Search Results (263)

How much a college education pays off varies widely from one student to the next, and that variation matters for admissions, financial aid, and mobility policy. Most estimates, however, report a single average return and treat each institution as an isolated row in a table, ignoring how schools relate to one another and how outcomes are distributed across demographic groups. We present FairEdu-GCT(Graph-Enhanced Causal Transformer), a framework that couples a heterogeneous graph encoder with a Transformer sequence model and an explicit fairness penalty. Institutions, geographic regions, and academic disciplines form a typed graph whose edges record graduate flows, spatial proximity, and disciplinary overlap. A Relational Graph Attention Network (R-GAT) turns this structure into institutional ecosystem embeddingsthat carry peer effects, regional labor-market signals, and the spread of institutional prestige, none of which survives in tabular representations. A Transformer then encodes each student’s educational history and merges it with the institutional embedding through a cross-modal attention bridge, and a counterfactual decoding head returns the full conditional earnings distribution under alternative institutional choices rather than a single point estimate. Because students are not randomly assigned to schools, we make no claim of strict causal identification; we treat CATE and PEHE strictly as estimation-quality diagnostics for a confounding-adjusted contrast, not as evidence of a proven causal effect. We instead adjust for observed confounders through a doubly robust objective and add an equalized opportunity regularizer so that accuracy does not come at the expense of protected subgroups. On linked U.S. College Scorecard, IPEDS, and NLSY97 data (6256 institutions drawn from 7312 Title IV schools; 161,043 person-institution-year records from 8984 respondents followed for ten years), FairEdu-GCT lowers RMSE by 16.2% and Precision in Estimation of Heterogeneous Effects (PEHE) by 25.1% against the strongest baseline (Causal Forest, DragonNet, TARNet, and TabTransformer), and shrinks the demographic parity gap by 46.5%. All gains are reported with 95% confidence intervals and effect sizes over ten seeds, and an extended fairness audit (calibration, predictive parity, and subgroup robustness) confirms the improvement is not confined to the two metrics we optimize. Ablations attribute a 9.0% RMSE reduction to the R-GAT encoder alone. A group-conditional SHAP analysis further shows that graph-derived proximity to regional technology clusters is an unusually strong predictor for first-generation minority students, a signal that tabular features cannot recover and one we read as a within-model association rather than a policy lever. Full article

Global oil and gas exploration and development are gradually expanding into deep and ultra-deep formations. Deep limestone exists in a long-term multi-field coupled environment featuring high temperature, high in situ stress and high pore pressure, which brings great challenges to reservoir stimulation and wellbore stability. To investigate the effects of confining pressure and pore pressure on limestone under high temperatures, triaxial compression tests were conducted on limestone at various temperatures (25~150 °C) using the GCTS RTR-2000 rock mechanics testing system. This paper investigates the evolution laws of strength and deformation parameters of limestone under varied temperature, confining pressure and pore pressure. The results indicate that: (1) Within the 25~150 °C range, the peak strength and elastic modulus of limestone exhibit a “decrease-then-increase” trend, with a strength rebound occurring at 150 °C driven by the “thermal expansion and compaction” effect. (2) Under a pore pressure of 50 MPa, temperature and confining pressure exert a significant coupled control effect on the mechanical properties of the rock, characterized by a critical confining pressure threshold of approximately 100–110 MPa. Below this threshold, high temperature acts as a weakening factor, whereas above it, high temperature acts as a strengthening factor and induces intense brittle failure under high pressure. (3) In the pore pressure coupling tests, the rock undergoes ductile failure as confining pressure increases at normal/room temperature, while a temperature of 100 °C strengthens the rock under high confining pressure. (4) Energy evolution analysis reveals that within the 75~125 °C range, the thermal pressurization of pore water and local thermal stresses induce massive microcracks, causing the dissipated energy to surge sharply to nearly 80%. The research findings provide a theoretical basis for wellbore stability analysis and fracturing parameter optimization in deep carbonate reservoirs. Full article

Background/Objectives: Accurate preoperative discrimination between benign and malignant testicular masses remains challenging. Lesion size has been suggested as a predictor, but robust cutoffs and the role of contralateral biopsy remain uncertain. Methods: We retrospectively analyzed a prospectively maintained single-center database of 387 patients treated for testicular lesions between December 2013 and November 2024. Patients with malignant non-germ cell histologies or prior systemic GCT therapy were excluded. Lesion size was evaluated as a predictor of malignancy using ROC analysis, logistic regression, and predefined cutoffs (5, 8, 10, 15 mm). Associations between contralateral biopsy results and clinical variables were assessed using uni- and multivariable analyses. Results: Of 387 patients, 284 (73.4%) had malignant GCTs. Malignant lesions were significantly larger than benign ones (median 25.0 vs. 5.5 mm, p < 0.001). Lesion size showed good discrimination between benign and malignant lesions (AUC 0.829, 95% CI 0.784–0.874), with a Youden-derived optimal cutoff of 12.5 mm. Internal bootstrap validation (2000 resamples) yielded a median optimal cutoff of 12.5 mm (95% percentile interval 7.45–19.5 mm), indicating uncertainty regarding the exact threshold. Among 360 patients with complete clinical and tumor-marker data, combining lesion size with age, AFP, β-HCG, and LDH significantly improved discrimination compared with lesion size alone (AUC 0.863 vs. 0.818; DeLong p = 0.003). Contralateral biopsy was performed in 249 patients, with 7 (2.8%) positive for GCNIS. Younger age was associated with contralateral GCNIS, while tumor size, serum markers, and histology were not predictive. Multivariable analysis showed no significant predictors. Conclusions: Lesion size is a strong predictor of malignant histology, although the optimal size threshold remains subject to uncertainty. Combining lesion size with readily available clinical and biochemical parameters may further improve preoperative risk stratification. Contralateral GCNIS was rare and not reliably predicted, supporting individualized biopsy strategies. Full article

Background: Influenza remains a significant global public health threat, causing substantial morbidity and mortality worldwide. While vaccination serves as the best preventive strategy, considerable interindividual variability in vaccine-induced immune responses persists. The ZBTB46 rs2281929 polymorphism (c.A31G; p.T11A; ACG>GCG), which corresponds to the evolutionarily conserved mouse mutation Zbtb46^T11A (c.A31G; ACT>GCT), has been associated with enhanced antibody responses to influenza vaccination in humans, though its functional mechanisms remain unknown. This study aimed to investigate how this mutation affects influenza vaccine immunogenicity using a knock-in mouse model. Methods: A Zbtb46^T11A knock-in mouse model was generated using CRISPR/Cas9 technology. Homozygous (HO) and wild-type (WT) mice were immunized with a quadrivalent influenza vaccine in a prime-boost regimen. Humoral immune responses were assessed by Enzyme-linked immunosorbent assay, hemagglutination inhibition (HI), and microneutralization (MN) assays. Antibody-secreting cells (ASCs) were quantified by Enzyme-linked immunospot assays. Germinal center B cells, plasma cells, plasmablast cells, conventional dendritic cell (cDC) subsets, and T helper (Th) cells were analyzed by flow cytometry. Statistical comparisons were performed using a two-sample t-test. Results: The Zbtb46^T11A mutation did not alter Zbtb46 protein expression or its abundance in cDCs. Following vaccination, HO mice exhibited significantly enhanced humoral responses, including higher HA-specific IgG titers, HI and MN antibody levels, and increased numbers of ASCs. Flow cytometry revealed elevated proportions of germinal center B cells and plasma cells in HO mice. Furthermore, HO mice showed a selective expansion of type 1 cDCs (cDC1s) and a concomitant increase in Th1 cell frequencies and IFN-γ-secreting cells, while cDC2 proportions and Th2 responses remained unchanged. Conclusions: The Zbtb46^T11A mutation is associated with enhanced influenza vaccine immunogenicity, concomitant with increased cDC1 proportions, Th1 polarization, and germinal center-dependent humoral immunity. These observed associations suggest a candidate mechanism whereby Zbtb46 modulation may shape adaptive immunity, though further functional studies are required to establish causality. These findings provide insights into host genetic variation in vaccine responsiveness and may inform personalized vaccination strategies. Full article

Of interest were the acute effects of lightweight lower-limb wearable resistance (WR) on the kinematics and kinetics of the countermovement jump (CMJ) and drop jump (DJ). Twenty male athletes (age: 18.05 ± 0.6 years; body mass: 76.4 ± 7.6 kg; height: 182.4 ± 5 cm) performed the CMJ and DJ under four loading conditions: 0%, 2%, 4%, and 6% body mass (BM). Variables of interest included jump height (JH), countermovement depth (CMD), total SSC duration (TCT/GCT), eccentric and concentric phase durations, relative concentric impulse (rCI), relative concentric mean force (rCMF), relative concentric mean power (rCMP), and concentric force index (CFI). Two-way repeated-measures ANOVAs were used to assess jump × load interactions, with Bonferroni-adjusted pairwise comparisons and planned contrasts used to examine within-jump and between-jump load responses, respectively. Significant jump × load interactions were observed for all variables analysed. In the CMJ, JH significantly decreased across all loaded conditions, including an 8.3% reduction with 2% BM. In contrast, DJ JH was preserved at 2% BM but significantly decreased at 4% and 6% BM. However, 2% BM was sufficient to increase DJ GCT and ConT, and reduce rCMF, CFI, and rCMP (p < 0.05). The change in JH differed between jumps at 2% BM only, whereas changes in CMD, rCMF, CFI, and rCMP differed between jumps across all WR loads. It appears that lightweight WR produces distinct jump-specific responses. Greater initial changes in CMJ JH and CMD suggest that WR altered countermovement strategy before substantially impairing concentric force production, whereas in the DJ, WR altered fast SSC force–time variables before reducing JH. When utilising WR to improve JH performance, practitioners should therefore avoid interpreting JH in isolation and monitor temporal variables (GCT/TCT/ConT/EccT), CMD, rCMF, rCMP and CFI. Full article

To alleviate renewable energy curtailment and the high operating costs arising from the temporal and spatial mismatch of distributed generation, this paper develops a cross-park dispatch optimization approach for power systems under the joint participation of carbon trading and green certificate trading (GCT). The proposed approach aims to improve system flexibility and economic performance in coordinated multi-park operation. Specifically, adjustable resources in different parks are dispatched in a coordinated manner, and the total comprehensive operating cost is taken as the optimization objective. In addition, the Alternating Direction Method of Multipliers (ADMM) is adopted to determine inter-park electricity trading prices and exchanged power in a distributed framework. Furthermore, an asymmetric bargaining model is introduced to distribute the cooperative benefits, ensuring a balance between fairness and incentive compatibility. Simulation results demonstrate that inter-park electricity interaction reduces generation costs by 5.29%. The integration of carbon and green certificate trading further reduces costs by 7.4%. After asymmetric bargaining-based benefit allocation, the operating costs of parks with higher contributions decrease by up to 10.34%. The results conclude that the proposed strategy effectively leverages the complementary advantages of multi-park resources and optimizes the synergy between carbon markets, green certificate markets, and physical dispatch. Full article

To address the challenges of restricted renewable energy accommodation, high carbon emissions, and elevated operating costs in integrated energy systems (IES), this paper proposes a stochastic optimization scheduling method that incorporates the synergy between carbon–green certificate trading and the multi-use applications of hydrogen energy. First, an integrated “electricity–carbon–hydrogen–methanol” model is constructed, incorporating proton exchange membrane (PEM) electrolyzers (ELs), methanol synthesis reactors, hydrogen storage systems, and hydrogen fuel cells (HFCs). Second, a concentrating solar power (CSP) plant coupled with an electric heater (EH) is integrated based on an “electricity–heat–electricity” mechanism. Concurrently, a joint carbon emission trading (CET) and green certificate trading (GCT) mechanism is incorporated into a low-carbon economic dispatch model to minimize total operational costs. On this basis, Information Gap Decision Theory (IGDT) is applied to address source–load uncertainties via risk-averse (RAS) and opportunity-seeking (OSS) strategies. Simulation results demonstrate that the proposed strategy achieves full accommodation of renewable energy. The EH-coupled CSP plant increases thermal output by 4.96%, reducing system carbon emissions by 8.07% compared with the non-EH scenario and decreasing natural gas procurement costs by 14.1%. Furthermore, the joint CET-GCT mechanism overcomes single-market limitations, increasing carbon trading revenues by 298.01% and lowering total operating costs by 39.6% compared with uncoordinated mechanisms. Finally, under IGDT uncertainty analysis, the opportunity-seeking strategy further reduces operating costs by 9.5% compared with the risk-averse strategy, enhancing the system’s low-carbon economic performance and operational flexibility. From the perspective of sustainable development, this study provides a practical dispatch framework for regional integrated energy systems to balance energy security, low-carbon transition and economic cost, offering methodological support for advancing the sustainable transformation of multi-energy systems amid the dual-carbon drive. Full article

Fish germline stem cells (GSCs) are pivotal mediators in the transmission of genetic information across generations, possessing irreplaceable significance in aquatic germplasm protection and genetic breeding. Stable in vitro culture serves as an essential prerequisite for construction of standardized fish GSC germplasm repositories. Only by developing a robust culture system to sustain long-term proliferation and stemness of GSCs can large-scale cell reserves be established and long-term safe preservation be realized, and relevant applications including germ cell transplantation (GCT), in vitro differentiation and gene editing be further supported. However, most existing studies focus merely on individual techniques or partial research modules, while few integrate GSC biological mechanisms, in vitro culture systems, and germplasm repository construction with downstream industrial applications. This review elaborates the biological characteristics and classification of fish GSCs, summarizes the regulatory mechanisms of GSC fate determination, and comprehensively updates the research progress of in vitro culture technology and germplasm repository development. Multiple application scenarios based on cell bank resources are holistically illustrated, and prevailing technical and industrial challenges are analyzed. The study aims to provide theoretical reference for promoting technological innovation and practical utilization of fish germ stem cell research. Full article

Background: High-dose chemotherapy (HDCT) followed by autologous stem cell transplantation (ASCT) is an established salvage therapy for relapsed or refractory (R/R) germ cell tumors (GCTs). Methods: We conducted a retrospective analysis of 9 patients (23–41 years of age) with relapsed/refractory (R/R) GCTs treated according to the Swedish–Norwegian Testicular Cancer Group Clinical Protocol (SWENOTECA), at the Specialized Hospital for Active Treatment of Hematological Diseases (SHATHD) in Sofia, Bulgaria. The study evaluates the efficacy and safety of HDCT followed by ASCT in R/R GCTs eligible for second-line consolidation. The cohort was predominantly high-risk, with 77.7% of patients exhibiting stable or progressive disease (SD/PD) after first-line platinum therapy. Response was assessed via RECIST 1.1 criteria and tumor marker monitoring. Results: Median OS and PFS were 8.4 and 5.9 months, respectively. While the ORR post-ASCT was 33.3% (all CR), the 2-year survival plateau (33.3%) suggests curative potential in a subset of patients. Notably, there was no treatment-related mortality (TRM). Conclusions: Tandem HDCT is a feasible salvage strategy with manageable toxicity and no TRM in this small, heavily pre-treated cohort. Although efficacy results are exploratory due to the limited number of patients, the observed long-term remissions confirm the curative potential of this standard-of-care consolidation in a real-world clinical setting. Full article

Accurate vessel trajectory prediction from Automatic Identification System (AIS) records is important for maritime traffic monitoring, route planning, and intelligent vessel traffic management. However, reliable prediction remains challenging for long forecasting horizons and turning maneuvers. To address this problem, this study proposes the Geometry-Consistent Trajectory Transformer (GCT-Former), a progressive and refinement-based framework for AIS-based vessel trajectory prediction. The proposed model integrates multi-scale historical trajectory encoding, progressive residual future-position generation, and global–local trajectory refinement to improve the stability and continuity of long-horizon trajectory prediction. The predicted trajectories are evaluated as geometric future-position estimates and can provide trajectory-level information for downstream maritime traffic monitoring and decision-support applications. Experiments are conducted on three real-world Danish maritime regions: Aarhus Bay, Great Belt, and Skagen. Compared with representative conventional and deep-learning trajectory prediction models, the proposed model shows its most consistent advantage in long-horizon prediction, particularly in terms of ADE and FDE. In the long-term setting, it achieves average displacement errors of 0.344, 0.546, and 0.218 km and final displacement errors of 0.774, 1.368, and 0.525 km on Aarhus Bay, Great Belt, and Skagen, respectively. The ablation analysis further shows that removing the multi-scale encoding module increases the long-term average displacement error by 7%, 4%, and 3%, while removing the progressive residual decoder leads to larger increases of 15%, 9%, and 8% on the three datasets. The turning-maneuver analysis also shows lower geometric prediction errors under mild-turning and sharp-turning scenarios. These results indicate that GCT-Former improves AIS-based vessel trajectory prediction, especially for long-horizon and maneuvering cases. Full article

Background/Objectives: Germ cell tumors (GCTs) are thought to arise from primordial germ cells that fail to appropriately differentiate and instead retain pluripotency programs. PRDM14 is a key regulator of pluripotency and primordial germ cell specification and is aberrantly expressed in multiple GCT subtypes. However, the role of PRDM14 in GCT malignancy remains unclear. In this study, we investigated whether PRDM14 functions in GCTs through CBFA2T2, a transcriptional corepressor previously identified as a PRDM14-interacting partner in pluripotent stem cells and developmental models. Methods: To determine the presence and level of PRDM14 and CBFA2T2 in GCT, a panel of GCT lines were assessed for RNA and protein expression and interaction. Then, to better understand the biological effects of PRDM14 and CBFA2T2 within GCTs, PRDM14 and CBFA2T2 knockdowns were employed. Results: We show that PRDM14 and CBFA2T2 are expressed across GCT cell lines, colocalize predominantly in the nucleus, and cooperate as a complex in GCT cell lines. Knockdown of either PRDM14 or CBFA2T2 resulted in reduced expression of key pluripotency genes and a significant impairment of cell proliferation, indicating a shared role in maintaining an undifferentiated, proliferative state. Transcriptomic analysis following PRDM14 or CBFA2T2 depletion revealed extensive overlap in differentially expressed genes and convergent alterations in developmental and metabolic signaling pathways. Conclusions: Together, these findings suggest that PRDM14 and CBFA2T2 form a functional complex that sustains pluripotency and proliferation in GCT cells. This supports a model in which persistence of germline regulatory mechanisms contributes to GCT malignancy, highlighting this interaction as a novel component of GCT biology. Full article

Accurate, non-invasive body weight estimation is essential for management and performance monitoring in beef cattle systems, yet conventional scales and manual measurements require animal handling, infrastructure, and labor. This study presents an integrated pipeline that segments cattle from overhead depth images and predicts body weight from extracted image features. The approach uses a Light Attention Encoder–Decoder (LAED) segmentation model combining depthwise separable convolutions, Gaussian Context Transformer (GCT) attention, a multi-scale dilated bottleneck, and dual heads for region and boundary prediction. Depth videos were collected using an overhead Intel RealSense D435 RGB-D camera from 60 beef heifers. To reduce animal-level leakage, leave-one-animal-out cross-validation was used for segmentation. LAED + GCT achieved 96.91% Dice (95% confidence interval (CI): 96.56–97.21%) and 94.22% IoU (95% CI: 93.58–94.77%), while operating at 33.08 frames per second. For weight prediction, biometric traits and deep features were evaluated using random forest, support vector regression, and fully connected neural networks. The best primary-metric body-weight model used biometric traits with support vector regression, achieving MAPE = 6.75%, pooled $R^2$ = 0.68, MAE = 23.92 kg, and RMSE = 31.79 kg. Among FCNN models trained independently within each cattle-level fold, the best result used ResNet50 features and achieved MAPE = 7.76%, a pooled $R^2$ = 0.56, an MAE = 27.60 kg, and an RMSE = 37.07 kg. The mean signed prediction bias for the biometric-SVR model was −1.04 kg, using predicted minus observed body weight, with a bootstrap 95% confidence interval of −9.63 to 7.41 kg. These results support the promise of overhead depth imaging for non-invasive cattle body segmentation and weight estimation, while larger external validation remains necessary. Full article

This article presents a practical framework for implementing, collecting, and interpreting inertial measurement unit (IMU) foot pod data to improve diagnostic understanding of baseball base running mechanics. Linear sprinting is used as a baseline, whereas the home-to-second-base sprint trial is used to examine how that capacity is expressed when athletes negotiate curvilinear running demands. The purpose is not to establish generalized performance outcomes, but to illustrate how IMU-derived spatiotemporal variables may be interpreted across successive base running segments in applied settings. Three competitive baseball players were selected from a larger dataset of n = 54 base runners tested using the same protocol with distinct home-to-second-base performance profiles as follows: the fastest case (Player X), an intermediate case (Player Y), and the slowest case (Player Z) were selected based on total home-to-second-base time. The cases were selected purposively to demonstrate the application of the IMU interpretation framework, including ground contact time (GCT), stride length (SL), push-off acceleration, and impact acceleration. Particular emphasis is placed on how curvilinear demands alter inside- and outside-foot function, and how segment-to-segment comparisons may help practitioners identify phases in which base runners maintain, reorganize, or lose mechanical efficiency. Compared with broader velocity-based approaches, the IMU framework provides complementary step-level information that may help practitioners generate hypotheses about how base runners organize movement across linear and curvilinear segments. These examples are intended to demonstrate a workflow for applied interpretation rather than to establish causal mechanisms. As a result, IMU foot pod analysis may offer practitioners a structured and portable method for interpreting curvilinear sprint mechanics, yet these case examples should be understood as descriptive rather than prescriptive. Full article

Dam seepage is a critical issue affecting the safe operation of reservoir dams, making the monitoring and early warning of abnormal seepage conditions particularly important. Currently, analyses of dam seepage primarily focus on using finite element methods to invert seepage conditions and employ regression analysis and classical machine learning methods to predict seepage. However, there has been limited analysis of the relationships among various influencing factors. The subjectivity of input factors in seepage safety monitoring models, the imprecision of factor relationships, and the randomness of parameter selection can all lead to uncertainty in model predictions. Therefore, to identify the primary factors influencing reservoir seepage issues, we took a specific reservoir project as an example and employed stepwise regression analysis and Granger causality tests to comprehensively examine the relationships between reservoir water level, rainfall, seepage pressure at various locations, and seepage pressure around the dam. Based on this analysis, the key influencing factors for seepage pressure around the dam were identified. The results indicate that reservoir water level and seepage pressure influence the seepage pressure around the dam. The stepwise regression method can comprehensively screen for potential influencing factors. Meanwhile, GCT utilizes time lag characteristics to further narrow the range of influencing factors. These two methods significantly narrow the scope of screening for factors affecting seepage pressure around the dam. These two methods can be used to narrow down the range of factors influencing seepage pressure around the dam, reduce interference from these factors, scientifically eliminate spurious correlations and redundant variables, and efficiently and reliably detect and provide early warnings of abnormal dam seepage. Full article

Objective: To examine lower-body stretch–shortening cycle (SSC) indicators across chronological age categories and playing positions in elite male youth soccer players. Methods: In a cross-sectional design, 984 male players from Slovakia (U15–U19) completed Squat Jumps (SJ), Countermovement Jumps (CMJ), and Drop Jumps (DJ) using the OptoJump photocell system. Outcomes included Eccentric Utilization Ratio (EUR), Reactive Strength Index (RSI), DJ Ground Contact Time (DJ GCT), and Jump Heights (JH). Differences were tested using factorial ANCOVA (age category × playing position) adjusted for height and weight, followed by Tukey-adjusted post hoc comparisons (p < 0.05). Results: Significant age-category main effects were observed for DJ RSI, DJ JH, CMJ JH, SJ JH, and DJ GCT. The largest effects were for DJ JH, CMJ JH, and SJ JH (ηp² = 0.096–0.112), whereas the DJ GCT effect was statistically significant but small (ηp² = 0.013). EUR showed no significant differences across age categories (p = 0.586). Positional differences were limited overall and mainly evident in selected U19 outcomes, particularly jump-height variables and DJ GCT. Conclusions: Lower-body SSC performance increased across chronological age categories, with the largest separation in jump-height and reactive strength outcomes. These differences likely reflect a combination of maturation, training exposure, and selection rather than chronological age alone. EUR remained stable across age categories and playing positions, although the JH-based ratio has limited sensitivity in the present test configuration. Positional separation emerged mainly at U19, supporting broad SSC development across earlier youth categories and position-sensitive interpretation in the oldest cohort. Full article