Variable Trajectories Research Articles

Seeking sufficient and appropriate care during the first year after spinal cord injury: a qualitative study

Study designLongitudinal qualitative study, based on a constructivist grounded theory and transformative approach.ObjectivesThis study investigated experiences of individuals with spinal cord injury (SCI) while navigating rehabilitation, resources for recovery, and community reintegration during the first year after injury.SettingAn acute inpatient rehabilitation facility in the Midwest United States.MethodsIn-depth, semi-structured interviews were conducted with 20 individuals with newly-acquired SCI. Interviews were conducted approximately every other month for one year, beginning at acute inpatient rehabilitation. Data were analyzed and interpreted using a constructivist grounded theory approach and transformative paradigm, which examines power and social structures within and across institutions and gives voice to people at risk for marginalization.ResultsParticipants experienced variable post-injury trajectories, with an average of four transitions within and across healthcare institutions in the first three months. Half of the cohort was discharged to a skilled nursing facility (SNF). Emergent themes included discharge (un)readiness; length of stay uncertainty and insurance impacts; challenges choosing a SNF including time-sensitive decisions; and early cessation of therapy in the SNF. Participants experienced resource navigation challenges such as communication/information access barriers and contending with many concerns at once.ConclusionsThe experiences of this cohort reveal significant challenges to attaining sufficient and appropriate rehabilitation. Acute inpatient rehabilitation is a critical aspect of recovery, but does not ensure sufficient intervention for maximization of functional skills and community reintegration. Innovative rehabilitation models need to be developed for positive impacts on successful transition to independent living in the community.

3D anatomy of the supraorbital and greater occipital nerve trajectories.

This research aims to enhance understanding of the anatomy of the supraorbital nerve (SON) and greater occipital nerve (GON), focusing on their exit points, distal trajectories, and variability, utilizing a novel 3D representation. Ten cadaveric specimens underwent meticulous dissection, and 3D landmarks were registered. Models were generated from CT scans, and a custom 3D method was employed to visualize nerve trajectories. Measurements, including lengths and distances, were obtained for the SON and GON. The SON exhibited varied exit points, with the lateral branches being the longest. The GON showed distinct branching patterns, which are described relative to various anatomical reference points and planes. No systematic left-right differences were observed for either nerve. 3D analysis revealed significant interindividual variability in nerve trajectories. The closest approximation between the SON and GON occurred between lateral branches. The study introduces a novel 3D methodology for analyzing the SON and GON, highlighting considerable anatomical variation. Understanding this variability is crucial for clinical applications and tools targeting the skull innervation. The findings serve as a valuable reference for future research, emphasizing the necessity for personalized approaches in innervation-related interventions.

An extended phase graph-based framework for DANTE-SPACE simulations including physiological, temporal, and spatial variations.

The delay alternating with nutation for tailored excitation (DANTE)-sampling perfection with application-optimized contrasts (SPACE) sequence facilitates 3D intracranial vessel wall imaging with simultaneous suppression of blood and CSF. However, the achieved image contrast depends closely on the selected sequence parameters, and the clinical use of the sequence is limited in vivo by observed signal variations in the vessel wall, CSF, and blood. This paper introduces a comprehensive DANTE-SPACE simulation framework, with the aim of providing a better understanding of the underlying contrast mechanisms and facilitating improved parameter selection and contrast optimization. An extended phase graph formalism was developed for efficient spin ensemble simulation of the DANTE-SPACE sequence. Physiological processes such as pulsatile flow velocity variation, varying flow directions, intravoxel velocity variation, diffusion, and effects were included in the framework to represent the mechanisms behind the achieved signal levels accurately. Intravoxel velocity variation improved temporal stability and robustness against small velocity changes. Time-varying pulsatile velocity variation affected CSF simulations, introducing periods of near-zero velocity and partial rephasing. Inclusion of diffusion effects was found to substantially reduce the CSF signal. Blood flow trajectory variations had minor effects, but differences along the trajectory reduced DANTE efficiency in low- areas. Introducing low-velocity pulsatility of both CSF and vessel wall helped explain the in vivo observed signal heterogeneity in both tissue types. The presented simulation framework facilitates a more comprehensive optimization of DANTE-SPACE sequence parameters. Furthermore, the simulation framework helps to explain observed contrasts in acquired data.

The pseudoentropy of allele frequency trajectories, the persistence of variation, and the effective population size

To concisely describe how genetic variation, at individual loci or across whole genomes, changes over time, and to follow transitory allelic changes, we introduce a quantity related to entropy, that we term pseudoentropy. This quantity emerges in a diffusion analysis of the mean time a mutation segregates in a population. For a neutral locus with an arbitrary number of alleles, the mean time of segregation is generally proportional to the pseudoentropy of initial allele frequencies. After the initial time point, pseudoentropy generally decreases, but other behaviours are possible, depending on the genetic diversity and selective forces present.For a biallelic locus, pseudoentropy and entropy coincide, but they are distinct quantities with more than two alleles. Thus for populations with multiple biallelic loci, the language of entropy suffices. Then entropy, combined across loci, serves as a concise description of genetic variation. We used individual based simulations to explore how this entropy behaves under different evolutionary scenarios. In agreement with predictions, the entropy associated with unlinked neutral loci decreases over time. However, deviations from free recombination and neutrality have clear and informative effects on the entropy’s behaviour over time.Analysis of publicly available data of a natural D. melanogaster population, that had been sampled over seven years, using a sliding-window approach, yielded considerable variation in entropy trajectories of different genomic regions. These mostly follow a pattern that suggests a substantial effective population size and a limited effect of positive selection on genome-wide diversity over short time scales.

Topology optimization for rigid and compliant hybrid mechanisms

This paper proposes a topology optimization method integrating the variable trajectory constraints to design rigid and compliant hybrid mechanisms. The variable trajectory constraints are distributed in the design domain and are uniformly modeled by nonlinear spring model. Each of the variable trajectory constraints has an active or inactive state and different states map various mechanical properties of the nonlinear springs. The nonlinear relation between force and displacement of the spring is formulated. A new group of design variables denoting the states of the springs is introduced into the traditional density-based topology optimization model. The design variables representing the element density of the continuum structure and the states of the variable trajectory constraints are uniformly penalized to avoid intermediate values in order to obtain a physically realizable mechanism. Sensitivity analysis is performed by the adjoint equation method. To demonstrate the versatility and the generality of the proposed method, the typical numerical examples including linear, spline and circular trajectory constraints were implemented. The numerical comparisons between the nonlinear spring model and the actual trajectory constraints verify the accuracy. The proposed method expands the application of topology optimization and can be extensively employed to design the mechanisms integrating both the compliant members and rigid parts.

Rare, long-distance dispersal underpins genetic connectivity in the pink sea fan, Eunicella verrucosa.

Characterizing patterns of genetic connectivity in marine species is of critical importance given the anthropogenic pressures placed on the marine environment. For sessile species, population connectivity can be shaped by many processes, such as pelagic larval duration, oceanographic boundaries and currents. This study combines restriction-site associated DNA sequencing (RADseq) and passive particle dispersal modelling to delineate patterns of population connectivity in the pink sea fan, Eunicella verrucosa, a temperate octocoral. Individuals were sampled from 20 sites covering most of the species' northeast Atlantic range, and a site in the northwest Mediterranean Sea to inform on connectivity across the Atlantic-Mediterranean transition. Using 7510 neutral SNPs, a geographic cline of genetic clusters was detected, partitioning into Ireland, Britain, France, Spain (Atlantic), and Portugal and Spain (Mediterranean). Evidence of significant inbreeding was detected at all sites, a finding not detected in a previous study of this species based on microsatellite loci. Genetic connectivity was characterized by an isolation by distance pattern (IBD) (r 2 = 0.78, p < 0.001), which persisted across the Mediterranean-Atlantic boundary. In contrast, exploration of ancestral population assignment using the program ADMIXTURE indicated genetic partitioning across the Bay of Biscay, which we suggest represents a natural break in the species' range, possibly linked to a lack of suitable habitat. As the pelagic larval duration (PLD) is unknown, passive particle dispersal simulations were run for 14 and 21 days. For both modelled PLDs, inter-annual variations in particle trajectories suggested that in a long-lived, sessile species, range-wide IBD is driven by rare, longer dispersal events that act to maintain gene flow. These results suggest that oceanographic patterns may facilitate range-wide stepping-stone genetic connectivity in E. verrucosa and highlight that both oceanography and natural breaks in a species' range should be considered in the designation of ecologically coherent MPA networks.

Identification of cell differentiation trajectory-related gene signature to reveal the prognostic significance and immune landscape in prostate cancer based on multiomics analysis

BackgroundIn the context of prostate cancer (PCa), the occurrence of biochemical recurrence (BCR) stands out as a pivotal factor significantly impacting prognosis, potentially leading to metastasis and mortality. However, the early detection of BCR poses a substantial challenge for PCa patients. There is an urgent need to pinpoint hub genes that can serve as predictive indicators for BCR in PCa patients. MethodsOur primary goal was to identify cell differentiation trajectory-related gene signature in PCa patients by pseudo-time trajectory analysis. We further explored the functional enrichment of overlapped marker genes and probed clinically relevant modules and BCR-related genes using Weighted Gene Co-expression Network Analysis (WGCNA) in PCa patients. Key genes predicting recurrence-free survival were meticulously identified through univariate and multivariate Cox regression analyses. Subsequently, these genes were utilized to construct a prognostic gene signature, the expression, predictive efficacy, putative functions, and immunological landscape of which were thoroughly validated. Additionally, we employed immunohistochemistry (IHC) and a western blotting assay to quantify the expression of PYCR1 in clinical samples. ResultsOur single-cell RNA (scRNA) sequencing analysis unveiled three subgroups characterized by distinct differentiation trajectories, and the marker genes associated with these groups were extracted from PCa patients. These marker genes successfully classified the PCa sample into two molecular subtypes, demonstrating a robust correlation with clinical characteristics and recurrence-free survival. Through WGCNA and Lasso analysis, we identified four hub genes (KLK3, CD38, FASN, and PYCR1) to construct a risk profile of prognostic genes linked to BCR. Notably, the high-risk patient group exhibited elevated levels of B cell naive, Macrophage M0, and Macrophage M2 infiltration, while the low-risk group displayed higher levels of T cells CD4 memory activated and monocyte infiltration. Furthermore, IHC and western blotting assays confirmed the heightened expression of PYCR1 in PCa tissues. ConclusionThis study leveraged the differentiation trajectory and genetic variability of the microenvironment to uncover crucial prognostic genes associated with BCR in PCa patients. These findings present novel perspectives for tailoring treatment strategies for PCa patients on an individualized basis.

Compassion Dynamics in Medical Students: An Ecological Momentary Assessment Study.

Effective interventions to support compassionate patient- and self-care requires an understanding of how to best assess compassion. Micro-ecological momentary assessment (micro-EMA), a method in which participants provide brief responses in real-time within their own environments, can capture changes in compassion across time and contexts. This study examined a micro-EMA approach for measuring the temporal dynamics of compassion in medical students during the COVID-19 pandemic. Medical students (N = 47) completed demographic information and self-report questionnaires assessing empathy and compassion for self and others. Participants then completed six bursts of micro-EMA smartphone-delivered surveys. Each burst was 14days, with 28days between bursts. During each burst, participants received four daily micro-EMA surveys assessing compassion, stress, positive affect, and negative affect. Dynamic structural equation modeling was used to examine micro-EMA responses. The overall micro-EMA response rate was 83.75%. On average, daily compassion did not significantly change across the academic year. However, there was significant within-person variability in medical students' compassion trajectories over the training year (b = 0.027, p < .01). At concurrent timepoints, micro-EMA assessed compassion was associated with greater happiness (b = 0.142, p < .001) and lower stress (b = -0.052, p < .05) but was not associated with sadness. In lagged analyses, higher micro-EMA assessed compassion predicted higher next day happiness (b = 0.116, p < .01) and vice versa (b = 0.185, p < .01). Results suggest it is feasible to use micro-EMA to assess daily levels of compassion among medical students. Additionally, there is wide variability in day-to-day fluctuations in compassion levels among medical students, with some students showing substantial increases in daily compassion across the training year and others showing decreases. Positive affect as opposed to negative affect may have particularly strong associations with compassion. Further examination of antecedents and consequences of fluctuations in daily compassion could inform potent intervention targets.

Recurrent evolutionary switches of mitochondrial cytochrome c maturation systems in Archaeplastida

Mitochondrial cytochrome c maturation (CCM) requires heme attachment via distinct pathways termed systems I and III. The mosaic distribution of these systems in Archaeplastida raises questions about the genetic mechanisms and evolutionary forces promoting repeated evolution. Here, we show a recurrent shift from ancestral system I to the eukaryotic-specific holocytochrome c synthase (HCCS) of system III in 11 archaeplastid lineages. Archaeplastid HCCS is sufficient to rescue mutants of yeast system III and Arabidopsis system I. Algal HCCS mutants exhibit impaired growth and respiration, and altered biochemical and metabolic profiles, likely resulting from deficient CCM and reduced cytochrome c-dependent respiratory activity. Our findings demonstrate that archaeplastid HCCS homologs function as system III components in the absence of system I. These results elucidate the evolutionary trajectory and functional divergence of CCM pathways in Archaeplastida, providing insight into the causes, mechanisms, and consequences of repeated cooption of an entire biological pathway.

Characterize fracture geometry and propagation with low frequency distributed acoustic sensing strain data

Low-frequency distributed acoustic sensing (LF-DAS) strain data from offset wells are widely used to characterize hydraulic fracture geometry. In this paper, we propose a new optimization model for DAS interpretation. The model quantifies the fracture propagation trajectory and fracture geometry variation with time from low-frequency DAS strain data of offset wells. First, the optimization model is developed by combining the Green function and the Sneddon fracture width function to correlate parameters such as fracture width distribution, fracture length and fracture location with the far-field strain distribution. Second, the optimization model is solved by the Levenberg-Marquardt nonlinear least squares algorithm. The model was validated by generating cases. In addition, the model was applied to the interpretation of fracture propagation characteristics for the fiber optic well case of HFTS-2 offset wells. The interpretation results can visually determine the fracture modification effect and help to improve the production efficiency.

Influence of interactive effects on long-term population trajectories in multispecies reintroductions.

Reintroduced populations are typically considered to progress through establishment, growth, and regulatory phases. However, most reintroduction programs do not monitor intensively enough to test this conceptual model. We studied population indices derived from track activity of 4 threatened species (greater bilby [Macrotis lagotis], burrowing bettong [Bettongia lesueur], greater stick-nest rat [Leporillus conditor], and Shark Bay bandicoot [Perameles bougainville]) over 23years after multiple reintroductions of each species in arid Australia. We compared population trajectories among species and investigated the effect of time and environmental variables. All species bred immediately after release, and the growth phase lasted 3-16years, varying markedly among but not within species. The end of the growth phase was characterized by an obvious peak in population density followed by either a catastrophic decline and sustained low density (bettongs), a slow decline to extirpation after 20years (stick-nest rat), or a slight decline followed by irregular fluctuations (bilby and bandicoot). Minor fluctuations were related to environmental variables, including 12-month cumulative rainfall and lagged summer maximum temperatures. Three of the 4 species did not reach a regulation phase, even after 23years, possibly due to interspecific competition and trophic cascades triggered by predator removal and multispecies reintroductions. Bilbies and bandicoots exhibited a second growth phase 18years after reintroduction, likely caused by high rainfall and increased resources following the population crash of overabundant bettongs. Our results suggest that assemblages within multispecies reintroductions demonstrate high variability in population trajectories due to interactive effects. Intensive monitoring to assess population viability may require decades, particularly where multiple species are reintroduced, release sites are confined, and the climate is unpredictable. Intensive monitoring also allows for adaptive management to prevent precipitous population declines. Practitioners should not assume reintroduced species pass through predictable postrelease population phases or that viability is assured after a certain period.

Fetal Medicine Foundation charts for fetal growth in twins.

To derive reference distributions of estimated fetal weight (EFW) in twins relative to singletons. Gestational-age- and chorionicity-specific reference distributions for singleton percentiles and EFW were fitted to data on 4391 twin pregnancies with two liveborn fetuses from four European centers, including 3323 dichorionic (DC) and 1068 monochorionic diamniotic (MCDA) twin pregnancies. Gestational age was derived using the larger of the two crown-rump length measurements obtained during the first trimester of pregnancy. EFW was obtained from ultrasound measurements of head circumference, abdominal circumference and femur length using the Hadlock formula. Singleton percentiles were obtained using the Fetal Medicine Foundation population weight charts for singleton pregnancies. Hierarchical models were fitted to singleton Z-scores with autoregressive terms for serial correlations within the same fetus and between twins from the same pregnancy. Separate models were fitted for DC and MCDA twins. Fetuses from twin pregnancies tended to be smaller than singletons at the earliest gestational ages (16 weeks for MCDA and 20 weeks for DC twins). This was followed by a period of catch-up growth until around 24 weeks. After that, both DC and MCDA twins showed reduced growth. In DC twins, the EFW corresponding to the 50th percentile was at the 50th percentile of singleton pregnancies at 23 weeks, the 43rd percentile at 28 weeks, the 32nd percentile at 32 weeks and the 22nd percentile at 36 weeks. In MCDA twins, the EFW corresponding to the 50th percentile was at the 36th percentile of singleton pregnancies at 24 weeks, the 29th percentile at 28 weeks, the 19th percentile at 32 weeks and the 12th percentile at 36 weeks. In DC and, to a greater extent, MCDA twin pregnancies, fetal growth is reduced compared with that observed in singleton pregnancies. Furthermore, after 24 weeks, the divergence in growth trajectories between twin and singleton pregnancies becomes more pronounced as gestational age increases. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Timescale of the Morphodynamic Feedback Between Planform Geometry and Lateral Migration of Meandering Rivers

AbstractAcross varied environments, meandering channels evolve through a common morphodynamic feedback: the sinuous channel shape causes spatial variations in boundary shear stress, which cause lateral migration rates to vary along a meander bend and change the shape of the channel. This feedback is embedded in all conceptual models of meandering channel migration, and in numerical models, it occurs over an explicit timescale (i.e., the model time step). However, the sensitivity of modeled channel trajectory to the time step is unknown. In numerical experiments using a curvature‐driven model of channel migration, we find that channel trajectories are consistent over time if the channel migrates ≤10% of the channel width over the feedback timescale. In contrast, channel trajectories diverge if the time step causes migration to exceed this threshold, due to the instability in the co‐evolution of channel curvature and migration rate. The divergence of channel trajectories accumulates with the total run time. Application to hindcasting of channel migration for 10 natural rivers from the continental US and the Amazon River basin shows that the sensitivity of modeled channel trajectories to the time step is greatest at low (near‐unity) channel sinuosity. A time step exceeding the criterion causes over‐prediction of the width of the channel belt developed over millennial timescales. These findings establish a geometric constraint for predicting channel migration in landscape evolution models for lowland alluvial rivers, upland channels coupled to hillslopes and submarine channels shaped by turbidity currents, over timescales from years to millennia.

Comparative analysis of internal flow characteristics and particle trajectories of centrifugal pumps with different impeller structures under solid-liquid two-phase flow conditions

The disc pump is a non-conventional centrifugal pump that utilizes centrifugal force and boundary layer effects to transport fluids. This pump is widely used in industries such as petrochemicals. However, due to the presence of particles in the solid-liquid two-phase flow, it causes wear and performance degradation of the pump’s flow components. However, due to the presence of particles in the solid-liquid two-phase flow, it can cause wear and performance degradation of the pump components. To study the internal flow characteristics of solid-liquid flow and the particle trajectory in a bladed disc pump, numerical simulation method was adopted to perform steady-state numerical simulation of spherical particles with different diameters (0.1 mm, 0.25 mm, 0.4 mm) in the bladed disc pump. The results indicate that compared to conventional centrifugal pumps, the performance of the bladed disc pump is lower. The variation in particle diameter has a minor influence on the intensity of the internal flow field in the bladed disc pump. The particle trajectories inside the impeller of the bladed disc pump are more chaotic, with larger diameter particles exhibiting a wider range of trajectory variations, while smaller diameter particles maintain relatively stable motion trajectories.

A test of the loose-equilibrium concept with long-lived organisms: Evaluating temporal change in freshwater mussel assemblages.

The loose-equilibrium concept (LEC) predicts that ecological assemblages change transiently but return towards an earlier or average structure. The LEC framework can help determine whether assemblages vary within expected ranges or are permanently altered following environmental change. Long-lived, slow-growing animals typically respond slowly to environmental change, and their assemblage dynamics may respond over decades, which transcends most ecological studies. Unionid mussels are valuable for studying dynamics of long-lived animals because they can live >50 years and occur in dense, species-rich assemblages (mussel beds). Mussel beds can persist for decades, but disturbance can affect species differently, resulting in variable trajectories according to differences in species composition within and among rivers. We used long-term data sets (10-40 years) from seven rivers in the eastern United States to evaluate the magnitude, pace and directionality of mussel assemblage change within the context of the LEC. Site trajectories varied within and among streams and showed patterns consistent with either the LEC or directional change. In streams that conformed to the LEC, rank abundance of dominant species remained stable over time, but directional change in other streams was driven by changes in the rank abundance and composition of dominant species. Characteristics of mussel assemblage change varied widely, ranging from those conforming to the LEC to those showing strong directional change. Conservation approaches that attempt to maintain or create a desired assemblage condition should acknowledge this wide range of possible assemblage trajectories and that the environmental factors that influence those changes remain poorly understood.

Feedback loops drive ecological succession: towards a unified conceptual framework.

The core principle shared by most theories and models of succession is that, following a major disturbance, plant-environment feedback dynamics drive a directional change in the plant community. The most commonly studied feedback loops are those in which the regrowth of the plant community causes changes to the abiotic (e.g. soil nutrients) or biotic (e.g. dispersers) environment, which differentially affect species availability or performance. This, in turn, leads to shifts in the species composition of the plant community. However, there are many other PE feedback loops that potentially drive succession, each of which can be considered a model of succession. While plant-environment feedback loops in principle generate predictable successional trajectories, succession is generally observed to be highly variable. Factors contributing to this variability are the stochastic processes involved in feedback dynamics, such as individual mortality and seed dispersal, and extrinsic causes of succession, which are not affected by changes in the plant community but do affect species performance or availability. Both can lead to variation in the identity of dominant species within communities. This, in turn, leads to further contingencies if these species differ in their effect on their environment (priority effects). Predictability and variability are thus intrinsically linked features of ecological succession. We present a new conceptual framework of ecological succession that integrates the propositions discussed above. This framework defines seven general causes: landscape context, disturbance and land-use, biotic factors, abiotic factors, species availability, species performance, and the plant community. When involved in a feedback loop, these general causes drive succession and when not, they are extrinsic causes that create variability in successional trajectories and dynamics. The proposed framework provides a guide for linking these general causes into causal pathways that represent specific models of succession. Our framework represents a systematic approach to identifying the main feedback processes and causes of variation at different successional stages. It can be used for systematic comparisons among study sites and along environmental gradients, to conceptualise studies, and to guide the formulation of research questions and design of field studies. Mapping an extensive field study onto our conceptual framework revealed that the pathways representing the study's empirical outcomes and conceptual model had important differences, underlining the need to move beyond the conceptual models that currently dominate in specific fields and to find ways to examine the importance of and interactions among alternative causal pathways of succession. To further this aim, we argue for integrating long-term studies across environmental and anthropogenic gradients, combined with controlled experiments and dynamic modelling.

Hemoperfusion with high-affinity polyethylene microbeads (Seraph-100®) for the removal of pathogens in chronic critically ill patients: Clinical experience.

Critically ill septic patients present variable clinical trajectories, with some succumbing to hyperinflammatory responses while others develop a chronic critical illness, characterized by a prolonged low-grade inflammation, muscle atrophy, and mechanical ventilation dependency and often develop secondary infections often caused by from low-virulence microorganisms or reactivated latent viruses. The Seraph-100® hemoperfusion cartridge takes advantage from heparin-coated ultra-high molecular weight polyethylene microbeads mimicking pathogen-binding cell receptors and can adsorb both pathogens and damage-associated molecular patterns released by injured tissues. We describe two chronic critically ill patients who developed secondary viral bloodstream infections successfully treated with this device.

Numerical multi-objective optimization of segmented and variable blank holder force trajectories in deep drawing based on DNN-GA-MCS strategy

Numerical multi-objective optimization of segmented and variable blank holder force trajectories in deep drawing based on DNN-GA-MCS strategy

Examining the Trajectory of Health-Related Quality of Life among Coronavirus Disease Patients.

Recent studies have reported a reduction in health-related quality of life (HR-QoL) among post-coronavirus disease 2019 (COVID-19) patients. However, there remains a gap in research examining the heterogeneity and determinants of HR-QoL trajectory in these patients. To describe and identify factors explaining the variability in HR-QoL trajectories among a cohort of patients with history of COVID-19. A prospective study using data from a cohort of COVID-19 patients enrolled into a registry established at a health system in New York City. Participants were enrolled from July 2020 to June 2022, and completed a baseline evaluation and two follow-up visits at 6 and 12months. We assessed HR-QoL with the 29-item Patient Reported Outcomes Measurement Information System instrument, which was summarized into mental and physical health domains. We performed latent class growth and multinomial logistic regression to examine trajectories of HR-QoL and identify factors associated with specific trajectories. The study included 588 individuals with a median age of 52years, 65% female, 54% White, 18% Black, and 18% Hispanic. We identified five physical health trajectories and four mental health trajectories. Female gender, having pre-existing hypertension, cardiovascular disease, asthma, and hospitalization for acute COVID-19 were independently associated with lower physical health. In addition, patients with increasing body mass index were more likely to experience lower physical health over time. Female gender, younger age, pre-existing asthma, arthritis and cardiovascular disease were associated with poor mental health. We found significant heterogeneity of HR-QoL after COVID-19, with women and patients with specific comorbidities at increased risk of lower HR-QoL. Implementation of targeted psychological and physical interventions is crucial for enhancing the quality of life of this patient population.

A Shape-Based Monitoring Method for Variable Trajectories of Finishing Mill Processes

As the most critical procedure in the hot strip mill process (HSMP), the performance of the finishing mill process (FMP) has a significant influence on the key performance indicators (KPIs). Considering that the multivariate statistical process monitoring (MSPM) methods and batch alignment methods (which are implemented in a point-to-point manner) cannot effectively handle the uneven-length and multiphase characteristics of FMP data, we propose a method to monitor the shape of the variable trajectories that are closely associated with KPIs. First, the historical FMP data characterized by different grades and thickness is utilized to build monitoring models based on the Shape-Based Distance (SBD) to obtain two statistics, i.e. the SBDs and the corresponding offsets when aligned with the central trajectories. Then, by comparing the statistics of the new coming trajectories with the control limits obtained from the training set, the new coming batches can be monitored. In the end, the proposed method is tested on the real FMP dataset to validate its effectiveness.