Union University

Background Despite growing scientific evidence and health guidelines, the global health paradox persists, with rising lifestyle-related diseases and escalating healthcare costs exposing the inadequacy of current efforts. Objective Three multidisciplinary congresses were held to generate evidence-based conclusions aimed at addressing the global health paradox. Methods A total of 58 experts from 62 entities participated in the international research and knowledge-exchange panels. Experts reviewed the latest findings to develop practical strategies and identify key research and policy priorities, focusing on the Healthy Eating & Active Living (HEAL) approach. Results, conclusion, and relevance The expert consortium endorsed a 33 evidence-based consensual-statement policy roadmap for addressing global health challenges, emphasizing that the HEAL approach can significantly contribute to the “Prevention First” appeal and broad ethical, social, ecological, and economic advantages, and ultimately supporting policy change.

Purpose Guided by social identity and social exchange theory, this study offers a conceptual model explaining how employees' perceptions of organizational justice—namely distributive, procedural, and interactional justice—shape their evaluations of firm performance when accounting for the mediating role of organizational identification. The model also introduces service climate as a contextual moderator of the justice–identification relationship. Design/methodology/approach Survey data from 246 full-time employees across diverse industries were analyzed using structural equation modeling to test the proposed hypotheses empirically. Findings Organizational identification partially mediates the link between justice perceptions and perceived firm performance. Service climate positively moderates the effect of procedural justice on identification, whereas its interaction with interactional justice yields a negative effect, contrary to expectations, indicating a substitution dynamic. Additionally, the three justice dimensions exert asymmetric influences on identification, underscoring the need to distinguish their distinct roles in organizational contexts. Originality/value This research advances performance management theory by demonstrating that employees' assessments of firm effectiveness are jointly shaped by their justice perceptions and organizational identification. This integrated framework offers a holistic and context-sensitive lens for understanding performance in contemporary organizations. For practitioners, it underscores the need for managerial strategies that are attuned to employees’ priorities across different justice dimensions and diverse organizational settings.

Accurate forecasting of water demand is essential for reliable and efficient operation of distribution networks. However, existing forecasting approaches are usually restricted to single-site closed settings and fail under distributional shifts across pumping stations, leaving the gap of cross-site generalization unresolved. This study addresses the problem using operational data collected from Supervisory Control and Data Acquisition (SCADA) systems provided by the Public Utility Company for Water Treatment Valjevo, which operates the Kolubara water supply region in Serbia. We extend the Informer architecture with statistical alignment (CORAL, MMD), adversarial adaptation (DANN), and meta-learning (MAML, Reptile) to explicitly handle zero , few , and full shot transfer scenarios under covariate shift. The proposed framework reduces mean and peak errors across forecasting horizons, improving resilience where operations are most vulnerable to demand surges, and thus carries direct social relevance for water security. Results show that statistical/adversarial alignment enables effective zero -shot transfer, while meta-learning supports rapid adaptation with only 24–72 h of labeled data, consistently outperforming classical and deep-learning baselines. The evaluation, conducted on multivariate SCADA data, was checked using standard accuracy and peak-sensitive metrics. Generally, the study establishes cross-site transfer learning as an engineering solution for water utilities, offering a deployable pipeline that adapts to new pumping stations with minimal calibration while reducing operational risks and costs and grounding its value in both methodological innovation and empirical validation. • Cross-site forecasting framed as domain adaptation under covariate shift. • Informer backbone extended with CORAL, MMD, DANN, MAML, and Reptile variants. • Meta-adaptation enables rapid few -shot learning with only 24 to 72 labeled hours. • Residual ACF/PACF diagnostics confirm removal of domain-specific autocorrelation. • Supports water security through adaptive forecasting across heterogeneous pumping sites.

Abstract Undesirable enzymatic browning of fruits and vegetables can be controlled by using effective tyrosinase inhibitors. In this study, bioactive tannins purified from the calyx of Potentilla fruticose (PFTs) showed prominent inhibition on both the monophenolase (IC50 = 134.85 ± 0.04 μg/mL) and diphenolase (IC50 = 118.06 ± 8.30 μg/mL) activities of tyrosinase. FT-IR spectroscopy and thiolysis coupled with reverse-phase HPLC-ESI-MS revealed that PFTs were oligomeric condensed tannins with (epi)catechin, (epi)catechin gallate, and (epi)gallocatechin gallate as the predominant constitutive units. The inhibition of diphenolase by PFTs was found to be reversible and mixed type, with competitive inhibition being dominant. Integrated fluorescence, FT-IR spectroscopy and molecular docking results further demonstrated that PFTs bound to tyrosinase via hydrophobic interactions and hydrogen bonding, thereby perturbing the microenvironment of amino acid residues and altering the secondary structure of tyrosinase, which consequently led to the loss of enzyme catalytic activity. During storage, the browning of fresh-cut asparagus lettuce was efficiently delayed after treatment with PFTs, suggestive of its possibility as an anti-browning agent. Furthermore, PFTs possessed superior antioxidant efficacy compared to the commercial antioxidant BHT, as evaluated by DPPH, ABTS and FRAP assays. Taken together, these findings supported the potential application of PFTs in the cosmetic and food preservation industries.

Background: Historical trials of adjunctive dexamethasone for management of neurologic symptoms in malignant spinal cord compression (MSCC) utilized high doses of dexamethasone for 3days then tapered over an additional 12days. There is limited evidence on the current practice of adjunctive dexamethasone. Objective: The purpose of this study was to evaluate various dosing strategies of dexamethasone in MSCC. Methods: This was a retrospective, single-site, analysis of hospitalized patients presenting with MSCC and received dexamethasone. Patients were grouped into 2 cohorts; an acute course (AC, ≤3days) and a prolonged course (PC, >3days), based on length of high-dose dexamethasone therapy (16mg/day). Primary outcome was cumulative dexamethasone dose between groups. Other additional outcomes evaluated safety and efficacy. Results: A total of 26 patients were included, with 14 patients in the AC group and 12 in the PC group. The median cumulative dexamethasone dose was significantly lower in the AC group compared to the PC group (117mg vs 165mg, P < 0.001). Time to IV-to-PO conversion was significantly delayed in the PC group (6days vs 1day, P < 0.001). There were no significant differences in additional outcomes. Conclusion: The findings of this study provide insights into consideration of early tapering strategies to decrease dexamethasone exposure and lessen the risk of adverse effects. Despite the retrospective nature of this small study, the findings of this study highlight the need for more standardized guidance to optimal dose, duration, and tapering strategy for dexamethasone use in patients with MSCC.

This research evaluated the efficacy of the Wechsler Intelligence Scale for Children—Fifth Edition (WISC-V) for gifted identification. Our sample included 390 gifted, highly gifted, and twice-exceptional (2e) children, referred by parents for testing at seven U.S. sites. We examined de-identified scoring data to determine mean performance patterns across WISC-V indexes and investigated which robust scoring options (each summarizing four to eight subtests) were sensitive to gifted and twice exceptional strengths. We found discrepant WISC-V primary index scores (≥1.5 SD differences) in a majority of our sample, undermining interpretability of Full Scale IQ scores for gifted identification. WISC-V mean scores ranged from very superior in untimed high-g Verbal Comprehension to average in low-g Processing Speed (irrelevant to gifted identification). A similar pattern emerged in our 2008 WISC-IV study of 334 gifted children. We show that the WISC-V performs effectively within multi-dimensional gifted and 2e identification approaches provided that the Full Scale IQ is not required. Instead, we demonstrate that any of six robust, high-g scores (ancillary and expanded indexes; FSIQ) may be used to document global strength or individual strength areas, satisfy gifted identification requirements, and guide advanced programming—even for 2e children, whose correspondingly low scores warrant further evaluation for co-existing weaknesses. We recommend best practices for use of these WISC-V scoring options for ethical identification of a broad, diverse range of gifted and 2e students, many of whom would be missed by averaging discrepant scores. Our study data prompted NAGC position statements on the WISC-V and WISC-IV.

Abstract Background Respiratory syncytial virus (RSV) causes annual outbreaks of respiratory illness with peak incidence occurring from late fall to early spring. While RSV is a leading cause of pediatric hospitalizations, it also poses a significant burden on older adults.Table 1.Cohort CharacteristicsTable 2.Multivariable-adjusted risk of supplemental oxygen, ICU needed, and stay length Methods We reviewed electronic medical records for hospitalized adults with laboratory-confirmed RSV between July 1, 2020, and June 30, 2024. Demographics, risk factors and outcomes were recorded. We created logistic and linear regression models to obtain multivariable-adjusted risks of supplemental oxygen needs, ICU level care, and increased length of stay (LOS). Results 371 patients met inclusion criteria. The cohort was predominantly older (≥65 years, 62%), White (60%), and female (57%), and were also in generally poor health (e.g., overweight BMIs, ∼50% current or former smokers, ∼50% with pulmonary or cardiovascular disease). Around one third required supplemental oxygen, 12% required ICU care and 2% died. The median LOS was 4 days, and both needing oxygen and ICU care associated with longer LOS (ps&amp;lt; 0.001). Multivariable-adjusted models suggested patients 85 years or older were at 160% higher risk to need supplemental oxygen; current smokers were at 140% higher risk, pulmonary patients 120%, and cardiac patients 70% (ps≤0.05); Hispanic or Latine patients were 60% at lower risk (p=0.04). Patients with pulmonary disease history had a 60% lower risk of needing ICU care (p=0.02). No demographic variables predicted LOS (ps &amp;gt;0.06). Conclusion We identified key demographic and clinical characteristics associated with greater illness severity of RSV, including the need for supplemental oxygen and ICU care. The roughly 1 in 3 requirements for supplemental oxygen, 12% ICU admission rate, and 2% in-hospital mortality highlight the considerable burden RSV imposes on hospitalized adults. Our findings suggest that elderly adults and those with underlying cardiopulmonary disease represent particularly high-risk groups for severe RSV manifestations. Current smokers and those over age 85 each had over twice the odds of requiring supplemental oxygen compared to younger patients and never-smokers. Protocols for RSV prevention—such as vaccination, early detection, and respiratory support may help optimize hospital outcomes. Disclosures All Authors: No reported disclosures

The rapid evolution of artificial intelligence (AI) has become one of the most transformative forces in the modern automotive landscape. Among the most significant beneficiaries of AI integration are electric vehicles (EVs), which rely on advanced software and intelligent systems far more heavily than traditional internal combustion engine vehicles. As the world embraces cleaner, smarter, and more sustainable transportation options, AI is driving a revolutionary shift in how electric cars are designed, operated, maintained, and experienced. From autonomous driving capabilities to intelligent energy management and predictive maintenance, AI is reshaping every aspect of the EV ecosystem. Autonomous Driving and Advanced Driver Assistance Systems (ADAS): One of the most prominent areas where AI is influencing electric vehicles is in the development of autonomous driving technologies. EVs serve as ideal platforms for autonomy due to their electronic architecture and digital-first design.

Engineering structures are susceptible to repeated impact loads. There has been little attention to the damage and structural characteristics of engineering structures subjected to multiple impacts. Repeated impact loading tests are performed on reinforced concrete (RC) beams to examine the cumulative damage effect on their dynamic characteristics. Changes in dynamic properties (frequency and damping ratio) are analyzed using the random decrement technique and the Hilbert–Huang transform (RDT-HHT) method. With the same cumulative impact energy, different distributions of multiple impact energy cause varying degrees of damage to RC beams. The bearing capacity of an RC beam with initial severe damage decreases further with subsequent impacts. The reduction in the first mode frequency of the RC beam gradually converges as the extent of damage increases. If a high-energy impact occurs first or if a single high-energy impact takes place, it leads to a more significant reduction in the first mode frequency under the same cumulative impact energy. The first mode damping ratio of impact-damaged RC beams increases with rising impact energy. However, if the impact energy is excessively high, causing wide cracks or severe concrete spalling, the energy dissipation capacity of the specimen is weakened, resulting in reduced damping of the RC beam.