Abstract: Background/Objectives: The Human Performance Envelope (HPE) is a multidimen-sional model that represents the range in which an individual operator's performance is acceptable or begins to become dangerous. Although several alternative models have been proposed, HPE currently remains primarily a theoretical concept. The goal of the study was therefore to translate this theoretical concept into practical applications, seeking to characterise and measure how HPE manifests itself in real-world contexts. Methods: Multivariate Autoregressive Models (MVAR) have been used in the analysis of complex systems in which variables are interdependent and mutually influence their dynamics over time. Professional Air Traffic Controllers (ATCOs) were involved in the study and asked to deal with realistic traffic scenarios while their behavioural, subjec-tive and neurophysiological data were collected. Partial Information Decomposition - Least Absolute Shrinkage and Selection Operator (PID – LASSO) model was then em-ployed to estimate the interactions among ATCO’s Human Factors (HFs) and identify the most appropriate characterisation of the HPE. Results: The results showed high and significant correlations among each ATCO’s performance and the corresponding neu-rophysiological – based HPE values. Furthermore, high-performance conditions (Best) were characterized by a significantly higher HPE values and a higher inter-HFs con-nections compared to low-performance (Worst) states. This suggested that a densely interconnected network of HFs is a prerequisite for operational resilience. Conclusions: The study provides the first application of a neurophysiological framework to model the causal interactions between HFs, translating the theoretical HPE into a quantifiable model validated against operator performance.

Abstract: This paper presents a nonlinear time-history re-assessment of an existing reinforced concrete (RC) frame building designed in 2007 according to the Romanian seismic code P100-1/2006 and re-checked against current seismic demand. Two three-dimensional solid finite-element models were developed in ANSYS: a bare RC frame and an RC frame with masonry infill panels. A distinctive feature is the explicit representation of longitudinal and transverse reinforcement embedded in the concrete solids, enabling direct tracking of steel stress demand and post-cracking load transfer. The models were subjected to bidirectional ground motions from the Vrancea 1977 and 1990 earthquakes and the Türkiye 2023 earthquake, scaled to match the P100-1/2013 target spectrum for the investigated site (a_g=0.40g). Modal analysis shows a clear stiffness increase due to infills, with the fundamental frequency rising from 4.4669 Hz (RC) to 5.8680 Hz (RC+M). Under the scaled records, infills substantially reduce global deformation demand: peak roof displacements in the transversal direction decrease from 9.87–14.26 mm (RC) to 2.74–3.38 mm (RC+M), and peak interstorey drift increments decrease from 3.35–4.94 mm to 0.92–1.16 mm, with drift ratios remaining well below conservative serviceability thresholds. Roof peak accelerations also decrease, reaching 0.490 g for RC versus 0.211 g for RC+M in the governing VN90 case. Base-reaction resultants and F_y–roof displacement loops confirm a stiffer global response with reduced displacement excursions for the infilled configuration. Local fields indicate that, in the bare frame, plastic strain concentrates at perimeter column bases and beam ends, while in the infilled model inelastic indicators shift toward masonry discontinuities around openings and panel corners; reinforcement demand peaks at beam ends, column bases, and the staircase region, consistent with torsional participation. The results highlight that masonry infills can strongly govern stiffness and drift demand at current design-level intensity, while introducing localised concentration zones that are relevant for performance assessment of existing buildings.

Abstract: Do humans and artificial intelligence systems apply consistent ethical frameworks when making organizational decisions, or do morally contested contextual features systematically influence moral judgments? We conducted a mixed-methods experiment with 300 organizational leaders and three frontier AI models (GPT-4, Claude 3 Opus, Gemini Pro 1.5) responding to 240 systematically varied ethical scenarios. We collected 6,000 human responses (300 participants × 20 scenarios each) and generated 7,200 AI responses at temperature 0.7 (240 scenarios × 3 models × 10 repetitions), with additional sensitivity analyses at temperatures 0.3, 0.5, and 1.0.Analysis revealed substantial systematic variation in moral judgments: both humans and AI systems (at temperature=0.7, selected post-hoc to match human total variation levels) made different recommendations for structurally identical dilemmas based on how stakeholders were described (identifiable individuals vs. statistical aggregates: OR=2.08, p<.001), whether actions were framed as active causation versus passive allowance (d=0.63, p<.001), and temporal proximity of consequences (OR=1.52, p<.001).We decomposed this variation into three components: (1) structural consistency (agreement when only irrelevant features vary: M=0.85), (2) contextual responsiveness (variation attributable to debatable features: 22-24% of total variance), and (3) arbitrary residual variation (32-34% of variance). AI temperature parameter directly controls variation magnitude: at T=0.3, AI showed less variation than humans (0.26 vs. 0.42, p<.001); at T=0.7 (typical deployment setting), AI approximated human levels (0.41 vs. 0.42, p=.56); at T=1.0, AI exceeded human variation (0.49 vs. 0.42, p<.001) but with degraded coherence (91.6% vs. 97.2% at T=0.7). This temperature-dependence means we cannot claim AI inherently exhibits human-like variation; rather, temperature embeds implicit assumptions about desired reasoning patterns. Critically, contextual feature effects (identifiability, relational, temporal, action-omission) remained significant across all temperatures (all η²p > 0.08, p<.001), indicating robust patterns independent of overall variation levels.Humans exhibited more relational reasoning than AI (d=0.56, p<.001). Mediation analysis on a coded subsample of 800 responses revealed that relational reasoning partially explained contextual responsiveness differences (indirect effect β=0.043, 95% CI [0.028, 0.061]), accounting for 69% of human-AI differences. Critically, relational reasoning was associated with higher contextual responsiveness but lower arbitrary variation, suggesting systematic sensitivity rather than random inconsistency.Whether contextual responsiveness represents cognitive bias or appropriate moral sensitivity remains philosophically contested. Principlism interprets our findings as evidence of widespread moral reasoning failures; particularism interprets identical patterns as appropriate attention to morally relevant contextual details. Our data provide empirical constraints for this normative debate but cannot adjudicate it.

Abstract: Codon optimization is a cornerstone technique in synthetic biology and biotechnological production, aimed at enhancing heterologous protein expression through synonymous codon substitutions. While optimization traditionally focuses on forward-strand translation efficiency, its impact on the complementary DNA strand is not always examined carefully enough. In this study, we investigate whether codon optimization inadvertently introduces antisense motifs, specifically bacterial antisense promoter (e.g., ‘TATAAT’), and whether such motifs can be silently injected into coding sequences on purpose without altering protein output. We developed a computational pipeline that (i) scans optimized sequences for antisense motifs, unintended; (ii) implements a silent injection algorithm that preserves amino acid sequence; and (iii) evaluates injection feasibility across a large genomic dataset. In a dataset of 484,741 protein-coding sequences, only 4.8 % naturally contained the motif, yet 77.28 % of motif-free sequences permitted silent injections. We extend these findings with codon bias analysis, derive analytical bounds for injection complexity, and propose computational defenses. These results uncover a novel cyber-biosecurity vulnerability in DNA design pipelines, emphasizing the need for bi-directional screening in codon optimization tools.

Abstract: Background/Objectives: Our study aims to identify potential new MRI features of brain metastases (BMs) that could be further used in overall survival (OS) assessment. Methods: A total of 109 patients with BMs were included. Kaplan-Meier analysis, the log-rank test, and Cox regression were implemented in the survival analysis. Signifi-cant features were subsequently incorporated into four distinct machine learning (ML) algorithms to predict six-month survival. Results: Survival analysis revealed that multiple brain lesions, synchronous presentation, and restricted diffusion were associ-ated with a poor prognostic value (HR > 1; p = 0.01, p = 0.02, and p < 0.005, respective-ly). Other features demonstrated a protective effect OS: the absence of extracranial le-sions (HR < 1, p = 0.04), and the presence of peripheral edema and solid enhancement (HR < 1, p < 0.0005). All treatment protocols—including surgery, gamma knife radio-surgery, whole brain radiation therapy, and chemotherapy - showed significantly bet-ter survival rates compared to best supportive care (HR < 1, p < 0.005). The Neural Networks was the top-performing ML model, achieving an AUC of 0.93. According to the Shapley Additive Explanations analysis, solid enhancement and radiotherapy had a positive impact on OS, whereas a higher number of lesions, larger volumes, and re-stricted diffusion were associated with negative outcomes. Conclusions: Our results confirm that including morphological MRI features of BMs in the prediction of OS sig-nificantly contributes to the enhancement of ML algorithms prediction and discrimi-natory capacity.

Abstract: Background/Objectives: Peristomal skin complications are common among individuals with a stoma and are associated with decreased quality of life, increased healthcare costs, social isolation, and various other challenges. However, these complications can often be prevented through appropriate care, patient education, counseling, and follow-up. This quasi-experimental study aimed to evaluate the effectiveness of education based on Orem’s Self-Care Deficit Nursing Theory (SCDNT) in preventing peristomal skin complications. Methods: The study sample included 45 patients with newly formed stomas, divided into an experimental group (n=24) and a control group (n=21). Data were collected using the Patient Characteristics Form, Self-Care Agency Scale (SCAS), Stoma Quality of Life Scale (SQOL), Patient Outcomes Evaluation Form, and Patient Opinions Questionnaire. The experimental group received education and counseling structured according to the components of SCDNT. Patient care, education, and follow-up were carried out in alignment with this framework. Results: Among the participants, 73.3% had undergone stoma surgery due to cancer, and 53.3% had an ileostomy. Peristomal skin complications were observed in 54.2% of patients in the experimental group and 95.2% in the control group (p<0.05). The most frequently reported complications were irritant dermatitis (71.4%) and hyperplasia (22.7%). The average complication recovery time was significantly shorter in the experimental group (21 ± 12.95 days) compared to the control group (44.65 ± 23.56 days) (p<0.05). Conclusions: Education, counseling, and follow-up based on SCDNT were effective in reducing both the incidence and duration of peristomal skin complications and enhancing patient engagement in self-care.

Abstract: Quantitative structure–activity/property relationship (QSAR/QSPR) is a well-established methodology widely used to model molecular properties based on structure, and is applied in fields such as drug design and environmental protection. The knowledge and procedures developed and used in QSPR modelling will be applied to the validation of protein folding rate models. Understanding the protein folding process is considered one of the most important scientific topics, and identifying the fundamental factors responsible for protein folding has been the subject of intensive research over the past 30 years [1]. Among the structural descriptors determining the protein folding rate, the length of the protein sequence, the content of regular secondary structures, and the average contact row distance between amino acids in the 3D structure are the most important. Comparative studies of different methods for predicting protein folding rates are occasionally published, and we conducted one such study. We found that the experimental data in literature databases and the data available online are inconsistent and scattered. This is partly due to differences in experimental data and protein sequence lengths, but more so due to the questionable quality of the models themselves. We observed very large deviations in the predictions of ln(kf) by some of the analysed models implemented as web servers. The root mean square errors (RMSEs) of some of the analysed models in predicting ln(kf) for a new external set of proteins are much larger than the RMSEs obtained for the same models on the training sets. External validation demonstrates that protein folding rate models available on web servers have accuracy for external protein sets comparable to that of a simple model based solely on the logarithm of protein chain length. This finding, which highlights the importance of external model validation as recommended by the OECD guidelines for QSAR validation, is fundamental and offers a new perspective for improving protein folding rate models by applying the knowledge and procedures used in the QSPR methodology.

Abstract: Introduction This study examines spatiotemporal trends in premature mortality across Mississippi’s 82 counties (2015–2025) using Years of Potential Life Lost (YPLL) before age 75. Methods County-level YPLL rates were drawn from County Health Rankings & Roadmaps (2015–2025 releases; underlying deaths ≈2012–2023). Trends were compared with U.S. averages, stratified by education, income, and insurance status, mapped via GIS, analyzed for spatial clustering with LISA, and modeled using spatial lag panel regression with year fixed effects. Results Mississippi’s YPLL rate rose 35.2% (10,918 to 14,764 per 100,000), far outpacing national trends and widening the state–U.S. gap by ~50%. Contrary to expectation, the largest increases occurred in high-education, high-income, low-uninsured (mostly urban/coastal) counties. High-High clusters intensified in the rural Delta/River counties, while Low-Low clusters vanished from urban and coastal areas. Spatial lag models showed strong spatial dependence (ρ ≈ 0.32); injury deaths (β = 58.2, p < .001), percent non-Hispanic Black, and paradoxically higher median income were key drivers. Conclusion Mississippi’s premature mortality crisis has shifted: rural burdens persist, but rapid deterioration in urban and more affluent counties now drives statewide worsening. Effective policy requires sustained rural investment in chronic disease control alongside urgent urban-focused interventions targeting injury and violence prevention, trauma systems, and mental health/substance-use services.

Abstract: Lokoja, the capital of Kogi State, Nigeria, is a rapidly growing mid-sized city located at the confluence of the Niger and Benue Rivers. While this location has driven urban expansion, it has simultaneously increased the city’s exposure to environmental risks, particularly flooding and ecosystem degradation. Despite their growing importance, cities of this scale remain underrepresented in African urban research. Using multi-decadal Landsat imagery (2000, 2010, 2020, and 2024), Random Forest supervised classification, and PyLandStats landscape metrics, this study examines the spatio-temporal dynamics of urban growth and landscape fragmentation in Lokoja. Results reveal a non-linear urban trajectory characterized by rapid expansion (2000–2010), partial consolidation (2010–2020), and renewed densification with intensified fragmentation (2020–2024). Urban land cover expanded from 6,668 ha in 2000 to 19,371 ha in 2010, declined to 12,883 ha in 2020, and increased again to 15,985 ha by 2024, representing a net growth of approximately 140%. Urban expansion has imposed severe ecological costs. Dense forest cover declined by 99.7% (from 373 ha to 1 ha), while woodland areas were reduced by 73.9%. Core habitat declined from 23% to 13.8% of the landscape, falling below the 15–20% threshold associated with ecological functionality. Edge density increased by 121%, amplifying urban heat island effects, surface runoff, and biodiversity loss. Although grassland cover increased by 77.1%, this reflects secondary succession rather than ecological recovery, given an estimated loss of 3,000 ha of original vegetation. The study recommends enforcing development restrictions below 10 m elevation with 100 m riparian buffers, restoring 500 ha of native riparian corridors, mandating a minimum of 20% urban tree canopy cover, and institutionalizing community-based monitoring of green spaces. These findings contribute empirical evidence on the sustainability challenges of mid-sized African cities and offer transferable planning strategies for ecologically sensitive urban regions.

Abstract: Various sight-threatening diseases are caused by an elevated permeability of the layer of retinal microvascular endothelial cells (REC), induced by high intravitreal levels of vascular endothelial growth factor-A₁₆₅ (VEGF-A₁₆₅). Barrier impairment is accompanied by an altered expression of proteins restricting para- and transcellular flow, counteracted by inhibition of VEGF-A-signaling. Here we investigated whether chloroquine, an inhibitor of lysosome acidification and autophagy, can prevent VEGF-A₁₆₅-induced impairment of the REC barrier. Cells were treated with 1-10 µM chloroquine ± 1.3 nM VEGF-A₁₆₅ for up to four days. Barrier function was assessed by continuous cell index measurements revealing that 10 µM chloroquine partly counteracted the VEGF-A₁₆₅-induced low cell index. Higher protein expression of the regulator of transcellular flow, plasmalemma vesicle-associated protein was also prevented, but not loss of tight junction protein claudin-1. Chloroquine in combination with VEGF-A₁₆₅ also lowered the protein expression of differentiation markers von Willebrand factor and caveolin-1, while the abundance of a cleavage product derived from adherens junction protein vascular endothelial cadherin increased. Importantly, the prominent localization of tight junction protein claudin-5 at the plasma membrane dramatically weakened, as shown by immunofluorescence staining. Taken together, despite apparently stabilizing the barrier formed by REC, chloroquine profoundly alters the endothelial phenotype.

Abstract: Background: Children with β-thalassemia major (β-TM) survive longer due to advances in transfusion and chelation therapy; however, cardiovascular complications have emerged as a leading cause of long-term morbidity. Chronic hemolysis, oxidative stress, and iron overload may promote early endothelial dysfunction and premature vascular aging, yet their impact on myocardial deformation in pediatric patients remains incompletely characterized. Objectives: To evaluate subclinical myocardial dysfunction and arterial stiffness in children with β-TM and to investigate hemolysis-related changes in asymmetric dimethylarginine (ADMA) and L-arginine as biomarkers of endothelial dysfunction in relation to cardiovascular involvement. Methods: Twenty-four children with β-TM and 20 age-matched healthy controls were included. Cardiac structure and myocardial deformation were assessed by conventional echocardiography, tissue Doppler imaging, and speckle-tracking strain analysis. Arterial stiffness was evaluated using oscillometric pulse wave analysis and bilateral carotid intima–media thickness (CIMT). Serum ADMA and L-arginine levels were measured, and hemoglobin, reticulocyte count, and ferritin levels were recorded. Results: Children with β-thalassemia major demonstrated significantly increased arterial stiffness compared with controls, including higher PWV (4.61 ± 0.37 vs. 4.38 ± 0.31), AIx@75 (28.5 ± 8.34 vs. 22.8 ± 6.51), left CIMT [0.45 (0.39–0.51) vs. 0.41 (0.38–0.46)], and right CIMT [0.43 (0.39–0.54) vs. 0.40 (0.34–0.46)]. In addition, patients exhibited reduced global longitudinal strain (–19.3 ± 2.91 vs. –21.84 ± 1.91), prolonged isovolumetric relaxation time [53 (37–71) vs. 45 (37–55)], and elevated E/Em (8.44 ± 2.19 vs. 6.92 ± 1.10). ADMA levels were significantly higher in patients (0.54 ± 0.19 vs. 0.39 ± 0.22) and were positively associated with reticulocyte counts and inversely correlated with hemoglobin levels. In addition, both ADMA and ferritin levels were positively correlated with arterial stiffness indices and left ventricular filling pressures. Conclusions: Children with β-TM exhibit an early cardiovascular aging phenotype characterized by impaired myocardial deformation, diastolic involvement, and increased arterial stiffness. The close association of ADMA with hemolysis markers, vascular stiffness, and myocardial deformation supports a central role of endothelial dysfunction in premature myocardial–vascular remodeling and suggests ADMA as a clinically relevant biomarker for early cardiovascular risk stratification in pediatric β-TM.

Abstract: The pancreatic pseudocyst is a collection of pancreatic fluid surrounded by a non-epithelialized wall composed of granulation tissue and fibrosis, occurring in approximately 10% of patients diagnosed with acute pancreatitis and in 20–38% of those with chronic pancreatitis. Most pseudocysts are situated in the head and pancreatic body, but about 20% developed in extrapancreatic locations. We present the case of a 46-year-old male patient diagnosed with chronic alcohol pancreatitis with acute exacerbation, who developed a large pancreatic pseudocyst with subcapsular location in the right hepatic lobe, successfully treated by laparoscopic surgical drainage. The computed tomography scan and postoperative biochemical analysis of the intracystic fluid played a key role in establishing the diagnosis of this rare condition. Intrahepatic pancreatic pseudocyst is a rare location of pancreatic pseudocysts, but the one located in the right hepatic lobe is an extremely rare location. The treatment of intrahepatic pancreatic pseudocysts may be conservative, or endoscopic, percutaneous, or surgical drainage may be necessary. The presence of symptoms, signs of extrinsic compression or complications require drainage of the pseudocyst.

Abstract: Research on how patients and family carers experience their relationships with physicians and healthcare staff is limited, particularly regarding the gap between ideal expectations and actual care. This study explored patients’ and family carers’ perceptions of the ideal care relationship, their lived experiences, and factors shaping discrepancies between expectations and reality. A total of 143 semi-structured interviews (mean age = 56.7 ± 13.2; 61.4% women) were conducted with 57 cancer patients and 86 family carers in outpatient oncology clinics in Southern Italy. Transcripts were analysed using Thematic Analysis of Elementary Contexts (TAEC), a mixed-methods approach combining qualitative and quantitative techniques. Four thematic clusters emerged: “Variability in the experience,” “The ideal care relationship,” “Waiting times and delays in care,” and “The luck of being cared for by a good physician.” Participants emphasized the importance of emotional support and family involvement, while also reporting unpredictability, variability in quality, and limitations in continuity and timeliness of services. These findings suggest that strengthening patient- and family-centred care requires both relational improvements and organizational interventions aimed at enhancing service coordination, resource allocation, and overall quality of care.

Abstract: Background and objectives: Upper gastrointestinal bleeding (UGIB) is a common cause of emergency department admissions with significant mortality risk. Risk stratification remains challenging in clinical practice. This study aimed to evaluate the associations of inflammatory biomarkers including Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Monocyte-to-Lymphocyte Ratio (MLR), Systemic Immune Inflammation Index (SII), and Systemic Inflammation Response Index (SIRI) with intensive care admission rates and 30-day mortality in patients with UGIB. Materials and Methods: A retrospective cohort study was conducted, including 307 patients with UGIB treated. Inflammatory biomarkers were calculated from admission hemogram results. The associations of these biomarkers with intensive care admission and 30-day mortality (survivors vs. non-survivors) were analyzed. ROC analysis was performed to evaluate the predictive value of inflammatory parameters for mortality. Results: The 30-day mortality rate was 14.3%. Significant differences were observed between survivors and non-survivors in terms of SII (median 1268vs. 2544, p=0.030) and SIRI values (median 3.96vs. 9.23, p=0.003). Furthermore, SIRI values exhibited substantial variances among the various Forrest bleeding classification groups (p=0.037). ROC analysis revealed that SII (AUC 61.1%, cut-off 1056.8) and SIRI (AUC 67.5%, cut-off 3.19) had limited predictive value for mortality. After adjusting for age, comorbidities, and bleeding etiology in multivariable analysis, SIRI remained independently associated with mortality. Conclusions: SII and SIRI demonstrate statistically significant associations with mortality in UGIB patients, though with limited discriminative ability. These biomarkers, which are easily calculable from routine blood tests, may serve as supplementary tools in the risk assessment of UGIB patients. Further prospective studies with larger cohorts are required to confirm these findings and investigate their potential clinical applications.

Abstract: In this work, we present a detailed comparison of the SuSAv2 (SuperScaling Approach version 2) and RDWIA (Relativistic Distorted-Wave Impulse Approximation) models with measurements of charged-current neutrino-induced single-pion production from different experiments (T2K, MINERvA and MiniBooNE), studying the differences between the two theoretical descriptions. The neutrino energy range in these experiments spans from hundreds of MeV to roughly 20 GeV, and the nuclear targets are mainly composed of ¹²C. The SuSAv2 model uses the single-nucleon inelastic structure functions from the ANL-Osaka DCC model, which allows for a separation of pion production channels, distinguishing between the π⁺, π⁻ and π⁰ final states. In the RDWIA approach, the Hybrid model developed by the Ghent group is used for the description of the boson-pion-nucleon vertex.

Abstract: The evolution of future Internet and sixth-generation (6G) networks is driving a paradigm shift from classical bit-centric communication toward meaning-aware and task-oriented communication models. Traditional information theory, while fundamental for ensuring reliable symbol transmission, does not account for semantic relevance or task effectiveness, which are critical for emerging applications such as autonomous systems, immersive services, and ultra-low-latency communications. This article presents a comprehensive review of Semantic Communications (SemCom) from a future Internet perspective. The review systematically analyses representative extensions of classical information theory aimed at quantifying semantic information, including semantic information measures, semantic channel capacity, and semantic rate–distortion formulations. In addition, the main mathematical and computational frameworks enabling practical semantic communication systems are examined, including the Information Bottleneck principle, learning-based end-to-end communication architectures, and reinforcement learning approaches for task-oriented optimization under network constraints. The review further discusses the role of semantic metrics, contextual modelling, and task-driven performance evaluation in the design of semantic-aware communication systems. The analysis identifies key open challenges, particularly the lack of a unified theoretical framework, the need for robust and context-aware semantic performance metrics, and the integration of semantic awareness into network-level design. Overall, this review highlights Semantic Communications as a promising paradigm for future Internet and 6G networks, where communication efficiency is increasingly determined by semantic relevance and task effectiveness rather than bit-level fidelity alone.

Abstract: This study explores the use of bentonite to enhance biological biogas upgrading in a bubble reactor (BR) operated under mesophilic conditions (39 ± 1 °C). The experimental setup consisted of a 2 L vertically oriented BR (height to diameter ratio 16:1) fed with a synthetic gas mixture (60% H₂, 15% CO₂, 25% CH₄, v/v) at a gas recirculation rate of 4 L L_R⁻¹ h⁻¹. The aim was to overcome hydrogen’s low gas-liquid mass transfer rate while avoiding the operational challenges typically associated with trickle-bed reactors (TBRs). Bentonite increases the density and hydrostatic pressure of the liquid medium, and likely alters its rheology, thereby extending the gas-liquid contact time without requiring elevated pressures or intensive gas recirculation. Additionally, bentonite is expected to provide microstructural support that promotes the formation of biofilm-like communities, creating favorable microenvironments for hydrogenotrophic methanogens. As a clay-based additive, bentonite may also contribute to improved process stability through adsorption of inhibitory compounds, enhanced bio-mass retention, and pH buffering. Under mesophilic conditions, the bentonite-modified BR achieved a methane production rate of 2.17 ± 0.06 L _CH4 L_R⁻¹ d⁻¹ at a gas retention time of 1.49 h, with methane purity reaching 96.25%. In comparison, a previously reported mesophilic BR operated under identical reactor configuration and operating conditions but without bentonite exhibited substantially lower methane production rates, supporting the beneficial role of bentonite in biological methanation. The findings highlight bentonite’s potential dual role -physical and biological- in improving process efficiency and stability in biological methanation.

Abstract: GEOGUIAS is a certified training program for local citizens to become knowledgeable tour guides, promoted by the Oeste UNESCO Global Geopark and supported by the National Tourism Office. The program's primary goal is to promote sustainable tourism and geoeducation, empowering the trainees to conduct geotouristic and educational tours, based on their region's geological, historical, and cultural heritage. The training combines on-line theoretical components with practical face-to-face field experiences. Participants learn about the local geology, history, culture, wildlife, and field safety, receiving a final Geoguide Certificate issued by the Oeste Geopark. The program aims to involve local communities in geotourism activities, contributing to creating new jobs and to support local economy, while safeguarding geoheritage sites. This study is based on a survey answered by >50 certified geoguides, characterizing their profile, expectations, and perceived results. It addresses the impact of training on geoguides, looking at the changes induced by the program on their local and professional or personal activities. Finally, the study aims to identify the impacts of this training and certification on local networking, sustainable geotourism and regional economic dynamics.

Abstract: Precision oncology has matured into a multidimensional field in which static molecular profiling — encompassing genomic, transcriptomic, and other omic data — is increasingly complemented by dynamic functional assays that measure direct tumor responses to therapeutic agents. While molecular diagnostics provide critical insights into cancer biology and potential drug targets, they do not always predict real-world therapeutic efficacy, especially in tumors characterized by high heterogeneity or complex regulatory networks. Functional ex-vivo testing platforms, including patient-derived organoids and tumor slice cultures, offer a phenotypic readout of drug resistance that reflects the integrated behavior of tumor cells within their microenvironment. This review synthesizes the technological advances and practical frameworks that support the integration of multi-omic and ex-vivo data in precision oncology. We present the current landscape of predictive modeling and functional validation, including workflows that move from transcriptomic and pharmacogenetic prediction toward rapid ex-vivo confirmation of drug effects, and discuss how such integrative approaches can refine therapeutic choices. We describe clinical implementation pathways, highlight operational and regulatory challenges, and explore ethical considerations that must be addressed to bring functional precision medicine into mainstream practice. By examining clinical feasibility, existing trial evidence, and emerging platforms, we highlight both the opportunities and barriers inherent in translating functional testing into routine care. Finally, we consider future directions aimed at achieving standardized, scalable, and clinically validated functional diagnostics. The integration of molecular and functional insights offers a promising route toward more accurate, individualized cancer therapy, and suggests a future in which treatment selection is guided not only by molecular signatures but by direct functional evidence of drug efficacy.

Abstract: This study addresses the critical challenge of optimizing outdoor thermal comfort for the aging population in old residential communities within China's hot-summer and cold-winter climate zones. Against the backdrop of urban regeneration and rapid demographic aging, it investigates how key landscape elements—ground reflectance, greening type, and pergola condition—influence the microclimate of community public spaces. The research employed an integrated methodology centered on numerical simulation. Using the ENVI-met software and an L₉(3⁴) orthogonal experimental design, it simulated the microclimatic effects of nine combined scenarios on typical summer and winter days for a case study in Nanjing. The comprehensive thermal comfort index, Physiological Equivalent Temperature (PET), was used as the primary evaluation indicator to assess the thermal comfort performance for elderly occupants, with the assistance of air temperature, wind speed, and relative humidity, and the results were analyzed via range analysis and ANOVA. The key findings indicate that: (1) Greening type and pergola condition are the dominant factors affecting microclimate and annual thermal comfort across seasons, while ground reflectance has a comparatively minor influence. (2) The combination of deciduous trees with lawn achieves the optimal cross-seasonal PET gain. It provides effective shading and cooling in summer while allowing beneficial solar penetration for warming in winter, substantially outperforming evergreen-dominated configurations. (3) The presence of a pergola consistently enhances comfort by providing essential shade in summer and acting as a windbreak in winter. The combination dominated by deciduous trees + lawn and pergola yield an overall PET gain 1.0967 ℃ higher than that of evergreen trees + shrub without pergola. This study provides evidence-based, elderly-specific landscape design strategies to inform the thermal environment optimization of public spaces in old residential areas undergoing renewal.