Transport, retention and degradation of the urban biocides terbutryn, diuron and octylisothiazolinone and the herbicide acetochlor in urban surface-soil interfaces.

Abstract Recent analysis of 2968 MaNGA early-type galaxies has yielded two notable trends with velocity dispersion ( σ ) not previously discussed in the literature. First, Fe abundance rises with σ but only until σ ≈ 100 km s −1 , after which it falls. This kink is reproduced by TNG100 simulations, implying that hierarchical merger processes might explain it. Second, astrophysical scatter in N is high for galaxies with σ < 100 km s −1 . Due to the restricted list of nucleosynthetic sources for N, it is likely that asymptotic giant branch stars provide most of this N. A varied star formation history (compared to that of massive galaxies) along with variable retention and recycling of N-enriched gas might explain the fuzz of N abundance in low- σ galaxies. Because a timescale argument seems necessary to explain the nitrogen fuzz, and an initial mass function argument is ruled out, similar timescale arguments for the [Mg/Fe] trend as a function of velocity dispersion are supported.

Forcibly displaced people face significant biopsychosocial barriers to accessing health care. Digital health interventions have emerged as tools to bridge care gaps and have been successfully implemented in other disadvantaged populations to improve health care access and outcomes. However, the feasibility and practicality of digital health interventions among forcibly displaced individuals cannot be fully evaluated without characterizing recruitment and retention rates for these interventions in this unique population. To evaluate the recruitment rate and retention rate for digital health interventions in forcibly displaced people. A comprehensive search was conducted in PubMed, Web of Science, and SocINDEX in January 2023, with an updated search in February 2024. The search strategy followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The protocol was registered in PROSPERO. Only randomized clinical trials evaluating digital health interventions in forcibly displaced populations were included. Non-peer reviewed studies, reviews, and studies lacking recruitment or retention data were excluded. Two independent reviewers screened and selected studies, and conflicts were resolved by a third reviewer. Data were extracted independently by 2 reviewers using Covidence, and a third reviewer resolved discrepancies. Meta-analysis was conducted using a random-effects model to estimate the pooled recruitment rate and retention rate. Study quality was assessed using the Downs and Black Checklist. Recruitment rate (percentage of prospective participants who were successfully randomized) and retention rate (percentage of randomized participants who completed the intervention). A total of 9 randomized clinical trials with 2858 participants were analyzed. The most frequently investigated technology was mobile applications (4 trials), followed by mobile phones (3 trials), with 1 study utilizing tablets and another using wearables. Recruitment rates varied widely across studies (16% to 100%), as did retention rates (28% to 91%). The pooled recruitment rate was 91% (95% CI, 57%-99%; I2 = 99%), and the pooled retention rate was 68% (95% CI, 48%-84%; I2 = 98%). In this systematic review and meta-analysis of 9 randomized clinical trials, forcibly displaced populations exhibited variable recruitment and retention rates, although pooled estimates were high. These findings suggest that digital technologies provide a unique opportunity for scalable health interventions in this population, which may mitigate the negative health consequences arising from the many biopsychosocial barriers to in-person care.

Long-term impacts of land cover change on nitrate export in mixed-use exurban and suburban watersheds.

ABSTRACT Riparian buffers provide many important functions for streams, including shade to limit water temperature increases after forest harvest. Conventional buffer designs often designate a minimum width, but alternative configurations such as hydrologically adaptive variable retention or canopy gaps buffers may enhance stream productivity by introducing heterogeneity in stream light whilst still providing thermal buffering, shade, and large wood recruitment. Therefore, alternative buffer designs may be an important climate adaptation strategy. To better understand stream temperature responses to conventional and novel alternative riparian buffer configurations, we conducted a large‐scale before‐after control‐impact experiment across 28 streams in western Oregon. We established six replicate stream blocks that each included five streams: an uncut reference stream and four streams with different riparian buffer designs (Fixed‐Width, Standard Practise, Variable Retention, and Canopy Gaps). Prior to treatment, all streams were well shaded (mean effective shade = 96.2%), post‐treatment percent shade was reduced by up to 31.4 percentage points. Mixed effect model estimates indicated a 7 day moving average of daily maxima temperatures (T7Max) increased post‐treatment by 0.89°C, 0.94°C, 0.79°C, and 0.42°C in Fixed‐Width, Standard Practise, Variable Retention, and Canopy Gaps treatments, respectively, but did not differ amongst treatments. Stream temperature response was explained by both percent reduction in effective shade and bankfull width, indicating stream temperature was more sensitive to reductions in shade in smaller streams. We found Variable Retention and Fixed‐Width buffers, but not buffers with Canopy Gaps, increased longitudinal temperature variability. Our findings suggest that novel alternative buffers were as protective of temperature as conventional buffers whilst allowing flexibility in application. Therefore, these hydrologically adaptive Variable Retention or Canopy Gaps alternatives may be viable tools to both limit temperature increases and enhance variation in light conditions.

Retention harvests are promoted as an alternative to clearcuts to enhance ecological values in managed forests. Understanding how retention affects carbon (C) dynamics over time and in various forest types is important for balancing objectives like timber production and C storage. This is particularly crucial now, as the climate mitigating effects of boreal forests are weakening due to both forest harvests and natural disturbances. Using data from a relatively long‐term experiment (pre‐harvest to 18‐years post‐harvest) in previously unharvested boreal mixedwood forest, we compared C pools (mature trees, regenerating trees and shrubs, deadwood, and soil) among harvest levels (clearcuts, 10%, 20%, 50%, 75% retention, and unharvested reference). Soil C appeared to be invariant at the scale of this study, so we focused our analyses on biomass in living and dead vegetation. Total pre‐harvest C storage was greater in conifer‐dominated and mixed stands than in deciduous (broadleaf)‐dominated stands, reflecting mainly greater biomass in live trees but also in downed deadwood. Net loss of C from the forest up to 3‐years post‐harvest scaled with harvest intensity in all forest types. At 3‐ and 18‐years post‐harvest in deciduous and 3‐years post‐harvest in conifer stands, all retention harvests resulted in larger C stocks than clearcuts; only higher retention levels provided this benefit at 3‐ and 18‐years post‐harvest in mixed (75% retention) and at 18 years in conifer stands (50%, 75% retention). In some forest types, the highest retention levels (75% for deciduous and mixed stands, 50% and 75% for conifer stands) maintained total C stocks statistically equivalent to unharvested forest at both 3‐ and 18‐years post‐harvest. Deciduous stands became net C sinks by 3–7 years post‐harvest, likely due to prolific aspen regeneration and growth. Mixed and conifer stands, however, were nearly C‐neutral or were C sources until 12–18 years post‐harvest. This reflected persistent effects of pre‐harvest forest type, including less aspen regeneration, slower growth of conifer seedlings, and mortality of retained conifers. Our results suggest that strategic retention harvesting could serve as a practical option to couple C storage options to other management considerations.

The newly proposed metabolic-associated fatty liver disease (MAFLD) definition better reflects the metabolic pathogenesis shared with non-alcoholic fatty liver disease (NAFLD), though with incomplete diagnostic overlap; this study systematically compares their prevalence and risk profiles in U.S. adolescents to inform optimal clinical management strategies. This cross-sectional study analyzed participants with complete survey data from the 2017-2020 cycle of the National Health and Nutrition Examination Survey (NHANES), identifying and comparing 532 MAFLD cases and 527 NAFLD cases through comprehensive prevalence assessment, detailed clinical characterization, regression for variable selection, and multivariate logistic regression analysis of independent risk factor associations. MAFLD prevalence was 22.8% (95%CI:18.8-26.8) vs. NAFLD's 25.8% (21.5-30.0). MAFLD cases demonstrated significantly greater metabolic severity, evidenced by elevated BMI (31.49 ± 6.63 vs 21.70 ± 4.18kg/m2), worsened insulin resistance (HOMA-IR 5.44 ± 3.59 vs 2.48 ± 1.44), and more pronounced hepatic injury markers (ALT 21.85 ± 13.04 vs 14.36 ± 7.40 U/L; all p < 0.001). MAFLD and NAFLD prevalence showed strong ethnic disparities, peaking in Mexican Americans (40.6% vs 42.9%) and obese females (79.0% vs 78.1%). LASSO regression selection identified obesity as the primary shared risk factor (MAFLD coefficient = 1.203; NAFLD = 0.844), while revealing MAFLD's more complex metabolic signature through retention of additional variables (8 vs 6 in NAFLD model). Waist circumference showed consistent associations across both classifications (MAFLD OR = 1.10, 95%CI:1.02-1.19; NAFLD OR = 1.09, 95%CI:1.03-1.15), though triglyceride levels only approached significance in NAFLD (OR = 1.60, 95%CI:0.93-2.75, p = 0.086). Multivariate logistic regression analyses confirmed stronger metabolic abnormalities associations in MAFLD (OR = 3.46, 95%CI:1.41-8.53, p = 0.011) versus NAFLD (OR = 1.45, 95%CI:0.63-3.32, p = 0.364), with similar patterns for obesity (MAFLD OR = 5.71, 95%CI:1.08-30.35; NAFLD OR = 2.24, 95%CI:0.62-8.13). This study demonstrates that while MAFLD and NAFLD share obesity as a core risk factor, MAFLD more specifically identifies adolescents with severe metabolic dysfunction and provides superior risk stratification. The stronger metabolic dysfunction associations and greater model complexity support MAFLD's clinical utility for early intervention in high-risk youth populations.

Virtual Digital Human Pedagogical Agents (VDHPAs) have emerged as vital tools in online and blended learning environments. However, the extent to which they improve learning outcomes in Virtual Reality (VR) environments remains inconclusive. This meta-analysis synthesizes findings from 36 empirical studies conducted between 2013 and 2023 to examine the effectiveness of VDHPAs in VR-based learning. Specifically, we analysed two process-oriented variables—cognitive load and social presence—and three outcome-oriented variables—retention, transfer, and other assessment types. The results indicate that while VDHPAs do not significantly reduce cognitive load (g = -0.084), they significantly enhance learners’ social presence (g = 0.402). Additionally, VDHPAs were found to improve retention (g = 0.451), transfer (g = 0.288), and other test scores (g = 0.423). Moderator analyses revealed that the effects vary depending on agent design features (e.g., gestures, voice, facial expression), content characteristics (e.g., subject domain, knowledge type), and learner attributes (e.g., education level, prior knowledge). This review further discusses the implications of agent embodiment, the "uncanny valley" in affective response, and challenges in long-term outcome assessments. The study contributes to a deeper understanding of how to optimise VDHPAs for immersive learning experiences and highlights directions for future interdisciplinary research in educational technology and digital arts.

This study offers a detailed comparative analysis of the reflexes of Proto-Bantu noun class prefixes within nine Gabonese languages belonging to the B50, B60, and B70 groups of Guthrie’s referential inventory of the Bantu languages. Genealogically speaking, all of them are part of the Kwilu-Ngounie subclade of the Bantu family’s West-Coastal Bantu branch. Starting out from a robust dataset comprising over 4000 lexical items collected through fieldwork and existing descriptions, the Comparative Method is used to distinguish changes in noun class morphology due to regular sound shifts from those emerging from analogical reanalysis and levelling. The comparative study shows a systematic reduction and reorganization of the inherited Proto-Bantu noun class system, notably the loss of classes 12/13 and 19 across all languages, variable retention and loss of classes 7/8 and 11, and complex patterns of reshuffling involving classes 5, 9/10, and 1/2. Key innovations, potentially reinforcing lexicon-based hypotheses of phylogenetic subgrouping within Kwilu-Ngounie, include the development of a class 7 allomorphy conditioned by stem-initial segments in the B50 languages and the emergence of vocalic prefixes restricted to the B60 and B70 languages.

Effects of variable retention on the interaction between tree regeneration and understory plants at different regeneration heights over 15 years in Nothofagus pumilio forests

QbD and green metric based HPLC method development and validation of bromocriptine mesylate in bulk product and biological samples.

Abstract Forests significantly influence regional and global water cycles through transpiration, which is affected by meteorological variables, soil water availability, and stand and site characteristics. Variable retention harvesting (VRH) is a forest management practice in which varying densities of trees, such as 55% and 33%, are retained after thinning or harvesting. These trees can be grouped together or evenly distributed. VRH aims to enhance forest growth, improve biodiversity, preserve ecosystem functions, and generate economic revenue from harvested timber. Application of VRH treatment in forest ecosystems can potentially impact the response of forest transpiration to environmental controls. This study analyzed the impacts of four different VRH treatments on sap flow velocity (SV) in an 83‐year‐old red pine (Pinus resinosa Ait.) plantation forest in the Great Lakes region in Canada. These VRH treatments included 55% aggregated (55A), 55% dispersed (55D), 33% aggregated (33A), and 33% dispersed (33D) basal area retention, and an unharvested control (CN) plot, 1 ha each. Analysis of counterclockwise hysteresis loops between SV and meteorological variables showed larger hysteresis areas between SV and photosynthetically active radiation (PAR) than vapor pressure deficit (VPD) and air temperature (Tair), particularly in clear sky and warm temperatures in the summer. It demonstrated that PAR was the primary control on SV across VRH treatments, followed by VPD and Tair. Larger hysteresis loop areas and higher SV values were observed in the CN and 55D treatments, with lower values found in the 55A, 33D, and 33A plots. This suggests that maintaining dispersed retention of 55% basal area (55D) is the optimal forest management practice that can be utilized to enhance transpiration and forest growth. These findings will assist forest managers and other stakeholders to adopt sustainable forest management practices, thereby enhancing forest growth, water use efficiency, and resilience to climate change. Additionally, these practices will contribute to nature‐based climate solutions.

Deprivation of Critical Care systems are a major cause of fatality worldwide, highlighting it’s need for saving human lives. This study proposes a novel hybrid ensemble model, which integrates Random Forests, Gradient Boosting Machines (GBM), and Neural Networks to enhance the predictive accuracy diagnostics. The methodology combines data pre-processing, feature selection, and ensemble learning, ensuring robust and reliable predictions. Comprehensive data pre-processing includes K-Nearest Neighbours (KNN) imputation for missing values, Z-Score normalization for scaling, and Polynomial Feature Generation for non-linear feature interactions. Feature selection performed using Recursive Feature Elimination (RFE) and Mutual Information relevant variable retention. The proposed model produces 98.55% accuracy, very surpassing nine baseline models, that includes XGBoost, Random Forests, and Neural Networks. Additional metrics such as precision (97.80%), recall (98.12%), F1-Score (98.00%), and ROC-AUC (99.12%) further validate the model's robustness. This framework not only demonstrates superior accuracy but also ensures computational efficiency, making it viable for deployment in real-world healthcare settings.

Firm performance always remained an area of interest for all stakeholders including stockholders, creditors, management, government, suppliers, etc. So far, several internal and external factors that contribute to the performance of a firm, have been identified by the researchers. Along with different external factors, the ownership structure is also considered an important factor contributing to firm performance. Various studies have found that the relation between ownership structure and firm performance is not straightforward. This relation is influenced by a number of other factors. The decision-making of a firm is affected by the ownership structure, based on the level of control different owners have over the organization. While conducting the research, the researcher has considered other factors like retention ratio, increase in debt level and firm’s size along with the different dimensions of ownership structure. This study has adopted the quantitative approach to study and analyze the relation between the selected variables in the model. The data has been collected from annual reports of different manufacturing companies. Stata software has been used to analyze the data. The findings of the study are mixed; stating that family and institutional ownership have a significant impact on the firm performance in the presence of the control variables (retention ratio, increase in debt level, and firm size) leading to the fact that firms with concentrated ownership tend to perform better in Pakistan as controlling shareholders have stronger incentive for controlling and monitoring the performance of the management team.

By studying beach tourism in South Lampung, Indonesia, researchers assess how customer satisfaction affects customer retention. In this study use variables, service quality, promotion, and destination image, with using the mediating variable and customer satisfaction and the endogenous variable customer retention, this article employs the Structural Equation Model (SEM) technique with 360 respondents, revealing a relationship where customer retention is influenced by service quality, promotion, destination image variables mediated by customer satisfaction. Therefore, researchers recommend several strategies for the Lampung Provincial government, namely being able to enhance promotions, providing good service to improve service quality, and developing adequate facilities that can be utilized by visitors to enhance destination image variables.

Abstract The province of British Columbia (BC) has undergone several attempts to address public discontent with forest management reflected in the decline in forestry over the last 25 years. The creation of silviculture systems such as variable retention and clearcut with reserves has addressed biodiversity and visual quality values allowing forest tenure holders to access timber using a clearcut, the profitable high volume/low-cost harvesting system. The author lists the negative consequences of application of retention silviculture systems built for purposes other than tree regeneration and timber production. The predominant application of such a silviculture system in BC and non-existence of forest management rooted in traditional partial harvesting systems may be a factor in financial losses to the Province of BC, decline in timber production and excessive application of chemical and manual brushing. The author suggests that the overhaul of forest management in BC including tenure reform and silviculture regulation change is needed to ensure proper ecologically suitable silviculture systems are applied and the BC forest management is revitalized.

It is well established that there is an elevated overdose risk with benzodiazepine (BZD) use during opioid agonist treatment (OAT). However, further studies regarding other aspects of how BZDs influence OAT are necessary. This review summarizes the literature on concurrent BZD use with medications for opioid use disorder (MOUD) and how they affect treatment retention in OAT. EMBASE (Ovid), PubMed, and Google Scholar database search tools were used to search for studies that examined the effect of concurrent BZD and MOUD on treatment retention in OAT. Studies published up to January 30th, 2024, were included with no restriction applied other than English language. The criteria for included literature were the presence of both BZD and at least one MOUD as a variable and treatment retention or MOUD adherence as an outcome. Fourteen articles met the criteria for review: eleven retrospective studies and three observational studies. Methadone was utilized in seven studies, buprenorphine in five, naltrexone in one, and suboxone (buprenorphine + naloxone) in one study. The included studies indicated that when BZDs are taken as prescribed and for shorter periods in conjunction with OAT, subjects are retained in their MOUD programs just as well as patients who do not take BZDs. Any potential benefits of increased treatment retention must be balanced against potential harmful effects of BZD use, such as drug overdose and addiction. Further studies must be performed to validate the results of treatment retention and to evaluate other factors that might affect OAT.

Breast augmentation, a commonly sought cosmetic procedure, has shifted towards autologous fat grafting (AFG) as an alternative to implants, primarily due to long-term complications associated with implants. This review aims to provide a comprehensive summary of the autologous fat grafting (AFG) application in breast augmentation surgery. A systematic search strategy was developed for the MEDLINE database and additional articles were identified by reviewing the references. AFG involves harvesting, processing, and injecting the patient's fat into the breast, providing natural results and fewer complications compared to implants. The procedure's success depends on the surgeon's skill. There are challenges and considerations associated with AFG, including volume limitations, variable retention rates, and potential complications such as infections and cyst formation. Uncertainties in fat retention rates influenced by various factors like fat content, processing methods, injection techniques, and patient characteristics, emphasizing the need for further research and careful patient selection.

Background: A prehospital, paramedic-administered scale to distinguish intracerebral hemorrhage (ICH) from acute cerebral ischemia (ACI) could improve routing to appropriate centers, enrich field randomized trials with targeted subtype patients, and potentially guide prehospital clinical treatment such as hyperacute blood pressure (BP) lowering. We aimed to create a quickly administered prehospital scale from prospectively performed field assessments. Methods: Two scales were created from NIH Field Administration of Stroke Therapy Magnesium (FAST-MAG) trial data, using logistic regression model with backward stepwise variable selection and retention criterion of p&lt;0.1. Scale one—CASPR-DB (Data-Based)—assessed 26 candidate variables available in routine prehospital care in 1675 patients (77.3% ACI, 22.7% ICH), who were randomly assigned to training (n=1114) or validation (n=561) sets. Scale two—CASPR-CS (Clinical Symptoms)—came from a subset of patients (n=467) in whom three additional clinical symptoms elicited in the field were also candidate items—headache, nausea, and progressing deficit. Results: For the CASPR-DB scale, the logistic regression model selected 10 of the 26 candidate variables in the training population. Factors associated with ICH were higher Los Angeles Motor Scale (LAMS) score, higher Glasgow Coma Score (GCS), higher systolic BP, Hispanic and Caucasian race-ethnicity, male sex, use of anti-platelet agents, decreased age, and absence of diabetes, atrial fibrillation, or valvular heart disease. Each was given a point value between 1-3, yielding a 19-point scale (Table 1). For the CASPR-CS scale, the logistic regression model selected 10 of the 29 candidate variables. All three symptom items—headache, nausea, and progressing deficit—were associated with ICH, along with 7 data-based variables. Each was given a point value between 1-3, yielding a 20-point scale (Table 2). CASPR-DB performance in training was sensitivity 64.4%, specificity 78.6%, accuracy 71.5%, c=0.774 and in validation was sensitivity 69.3%, specificity 61.7%, accuracy 71.5%, c=0.710. CASPR-CS performance was sensitivity 71.8%, specificity 77.8%, accuracy 74.8%, c=0.830. Figure 1 shows the proportions of ICH patients at each CASPR-CS score level. Conclusions: The CASPR-DB scale shows good and CASPR-CS scale very good performance in distinguishing ICH vs ACI in prehospital setting. These readily performable scales could improve prehospital routing and treatment of ICH patients.

Introduction: Prior attempts to assess risk of symptomatic intracranial hemorrhage (sICH) after endovascular thrombectomy have been limited by reliance on information obtained after thrombectomy (such as TICI reperfusion) and lack of generalizability to routine clinical practice. Methods: Patients presenting to GWTG-Stroke participating hospitals between July 2021 and June 2023 with last known well within six hours prior to presentation, who received endovascular thrombectomy were included. The primary outcome was sICH; secondary outcomes included in-hospital mortality, mRS at discharge, and length of stay. The study population was divided into a derivation and validation cohort with 70:30 partition. According to a pre-specified statistical analysis plan, a full model of 31 candidate variables and subsequently a highly parsimonious model including only variables measured before EVT deployment was fit for each endpoint, with variable retention guided by multiple factor analysis (MFA). Models were then externally validated in the HERMES clinical trial population. Results: 31,668 patients (median age 71 [Q1: 61, Q3: 81]) were included, of whom 1,799 (5.7%) developed sICH. In the validation cohort, the area under the receiver operating characteristics curve (AUC) for the full model was 0.649 (Table 1), and the AUC for the simplified points score was 0.589 (Table 2). At the conference, we will present results of external validation and secondary endpoints, details of model calibration, and direct comparisons to existing risk scores. Conclusions: A risk score for sICH after thrombectomy for acute stroke devised using routinely collected data known prior to intervention had good performance compared to existing approaches.