fungal pathogens. By identifying and characterizing a diverse array of viruses in H. annosum populations from Czechia, the research opens new avenues for biocontrol strategies. The discovery of 25 distinct ssRNA viruses, some of which reduce fungal growth and alter proteome profiles, suggests that these viruses could be harnessed to mitigate the impact of Heterobasidion. Understanding the interactions between these viruses and their fungal hosts is crucial for developing effective, environmentally friendly methods to protect conifer forests and maintain ecosystem health. This study lays the groundwork for future research on the application of mycoviruses in forest disease management.

Data-Driven Multi-Fault Detection in Pipelines Utilizing Frequency Response Function and Artificial Neural Networks

This research presents a data-driven structural health monitoring (SHM) approach for pipeline systems that leverages frequency response function (FRF) signals and artificial neural network (ANN) algorithms to accurately identify and classify diverse pipeline fault conditions. The study focuses on three specific faults: bolt looseness, scale deposits, and crack occurrence at pipeline supports, which were replicated on a pipeline segment located at the Sound and Vibration Research Group (SVRG) at University Putra Malaysia (UPM). The FRF signals were captured using accelerometers to monitor the structural health of the pipeline. The data acquisition stage involved collecting FRF signals from the accelerometers to capture vibrations and responses related to the identified faults using a Siemens LMS SCADAS data acquisition unit. The data underwent preprocessing, including the application of principal component analysis (PCA) for feature selection. The subsequent data processing stage involved the application of an artificial neural network (ANN) algorithm for pattern recognition to analyze and classify the acquired data, identifying patterns associated with the replicated fault conditions. The proposed methodology demonstrated exceptional performance, with the ANN model achieving consistently high overall accuracy (above 99.7%) and remarkably low mean squared error (in the range of 0.0088×10−3to0.3062×10−3) across multiple iterations and sensor datasets. The detailed class-specific metrics, including accuracy, precision, sensitivity, and F1-score, further substantiated the model's effectiveness in identifying the individual fault types with near-perfect or perfect results for the majority of the fault scenarios. The location-invariant performance of the ANN model across different sensor placements demonstrates the robustness of the proposed data-driven SHM methodology. This research highlights the transformative potential of integrating state-of-the-art data-driven techniques to revolutionize the monitoring and assessment of critical pipeline infrastructure, ultimately enhancing the safety, reliability, and longevity of these vital systems.

Analysis of the diversity pipeline for the orthopedic trauma surgeon workforce in the United States

IntroductionThere is a lack of research on the state of racial, ethnic, and gender diversity in the emerging orthopedic trauma workforce. The purpose of this study was to analyze the training pathway for diverse candidates in orthopedic trauma as it relates to race, ethnicity, and sex. MethodsSelf-reported demographic data were compared among allopathic medical students, orthopedic surgery residents, orthopedic trauma fellows, and the general population in the United States (2013–2022). Race categories consisted of White, Asian, Black, and Native American/Alaskan Native (NA/AN), and Native Hawaiian/Pacific Islander (NH/PI). Ethnicity categories were Hispanic/Latino or non-Hispanic/Latino. Sex categories were male and female. Representation was calculated at each stage of accredited training. Participation-to-prevalence ratios (PPRs) quantified the equitable representation of demographic groups in the emerging orthopedic trauma workforce relative to the US population. PPR thresholds were used to classify representation as overrepresented (PPR > 1.2), equitable (PPR = 0.8–1.2), and underrepresented (PPR < 0.8). ResultsRelative to medical school and orthopedic surgery residency, fewer female (48.5 % vs 16.7 % vs 18.7 %, P < 0.001), Hispanic (6.1 % vs 4.5 % vs 2.6 %, P < 0.001), Black (6.9 % vs 5.0 % vs 3.1 %, P < 0.001), and Asian (24.0 % vs 14.3 % vs 12.2 %, P < 0.001) trainees existed in orthopedic trauma fellowship training. In contrast, more male (51.5 % vs 83.3 % vs 81.3 %, P < 0.001) and White (62.8 % vs 79.1 % vs 84.0 %, P < 0.001) trainees existed in orthopedic trauma fellowship relative to earlier training stages. There were zero NA/AN or NH/PI trainees in orthopedic trauma (PPR = 0). Relative to the US population, Hispanic (PPR = 0.14), Black (PPR = 0.25), and female (PPR = 0.37) trainees were underrepresented in orthopedic trauma. In contrast, Asian (PPR = 2.04), male (PPR = 1.64), and White (PPR = 1.36) trainees were overrepresented in orthopedic trauma. ConclusionWomen, racial, and ethnic minorities are underrepresented in the emerging orthopedic trauma workforce relative to the US population, and earlier stages of training. Targeted recruitment and guided mentorship of these groups may lead to greater interest, engagement, and diversity in orthopedic trauma.

Reaching back to enhance the future: the American Association for the Surgery of Trauma Diversity, Equity and Inclusion Pipeline Program

ObjectivesThere are significant disparities in the surgical workforce in comparison with medical student demographics. Pipeline programs have shown to be effective in addressing gaps. The American Association for the Surgery...

Exploration and application of welding technology for misalignment of pressure pipe orifices in a pumped storage power station

Abstract Pumped storage power stations are currently the most economical and clean large-scale energy storage method. Pumped storage power stations have flexible start and stop, rapid response, and have six major functions, including peak shaving, valley filling, frequency regulation, phase modulation, emergency backup, and black start. With the transformation of the energy system towards clean, low-carbon, safe and efficient, the operational characteristics of the power system will undergo significant changes, requiring sufficient flexible regulation of power sources and energy storage facilities. It is more urgent to accelerate the development and construction of pumped storage energy. Due to the characteristics of pumped storage installation, high-strength pressure steel pipes are required on the upstream side of the power station units as the water diversion pipeline. This article takes a pumped storage power station as an example to analyze and handle the problem of pipe misalignment encountered during the welding process of pressure steel pipes in the power station. Satisfactory results have been achieved, ensuring the welding quality and providing reference for other engineering projects.

Enhanced crop health monitoring: attention convolutional stacked recurrent networks and binary Kepler search for early detection of paddy crop issues.

The diseases that affect the plants cannot be easily avoided due to rapid and substantial changes in the environment and climate. Generally, paddy crops are affected by several conditions including pests and nutritional deficiencies. Hence, it is important to detect these disease-affected paddy crops at an early stage for better productivity. To detect and classify the problems in this specific domain, deep learning approaches are utilized. In this paper, a novel attention convolutional stacked recurrent based binary Kepler search (ACSR-BKS) algorithm is used to detect diseases, nutritional deficiencies, and pest patterns at an early stage via diverse significant pipelines namely the data augmentation, data pre-processing, and classification phase thereby providing pest patterns and identifying nutritional deficiencies. Subsequent to data collection processes, the images are augmented via zooming, rotating, flipping horizontally, shifting of height, width, and rescaling. To acquire the accurate and best results in terms of classification, the parameters need to be tuned and adjusted using the binary Kepler search algorithm. The results revealed that the accuracy of the proposed ACSR-BKS algorithm is 98.2% in terms of detecting the diseases. Then, the obtained results are compared with the other existing approaches. Additionally, it is revealed that the yield of paddy can also be improved by utilizing the proposed disease-detecting methods.

Are Digital Humanities platforms facilitating sufficient diversity in research? A study of the Transkribus Scholarship Programme

Abstract To what extent do Digital Humanities (DH) platforms support access to diverse user cohorts? We take, as a case study, the Automated Text Recognition (ATR) platform Transkribus and its Transkribus Scholarship Programme (TSP), which provides free processing credits to eligible users. Using a mixed methods approach we address the following questions: What are the demographics of those using the TSP scheme? What work is enabled by such a scheme? How can this inform more equitable access to DH platforms? The findings demonstrate how ATR tools are currently used and made accessible. TSP applicants are overwhelmingly students (n = 111/156, 71.15 per cent) drawn from universities and research institutes, mostly in Europe, but are globally distributed; representing institutions that do not hold shares in Transkribus, and indicating a diverse user pipeline. Further work is required to increase potential benefits of the scholarship and to ensure sustainability. Increased dialogue between the Recognition and Enrichment of Archival Document-COOP and applicants would assist in the calculation of processing costs. We show financial—or in-kind—support is necessary to increase access to paid-for platforms, ensuring a diversity of DH research. We also provide recommendations for platform providers and funding bodies regarding access and the impact this can have, including locating a sustainable balance between absorbing the costs of maintaining DH or digital scholarship tools and providing sufficient support and training to further enable diverse research.

Nanopore Current Events Magnifier (nanoCEM): a novel tool for visualizing current events at modification sites of nanopore sequencing.

Nanopore sequencing technologies have enabled the direct detection of base modifications in DNA or RNA molecules. Despite these advancements, the tools for visualizing electrical current, essential for analyzing base modifications, are often lacking in clarity and compatibility with diverse nanopore pipelines. Here, we present Nanopore Current Events Magnifier (nanoCEM, https://github.com/lrslab/nanoCEM), a Python command-line tool designed to facilitate the identification of DNA/RNA modification sites through enhanced visualization and statistical analysis. Compatible with the four preprocessing methods including 'f5c resquiggle', 'f5c eventalign', 'Tombo' and 'move table', nanoCEM is applicable to RNA and DNA analysis across multiple flow cell types. By utilizing rescaling techniques and calculating various statistical features, nanoCEM provides more accurate and comparable visualization of current events, allowing researchers to effectively observe differences between samples and showcase the modified sites.

Robust pressure prediction of oil and gas pipeline networks based on equipment embedding neural network

Currently, extensive pipeline networks are developed in response to the demands of the oil and gas industry. The accurate estimation of the hydraulic condition of pipeline networks holds significant importance in the fields of pipeline design and safety management. Nevertheless, predicting the pressure of oil and gas pipeline networks with different equipment and structures remains challenging. To meet this challenge, a novel pressure prediction model for the oil and gas pipeline networks based on the equipment embedding neural network (EENN) is proposed in this study. The proposed model embeds different equipment models into the neural network model. The neural network in this model is used to focus on learning the connection characteristics of the pipeline network to achieve higher prediction accuracy. The present study first explores different embedding combinations of the EENN model to estimate the pressure in an oil pipeline network system that involves a non-isothermal batch transportation process. Then, the trained model is applied to predict the pressure in a gas pipeline network. The optimal EENN exhibits an average prediction error of 18.5% for oil pipelines and 0.36% for gas pipelines, which is lower than 20.8% and 3.57% under the neural network. The findings of this study demonstrate the efficacy of the proposed EENN in accurately forecasting pressures in diverse oil and gas pipeline networks by reducing the complexity of the learning process.

Landscape of toxin-neutralizing therapeutics for snakebite envenoming (2015-2022): Setting the stage for an R&D agenda.

Progress in snakebite envenoming (SBE) therapeutics has suffered from a critical lack of data on the research and development (R&D) landscape. A database characterising this information would be a powerful tool for coordinating and accelerating SBE R&D. To address this need, we aimed to identify and categorise all active investigational candidates in development for SBE and all available or marketed products. In this landscape study, publicly available data and literature were reviewed to canvas the state of the SBE therapeutics market and research pipeline by identifying, characterising, and validating all investigational drug and biologic candidates with direct action on snake venom toxins, and all products available or marketed from 2015 to 2022. We identified 127 marketed products and 196 candidates in the pipeline, describing a very homogenous market of similar but geographically bespoke products and a diverse but immature pipeline, as most investigational candidates are at an early stage of development, with only eight candidates in clinical development. Further investment and research is needed to address the shortfalls in products already on the market and to accelerate R&D for new therapeutics. This should be accompanied by efforts to converge on shared priorities and reshape the current SBE R&D ecosystem to ensure translation of innovation and access.

Ambient Vibration Analysis of Diversion Pipeline in Mount Changlong Pumped-Storage Power Station

This study analyzes the ambient vibrations induced while running the Mount Changlong pumped-storage power station (PSPS). The ground vibration data of the power station during its operation were acquired with vibration sensors. Different units were selected and compared under working conditions, and the conclusions were as follows: (1) Ambient vibrations induced by the running of units constituted the primary source of vibration, and they attenuated as the distance increased. (2) The vibration acceleration under pumping conditions was larger than that under power generation conditions, and the ground vibration acceleration increased with an augmentation of the power. (3) The running of adjacent units generated mutual interference, and the types of units were different, which led to complex variations in the spectrum maps. (4) The vibration acceleration of the lower flat tunnel was prone to surpassing the standard when the number of units running together exceeded three.

PipeVal: light-weight extensible tool for file validation.

The volume of biomedical data generated each year is growing exponentially as high-throughput molecular, imaging and mHealth technologies expand. This rise in data volume has contributed to an increasing reliance on and demand for computational methods, and consequently to increased attention to software quality and data integrity. To simplify data verification in diverse data-processing pipelines, we created PipeVal, a light-weight, easy-to-use, extensible tool for file validation. It is open-source, easy to integrate with complex workflows, and modularized for extensibility for new file formats. PipeVal can be rapidly inserted into existing methods and pipelines to automatically validate and verify inputs and outputs. This can reduce wasted compute time attributed to file corruption or invalid file paths, and significantly improve the quality of data-intensive software. PipeVal is an open-source Python package under the GPLv2 license and it is freely available at https://github.com/uclahs-cds/package-PipeVal. The docker image is available at: https://github.com/uclahs-cds/package-PipeVal/pkgs/container/pipeval.

Establishment and inactivation of mono-species biofilm in a semipilot-scale water distribution system using nanocomposite of silver nanoparticles/montmorillonite loaded cationic chitosan

This study presents a novel approach in the synthesis and characterization of nanocomposites comprising cationic chitosan (CCS) blended with varying concentrations of silver nanoparticles/montmorillonite (AgNPs/MMT). AgNPs/MMT was synthesized using soluble starch as a reducing and stabilizing agent. Subsequently, nanocomposites, namely CCS/AgMMT-0, CCS/AgMMT-0.5, CCS/AgMMT-1.5, and CCS/AgMMT-2.5, were developed by blending 2.5 g of CCS with 0, 0.5, 1.5, and 2.5 g of AgNPs/MMT, respectively, and the corresponding nanocomposites were prepared using ball milling technique. Transmission electron microscopy (TEM) analysis revealed the formation of nanocomposites that exhibiting nearly spherical morphologies. Dynamic light scattering (DLS) measurements displayed average particle sizes of 1183 nm, 131 nm, 140 nm, and 188 nm for CCS/AgMMT-0, CCS/AgMMT-0.5, CCS/AgMMT-1.5, and CCS/AgMMT-2.5, respectively. The narrow polydispersity index (~0.5) indicated uniform particle size distributions across the nanocomposites, affirming monodispersity. Moreover, the zeta potential values exceeding 30 mV across all nanocomposites that confirmed their stability against agglomeration. Notably, CCS/AgMMT-2.5 nanocomposite exhibited potent antibacterial and antibiofilm properties against diverse pipeline materials. Findings showed that after 15 days of incubation, the highest populations of biofilm cells, Pseudomonas aeruginosa biofilm, developed over UPVC, MDPE, DCI, and SS, with corresponding HPCs of 4.79, 6.38, 8.81, and 7.24 CFU/cm2. The highest cell densities of Enterococcus faecalis biofilm in the identical situation were 4.19, 5.89, 8.12, and 6.9 CFU/cm2. The nanocomposite CCS/AgMMT-2.5 exhibited the largest measured zone of inhibition (ZOI) against both P. aeruginosa and E. faecalis, with measured ZOI values of 19 ± 0.65 and 17 ± 0.21 mm, respectively. Remarkably, the research indicates that the youngest biofilm exhibited the most notable rate of inactivation when exposed to a dose of 150 mg/L, in comparison to the mature biofilm. These such informative findings could offer valuable insights into the development of effective antibiofilm agents and materials applicable in diverse sectors such as water treatment facilities, medical devices, and industrial pipelines.

Obstetric Racism, Education, and Racial Concordance.

The United States holds the distinction of being the developed country with the worst perinatal outcomes despite spending the most per capita on health care. Black women are three to four times more likely than White women to experience adverse birth outcomes. These outcomes persist despite access to prenatal care, insurance, and college education. A long overdue racial reckoning has arrived, beginning with acknowledging the fallacy of race-based medicine and the role of enduring systemic racism as foundational to obstetric racism in the reproductive lives of Black women. Centering voices of Black women and honoring their lived experiences are essential to providing respectful maternity care. Naming micro- and macroaggressions experienced by Black women allows for dismantling of systemic barriers which perpetuate inequitable outcomes and enable substandard care. Racial concordance (shared racial identity) is one tool to consider in creating safe health care spaces for Black women. Improving diversity of the nursing workforce specifically, and the health care workforce in general, is necessary to affect racial concordance. Application of skills in cultural humility can mitigate challenges associated with adverse patient encounters for Black women as diversity pipeline strategies are explored. Histories of foundational fallacy, their impact on care and outcomes, and patient-driven indicators for improving pregnancy care experiences for women of color are explored through the lens of a Black physician and the collective reproductive health workforce.

Talent mobility for accelerating diversity at leadership levels: A pilot study

Mayo Clinic is committed to reskilling and upskilling its workforce and to creating a strong, diverse leadership pipeline to advance its ‘Bold. Forward.’ strategy. In alignment with this commitment, the Mayo Clinic Shared Services Organization (MCSSO) launched a pilot offering staff the opportunity to work in a hybrid role and build new skills and connections. Pilot participants split their time equally between job roles in which the professional skill sets required were approximately the same. The pilot involved six MCSSO departments and six candidates (three pairs) from the participating departments. Staff were recruited for three roles: senior project manager, senior business analyst and call centre representative. Each of the three pairs worked in a hybrid assignment for six months. Candidates were offered opportunities to network with each other, MCSSO senior leaders and other diverse colleagues. Pilot evaluations were conducted at 0, 3 and 6 months with candidates and their supervisors. Additionally, benchmarking with external organisations allowed learning from advanced talent mobility and leadership diversity programmes. The evaluations highlighted that 50 per cent of the candidates were promoted by the end of their hybrid assignment. Most of them engaged in new projects, cross-trained and gained valuable insights, skills and expertise. Candidates and supervisors valued the opportunity to network with senior leaders and cross-functional colleagues. The pilot and external benchmarks emphasised the importance of a formal ‘talent mobility programme’ to build and sustain a diverse leadership pipeline. It is crucial to be intentional and bold with hybrid and mobility opportunities for intersectional candidates, under-represented groups and staff committed to equity, inclusion and diversity. All candidates and supervisors wanted the pilot to be expanded and operationalised. We believe that these early experiences, results and lessons on preparing diverse talent for leadership levels in the organisation are broadly transferable to other healthcare and non-healthcare organisations.

Leveraging PDS teacher preparation grants: a majority–minority research university’s approach to increasing the diverse teacher pipeline

PurposeA primary goal of the Collaboration and Resources for Encouraging and Supporting Transformations in Education (CREST-Ed) program was to increase the number of highly qualified, minoritized teachers committed to teaching in minority-serving, high-need school districts. This study's purpose was to evaluate the CREST-Ed program's impact on teacher residency outcomes using multiple sources of program evaluation data collected during the five-year grant.Design/methodology/approachThis study of a federal Teacher Quality Partnership (TQP) grant at Georgia State University (GSU), a minority-serving institution (MSI) and research university, shows teacher residency programs can improve the diverse teacher pipeline. The grant, CREST-Ed, provided professional development schools (PDS) support for four urban and 23 rural school districts through partnerships with GSU, Albany State University (ASU) and Columbus State University (CSU).FindingsThe study findings suggest that teacher preparation grants can be leveraged to recruit traditionally minoritized teachers of color to increase the diverse teacher pipeline and strengthen PDS partnerships.Originality/valueBoth urban and rural PDSs could benefit from teacher residency programs like the CREST-Ed model that catered to the unique needs of each school and partnership district.

Machine learning-based peptide-spectrum match rescoring opens up the immunopeptidome.

Immunopeptidomics is a key technology in the discovery of targets for immunotherapy and vaccine development. However, identifying immunopeptides remains challenging due to their non-tryptic nature, which results in distinct spectral characteristics. Moreover, the absence of strict digestion rules leads to extensive search spaces, further amplified by the incorporation of somatic mutations, pathogen genomes, unannotated open reading frames, and post-translational modifications. This inflation in search space leads to an increase in random high-scoring matches, resulting in fewer identifications at a given false discovery rate. Peptide-spectrum match rescoring has emerged as a machine learning-based solution to address challenges in mass spectrometry-based immunopeptidomics data analysis. It involves post-processing unfiltered spectrum annotations to better distinguish between correct and incorrect peptide-spectrum matches. Recently, features based on predicted peptidoform properties, including fragment ion intensities, retention time, and collisional cross section, have been used to improve the accuracy and sensitivity of immunopeptide identification. In this review, we describe the diverse bioinformatics pipelines that are currently available for peptide-spectrum match rescoring and discuss how they can be used for the analysis of immunopeptidomics data. Finally, we provide insights into current and future machine learning solutions to boost immunopeptide identification.

Simulation of Hydrate Particles Aggregation and Deposition in Gas-Dominated Flow

Summary Owing to low-temperature and high-pressure production environments, hydrate generation, accumulation, and deposition are prone to occur in deepwater oil and gas production wells and transportation pipelines, leading to pipeline blockage and threatening the safety of oil and gas production. To explore the aggregation mechanism and deposition law of hydrate particles in the main gas diversion pipeline, this study considered the adhesion effect of hydrate particles and established a hydrate particle aggregation and deposition model based on theory and experiments. The coupled computational fluid dynamics-discrete element method (CFD-DEM) is used in the simulation calculation. The simulation results were compared with the relevant experimental results, and maximum and average errors of 9.48% and 4.56% were observed, respectively. It was found that the main factor affecting the aggregation of hydrates is the adhesion between particles. As the subcooling temperature increased, the aggregation and adhesion of the hydrate particles increased to varying degrees. The tangential adhesion force between the hydrate aggregate particles was significantly greater than the normal adhesion force, and the adhesion force between the particles gradually increased from the surface to the interior of the aggregates. The coordination number of the hydrate particles can quantitatively characterize the degree of aggregation and is affected by many factors, such as adhesion. By studying the particle coordination number, the evolution of hydrate accumulation and deposition under different conditions can be summarized. Based on the simulation results, the mathematical relationship between different dimensionless numbers and hydrate deposition ratio (HDR) was calculated, and an expression that can predict the HDR was obtained, with an average relative error of 10.155%. This study provides a theoretical basis for predicting the aggregation and deposition of hydrate particles in gas-dominated systems and a reference for the development of hydrate prevention and control plans.

Understanding pathways to health-system pharmacy administration: A journey mapping study.

Pharmacy administrators play a critical role in the success of health systems, yet pathways to pharmacy administration are incompletely understood. The purpose of this study was to explore and describe pathways to becoming a health-system pharmacy administrator, including challenges experienced and resources needed. Participants (N = 21) individually completed one or more journey maps detailing the pathway(s) to pharmacy administration and then engaged in small group discussion to identify common themes. A large group debrief was used to share and identify findings across small groups. Thematic analysis was utilized to identify common ideas shared. There was variation across the maps, illustrating many steps one might follow to become a pharmacy administrator. In the 23 maps completed, pathways most frequently began with pharmacy school (n = 9, 39.1%), high school (n = 6, 26.1%), or undergraduate training (n = 4, 17.4%). Most included residency training or dual master's of science in health-system pharmacy administration/residency training (n = 16, 69.6%). Common challenges included distractions, time constraints, grades/performance, financial constraints, and stress. Common resources needed included exposure to diverse career paths, pipeline and outreach support, mentoring, and leadership. Themes included debate about the definition of a pharmacy administrator, questions regarding the core competencies of the pharmacy administrator, discussion regarding ways to enter pharmacy administration, and reflection on the role of serendipity and networking. Understanding the pathways to pharmacy administration is critical to fostering a sustainable and competent workforce. Work must be done to identify strategies and develop processes for identifying, equipping, and retaining talented health-system pharmacy administrators and leaders.