Advancing Open Science

Background: Human milk-derived fortifiers (HumBMF) are an alternative to bovine protein-based fortifiers (BovBMF) for preterm infants, but their comparative effectiveness and safety remain uncertain. We evaluated the effects of HumBMF versus BovBMF in preterm or very low birth weight infants. Methods: Randomised controlled trials (RCTs) comparing use of HumBMF versus BovBMF to fortify human milk were identified through four databases and three trial registries (to 11 May 2026). At least two reviewers independently screened studies, extracted data, and assessed risk of bias. Fixed-effect meta-analyses and GRADE assessments were performed. Prespecified analyses separated trials comparing fortifier type alone, in which any mother’s own milk (MOM) shortfall was supplemented with donor human milk (DHM) in both arms; and dual-intervention trials, in which MOM shortfall was also randomised to DHM in the HumBMF arm or preterm formula in the BovBMF arm. Results: Nine RCTs were included. In trials comparing fortifier type alone, there was no evidence that HumBMF reduced mortality (RR 0.60 (95% CI 0.29–1.23), low-certainty) or necrotising enterocolitis (NEC; RR 0.83 (0.39–1.78), very low-certainty). In dual-intervention trials, where MOM shortfall was supplemented with DHM rather than formula, NEC was lower (RR 0.45 (0.20–0.99), moderate-certainty). Conclusions: Current evidence does not demonstrate clinical advantages of HumBMF over BovBMF when added to the same human milk diet. Reductions in NEC occurred only where DHM also replaced preterm formula and cannot be attributed to fortifier type alone. Future research should distinguish the independent effects of fortifier composition from those of an exclusive human milk feeding strategy.

Water resources carrying capacity (WRCC) includes the relationships between water resources utilizations and economic development, social demand, and ecological protection. Most previous studies lack WRCC analyses of regions experiencing economic development and industrial development. Therefore, this study takes Jiangsu Province in China as a typical case which includes 13 prefecture-level cities from 2012 to 2021. To provide a comprehensive and nuanced assessment, this study proposes an integrated analytical paradigm for WRCC that explicitly incorporates system coordination, dynamic drivers, and spatiotemporal evolution. First, the entropy-weighted Chebyshev–TOPSIS method is applied to calculate WRCC. Second, the coupling coordination degree model (CCD) is introduced to assess coordination among the four subsystems. Third, the Panel Vector Autoregression model (PVAR) is used to examine dynamic interactions. Fourth, the geographically and temporally weighted regression model (GTWR) is considered to identify spatiotemporal trends with a certain degree of endogeneity. The results indicate that WRCC generally improved across Jiangsu Province over the study period, although marked differences persist among its 13 prefecture-level cities. Suzhou and Nanjing presented relatively high WRCC levels, whereas Huai’an and Suqian showed weaker coordination. The economic subsystem is strongly constrained by water resources and ecological conditions. The impact of the ecological environment on WRCC continues to intensify, which indicates its increasing role in regional water resource management. These findings show that WRCC is jointly shaped by interactions among subsystems and by drivers that vary across space and time. The proposed framework can support water allocation, ecological protection, and development planning tailored to the conditions of individual cities.

This study presents a structured evaluation of key factors influencing the design of shallow geothermal (SG) hybrid heating and cooling systems in the Danube Region. As part of the Danube GeoHeCo project, a criteria catalogue was developed using the Analytic Hierarchy Process (AHP) to support the creation of an IT decision support tool. Through expert-based pairwise comparisons and eigenvalue analysis, the relative weights of technical, geological, socioeconomic, and environmental criteria were derived. Results show that thermal demand, drilling costs, and hydrogeological site characteristics are the most influential parameters. The final ranked list of twenty sub-criteria provides a basis for prioritizing input data and optimizing early-stage system design. This framework supports more efficient project planning, targeted data collection, and the development of robust shallow geothermal hybrid solutions aligned with regional energy transition goals.

Optimizing the morphology and structure of noble metal nanomaterials is critical for the design of high-performance surface-enhanced Raman scattering (SERS) substrates for trace analyte detection. A plasmon-tunable SERS platform consisting of AuAg alloy nanostars anchored on a hydrophobic polydimethylsiloxane (PDMS) matrix was developed, which combined the chemical stability of Au and the strong localized surface plasmon resonance of Ag. AuAg alloy nanostars with sharp tips were synthesized via a galvanic replacement reaction, in which the precise modulation of Ag seed concentration enabled a morphological evolution from solid to hollow nanostructures. The optimized AuAg-3 nanostars exhibited the highest SERS response due to a dual synergistic mechanism: strong electromagnetic enhancement at the sharp branched tips and additional plasmonic enhancement from the hollow cavity through light scattering and trapping, which increased the optical path length and excitation efficiency. Furthermore, these nanostars were transferred onto a flexible PDMS film through interfacial self-assembly. The resulting hydrophobic PDMS-AuAg-3 substrate synergistically combined the strong electromagnetic enhancement from the nanostars with efficient analyte enrichment driven by the hydrophobic surface, achieving an ultra-low detection limit of 2.4 × 10⁻¹⁰ M for methylene blue (MB). This strategy effectively balances high sensitivity and excellent reproducibility, offering a robust pathway for the development of next-generation flexible SERS sensors.

Distribution-shift alarms do not establish classifier harm. We evaluated the detectability, frozen-head relevance, and performance deterioration of two public DenseNet-121 chest-radiography classifiers under 30 controlled image conditions. Signals covered pixels, 64-component PCA representations, logits, probabilities, and calibrated high-error selection. An exact whole-model-null intervention changed representations while preserving all 18 released output slots to within 4.09 × 10⁻¹⁴; PCA monitoring detected all six interventions, five-logit monitoring detected none, and the paired Brier change was negligible. Across image shifts, PCA and logit alarm rates were 97% and 52%. In held-source/held-family prediction of primary Brier harm, probability mean displacement had the lowest error (MAE 0.00679); neither PCA signal outperformed the training-mean baseline after correction, whereas three output-facing signals beat both prespecified baselines. Secondary results were outcome-dependent: PCA RFF-MMD ranked best for macro-AUC and locked-F1 loss. An exploratory ConvNeXtV2-Atto/MobileViT-XS arm reproduced the construct separation: representation monitoring detected 57/60 conditions and all six task-null controls, while logit monitoring detected no task-null control; probability mean had the lowest held-architecture/held-family Brier-harm error ratio (0.404). The results show that detectability, task relevance, and metric-specific harm are distinct constructs and should be reported separately.

Alignments explain deviations between an event trace and a process model, but difficult traces can make exact computation slow. This paper studies whether one pretrained neural scorer can be reused to propose alignments for different Petri nets and activity vocabularies. LARA (Learned Alignment with Replay Assurance) encodes the Petri net and the complete trace, scores possible moves, and constructs a candidate using a decoder that tracks the marking. Independent replay checks executability and computes the candidate cost. Optional exact search establishes optimality or supplies a replacement. We explain the neural machinery, synthetic training procedure, and verification contract. Across three training seeds, greedy decoding produces 90.8% optimal candidates on the 512-row synthetic test set (sample standard deviation: 0.3 percentage points), which can be compared with 86.9% without guidance. All candidates pass replay. An optional single-log repair procedure raises the reference checkpoint’s rate from 91.0% to 97.3%. The largest learned benefit concerns duplicate activity labels. Tests exclude training-isomorphic graphs, include cyclic structures, and evaluate held-out cases from three public logs. They reveal inconsistent structural gains and no real-log quality advantage from learned rankings. Common-boundary timings compare per-trace methods, while established approximations remain stronger than the greedy candidate policy. Certified mode runs exact search on every trace. The results support a limited role for reusable scoring, with guarantees supplied by process semantics.

The study examines the evolution of financial system structural orientation as a variable reflecting the relative weight of bank credit and market capitalization. The study aims to assess the long-term evolution of financial system structural orientation, its convergence patterns, and its response to major economic shocks. The empirical analysis covers 20 countries over the period 2001–2024. The study combines an analysis of cross-country differences and the temporal variability of structural orientation with β- and σ-convergence tests, complemented by an analysis of structural deviations and post-shock adjustment during the 2008 financial crisis and the COVID-19 pandemic. The results reveal substantial heterogeneity in the structural trajectories of financial systems and differences in the stability of these trajectories. At the same time, a tendency toward convergence in structural orientation is observed in the absence of statistically significant evidence of a reduction in cross-country dispersion. The shock analysis demonstrates differences not only in the magnitude of structural changes but also in post-shock adjustment and recovery. The findings contribute to a dynamic understanding of the relationship between the banking and market-based components of financial systems and support the need to assess this relationship beyond the boundaries of static country classification.

We aimed to investigate the acute anticonvulsant and long-term antiepileptogenic effects of the synthetic triterpenoid CDDO-EA in complementary experimental models of epilepsy. CDDO-EA was evaluated in the pentylenetetrazol seizure model and a kainic acid-induced post-status epilepticus model. Acute seizure severity, latency to generalized seizures, oxidative stress and inflammatory markers, spontaneous recurrent seizures, and hippocampal neuronal survival were assessed. In the pentylenetetrazol model, CDDO-EA pretreatment reduced maximal seizure severity and prolonged the latency to stage V-VI seizures. These effects were associated with decreased inflammatory cytokine levels and malondialdehyde levels, alongside increased superoxide dismutase and catalase activities 24 h after pentylenetetrazol administration. In the post-status epilepticus model, two weeks of CDDO-EA treatment significantly delayed the onset of spontaneous recurrent seizures and produced sustained reductions in weekly seizure frequency and cumulative seizure burden. Histological analysis demonstrated greater neuronal preservation in the hippocampal CA1 and CA3 regions of CDDO-EA-treated animals compared with vehicle controls. CDDO-EA exerts both anticonvulsant and disease-modifying effects by attenuating seizure severity, restoring redox-inflammatory homeostasis, preserving hippocampal neurons, and suppressing epileptogenesis after status epilepticus, supporting its therapeutic potential as a novel strategy for epilepsy.