Abstract: Background/Objectives: Birt-Hogg-Dubé (BHD) syndrome is a rare autosomal dominant disorder caused by germline pathogenic variants in the FLCN gene. Although it carries a substantial lifetime risk of renal cell carcinoma, its earliest manifestations are typically pulmonary cysts and spontaneous pneumothorax, which are frequently misclassified as primary spontaneous pneumothorax, resulting in diagnostic delay and inadequate oncological surveillance. We aimed to characterise the real-world phenotypic spectrum of BHD encountered in a respiratory referral setting. Methods: We retrospectively describe seven consecutive patients with genetically confirmed BHD syndrome diagnosed at our tertiary referral centre between 2022 and 2024. Demographic data, smoking history, FLCN variants, pneumothorax episodes, HRCT findings, pulmonary function tests and extrapulmonary neoplasms were collected. Reporting followed the PROCESS 2020 guideline. Results: Mean age at genetic diagnosis was 53.1 years (range 41–64). All seven patients had multiple thin-walled pulmonary cysts on HRCT, with the typical basal, subpleural and paramediastinal distribution; three had a pneumothorax history. Despite largely preserved spirometry (mean FEV1 82.4% predicted), DLCO was reduced in five patients (mean 67.4% predicted) and was the most frequently affected functional parameter, although the overall functional picture was heterogeneous. Five patients had solid neoplasms (one renal, one colorectal, one thyroid/parathyroid, one ovarian, one lung adenocarcinoma). Conclusions: In this referral-based case series, pulmonary cysts were a constant finding and DLCO was the most frequently reduced functional parameter, although the functional picture varied across patients. These descriptive observations are hypothesis-generating and require prospective, controlled validation—including comparison with other diffuse cystic lung diseases—before any diagnostic algorithm can be proposed.

Abstract: The present study aimed to evaluate the stability of volatile organic compounds (VOCs) in exhaled breath samples under different storage conditions (refrigeration at -20 °C vs. room temperature) and analysis times (0 h, 3 h, 6 h, 12 h). Alveolar exhaled breath samples were collected from 30 volunteers in 500 mL Tedlar® bags, followed by analysis using headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-mass spectrometry (GC-MS). The results showed the putative identification of 73 metabolites, 41 of which were common to both conditions. Pre-analytical storage of the samples at -20 °C significantly altered (p < 0.05) the stability of 33 of the 41 common VOCs analyzed. Specifically, refrigeration improved stability by reducing the coefficient of variation (CV) in 23 of these metabolites compared to samples kept at room temperature. Highly stable metabolites with a CV < 15% were found. A 90% loss of the analytical signal was observed 12 hours after sample collection, in contrast to the stability maintained in refrigerated samples. These findings highlight the influence of pre-analytical conditions on the integrity of volatile profiles, establishing immediate refrigeration as a fundamental step for the study of potential biomarkers present in breath. These results provide key criteria for the standardization of breathomics protocols.

Abstract: The paper examines the impact of gas turbine engine component manufacturing quality on the efficiency criteria of its life test. Known methods for selecting test parameters apply maximum damageability equivalence and minimum test time as test efficiency criteria. This study also proposes taking into account the maximization of engine lifecycle profits through the proper selection of test parameters. Engine components that determine its life were selected: the turbine blade, rotor bearing, reducer driving gear, fan bearing, and DC and AC generators. Both the mathematical expectation and variance of the quality parameters were varied during the study. The manufacturing quality of engine components and assemblies is characterized by geometric, mechanical, and physical parameters. These parameters include bearing fit diameters, initial radial clearance, turbine blade geometry, mechanical properties and gear shape, generator insulation quality, and others. Parameters selection was based on the life cycle simulation model. The following results were obtained in the course of the study: (1) Manufacturing accuracy has a more significant impact on test results than deviations from mean values of initial state parameters; (2) Despite the fact that variation in production parameters from the standard values do not affect the comparability of test results, they lead to an acceleration of the testing process. At the same time, this entails a decrease in overall economic efficiency throughout the entire life cycle of the product; (3) The overall profitability of a production run of engines is primarily determined by the quality characteristics of the turbine blades, and least on fan bearing quality parameters; (4) in the case where there is a full guarantee of engine component manufacturing quality, only short-term (acceptance, control) tests can be carried out.

Abstract: Increasing high-impact, low-probability (HILP) disruptions require a paradigm shift in emergency power for critical infrastructure (CI), moving away from traditional cost-driven assessments toward physical resilience. To address this gap, this article develops a resilience-oriented screening framework to prequalify energy technologies (including CHP and CCHP) for CI facing prolonged outages. Diverging from pure economic optimization, the methodology prioritizes survivability criteria: islanding readiness, black-start capability, fuel autonomy, multivector energy coverage, implementation feasibility, and operational safety. A hospital serves as the reference CI due to its rigorous demand for simultaneous electricity, heat, cooling, and process loads. The framework employs a two-stage procedure: a Stage I go/no-go boundary filter and a Stage II weighted scoring matrix. This methodology evaluates a broad technology basket encompassing gas, biogas, and biomass CHP, CCHP with absorption cooling, hybrid CHP/BESS, RES+BESS, and diesel generators. Rather than providing a definitive techno-economic ranking, this study establishes a transparent, replicable front-end engineering tool. Ultimately, the results define boundary conditions for prequalifying multivector energy architectures, creating a foundation for future modeling and dynamic simulations of CI microgrids.

Abstract: The educational portfolio is in line with the principles of OBE (Outcome-Based Education) as a tool enabling the documentation and assessment of learning outcomes in a continuous, individualized manner, embedded in a real clinical context. Its use allows for a shift away from point-based assessment of achievements in favor of monitoring the progression of competencies over time, which is one of the key postulates of competency-based education (programmatic assessment). The educational portfolio is an important tool supporting the process of medical education, combining the perspectives of the teaching physician and the medical student. From the clinical teacher’s point of view, the portfolio enables systematic assessment of the student’s progress, clinical competencies, reflective skills, and professional development over time. It also facilitates the individualization of the teaching process, supports constructive feedback, and promotes the development of professional attitudes consistent with the principles of evidence-based medicine and medical ethics. For medical students, the portfolio is a space for active learning, integrating theoretical knowledge with clinical experience. It allows them to document the skills they have acquired, analyze their strengths and areas for further development, and develop self-reflection and responsibility for their own learning process. Regular portfolio maintenance promotes awareness of the role of a future physician and prepares students for lifelong learning. The joint use of the portfolio by the teacher and student strengthens the partnership model of education, increases the transparency of requirements, and improves the quality of medical education, making it more focused on the development of competencies and patient needs.

Abstract: The rapid expansion of unmanned aerial vehicles (UAVs) applications in logistics, surveillance, and defense highlights the need for scalable and reliable energy delivery solutions. Conventional charging approaches constrain operational endurance and scalability, requiring frequent returns to base. This paper presents a laser-based wireless power transmission system designed to enable safe, contactless and efficient power transfer from ground to air. The proposed architecture integrates a high-power optical source, a hierarchical beam-pointing system combining coarse and fine steering, and a receiver-side sensing and energy-conversion module. The system is designed to be adaptable across different UAV classes, from lightweight platforms to larger aerial systems. An experimental campaign is conducted to validate the main system functions under representative operating conditions. Beam propagation, pointing accuracy, and control response are characterized through laboratory and outdoor tests, including long-range spot measurements and closed-loop steering validation. Overall, the study demonstrates the feasibility of laser-based wireless energy transfer for UAV applications and provides an experimental foundation for the development of persistent aerial operations in both civil and defense scenarios.

Abstract: Raman spectroscopy combined with machine learning offers a rapid, label-free approach for bacterial identification, but robust translation remains challenged by spectral variability, biological heterogeneity, and limited model interpretability. Here, we present an integrated evaluation of an optimized Spectral Transformer (ST) framework for Raman-based bacterial classification benchmarked against a systematically optimized one-dimensional convolutional neural network (1D-CNN). The comparison was performed using a curated 36-class dataset comprising 15 Gram-negative bacterial entries, 15 Gram-positive bacterial entries, one non-bacterial microorganism, and five background/reference classes, enabling evaluation of both species-level and fine-grained bacterial classification. Under 15 dB noise-augmented evaluation, the ST achieved 80.6% ± 0.3% accuracy and a Matthews correlation coefficient (MCC) of 0.801 ± 0.003, outperforming the 1D-CNN baseline with 72.9% ± 0.3% accuracy andanMCCof0.721±0.003. Integrated Gradients analysis combined with attention map visualization enabled multi-level model interpretation, revealing that the ST’s improved robustness correlates with more bounded attribution patterns during misclassification, whereas the 1D-CNN’s feature attribution becomes scattered under noise perturbation. Importantly, this interpretability-driven analysis identified model-specific failure modes in the baseline architecture, including an over-reliance on non-specific spectral regions under noise, which can inform future data collection strategies and guide refinements to experimental protocols. These results demonstrate that attention-based spectral modeling improves Raman-based bacterial classification under noise-perturbed conditions while enabling multi-level interpretability that bridges model understanding with actionable feedback on experimental design and data quality requirements.

Abstract: Aerial radiation surveys produce sparse trajectories that must be reconstructed into contamination maps. Conventional aerial interpolators — inverse distance weighting (IDW) and ordinary kriging — treat observations as local ground samples, ignoring that each measurement integrates radiation over an extended footprint A(x,y) = (C * K)(x,y). The resulting double-blurring imposes a second smoothing on already-convolved values, causing systematic underprediction regardless of measurement density. We cast reconstruction as inverse deconvolution. A physics-aware encoder-decoder receives five channels (sparse measurements, IDW baseline, land-water scalar prior, measurement mask, water mask) and learns to invert K under a forward-consistency loss. The network is pretrained on synthetic data and deployed without fine-tuning. At a 50% random within-system holdout over 2,213 Ukedo points [7], 25 runs achieve a mean root-mean-square error (RMSE) of 705.4 ± 102.8 counts per second (CPS) versus 916.8 ± 34.2 (IDW) and 832.4 ± 31.3 (Kriging), with directional improvement over IDW in 25/25 runs. In a 3-model ensemble diagnostic, among held-out points exceeding T = 6,000 CPS (n = 64 at split seed 10, near the IDW ceiling), the U-Net recovers approximately 80% while IDW and kriging both fall to approximately 0%. The operational value lies in high-intensity hotspot recovery; spatially independent validation remains an open challenge.

Abstract: Accurate significant wave height prediction is essential for fuel-efficient ship operation and weather routing, as wave-induced resistance directly affects propulsion demand and fuel consumption. This study proposes a Residual U-Net-based deep learning correction model to improve long-range SWH forecasts from WAVEWATCH III (WW3). WW3 global forecast fields were corrected using the proposed model, with CMEMS reanalysis data used as the ground-truth reference. The corrected outputs, denoted as WW3_UNET, were evaluated against 10-minute-resolution main engine fuel oil consumption (ME1_FOC) records and onboard wave observations from a commercial vessel traversing the South Atlantic in 2025. WW3_UNET showed markedly improved agreement with ship observations compared with the raw WW3 forecast across all lead times from 0 to 288 h. When a 24-hour moving average was applied, WW3_UNET achieved a correlation of 0.720 with ME1_FOC at the 168–180 h lead time, closely approaching the 0.736 obtained from onboard wave measurements. These results indicate that AI-corrected forecasts can provide observation-consistent wave information up to 7–8 days in advance. The proposed approach can support fuel-aware weather routing and voyage planning, thereby contributing to improved maritime energy efficiency and decarbonization.

Abstract: Agricultural intensification degrades farmland biodiversity, prompting the use of wildflower strips to restore natural enemies. However, their spatio-temporal effects on predators in arid agroecosystems remain unclear. We investigated ground-dwelling spiders in sown wildflower strips versus natural margins across four cropping systems in arid northwestern China using pitfall traps along a spatial gradient throughout the growing season. While overall diversity did not differ significantly between treatments, three key patterns emerged. First, spider abundance remained stable across the spatial gradient, but taxonomic diversity increased significantly toward the crop interior. Second, while communities in natural margins peaked early and declined during the hot, dry mid-summer, wildflower strips maintained high populations, acting as crucial temporal refuges. Third, wildflower strips reorganized species co-occurrence networks, fostering more resilient community structures. We conclude that in water-limited environments, wildflower strips stabilize predator populations during harsh weather and enhance community resilience. These findings highlight the value of wildflower strips in designing sustainable ecological pest management strategies for arid agroecosystems.

Abstract: We introduce the concept of asymptotic admissibility as a branch-selection principle for implicit analytic deformation systems and develop its geometric realization within the Implicit Biparametric Deformator System (IBDS). Rather than attempting a global classification of all complex solution branches, the framework isolates a distinguished admissible branch through structural asymptotic constraints, global injectivity, and sectorial boundarycovering properties. We prove the global univalence of the defining structural operator on the open right half-plane, establish the existence and uniqueness of the positive real spine, and demonstrate strict right-half-plane containment via explicit topological boundary-tracking. The analysis reveals two fundamental asymptotic horizon geometries governing the admissible branch: a non-linear dissipation horizon and a linear transport horizon. These structures lead naturally to a parameter-separation principle in which the deformation parameter α determines the asymptotic geometric phase, while the transport parameter β regulates horizon intensity without altering the continuation topology.

Abstract: Background/Objectives: Breast milk transfers living maternal cells and epigenetic regulators, including microRNAs (miRNAs), into the nursing infant, creating biological bonds that extend beyond nutrition. For Muslim communities, this has underappreciated implications, as Islamic law establishes milk kinship (raḍāʿ), a legally recognised familial bond formed through breastfeeding that prohibits marriage between milk siblings. Contemporary human milk banking, however, relies on anonymised donor milk that makes milk kinship traceability impossible for Muslim families. Methods: A narrative review of the biomedical literature on cellular microchimerism and epigenetic transfer via breastfeeding was conducted, alongside review of primary Islamic legal sources and classical and contemporary scholarship on raḍāʿ. Results: Breastfeeding transfers stem cells, immune cells, and miRNA-carrying exosomes from the nursing woman into multiple infant tissues, where they integrate and induce persistent changes in gene expression. Children nursed by the same woman share these biological inputs and may thereby exhibit cellular and epigenetic similarities that partially mirror consanguinity. A substantial body of evidence links consanguineous marriage to a doubling of congenital anomaly risk, a 20-fold increase in rare autosomal recessive disease, elevated infant mortality, and increased intellectual disability. The Islamic prohibition of marriage between milk siblings therefore serves a biologically coherent public health function analogous to, and scientifically consistent with, the prohibition of blood-relative marriage. Importantly, anonymised milk banking creates unresolvable uncertainty about milk kinship ties for Muslim families. Conclusions: The biological evidence for a substantive breastfeeding bond is stronger than commonly appreciated and is directly relevant to Muslim religious obligations. The Islamic prohibition of marriage between milk siblings is biologically coherent — milk siblings share cellular and epigenetic material in ways that parallel consanguinity, which carries well-documented health risks for offspring. Traceability frameworks in milk banking offer a clinically and ethically workable path forward. We provide specific recommendations for researchers, neonatal clinicians, milk bank administrators, and Islamic scholars in this regard.

Abstract: Speech Large Language Models (Speech LLMs) have exhibited exceptional efficacy across various tasks, including Automatic Speech Recognition (ASR) and general audio understanding. However, the quadratic complexity of self-attention mechanisms constrains long-form scalability and incurs prohibitive inference overhead. Consequently, token compression has become a key strategy for facilitating lightweight and efficient inference. To address this, we propose SA-MAP, a plug-and-play compression framework for Similarity-Attention driven joint token Merging And Pruning that exploits the inherent temporal dependencies of speech. Specifically, the framework operates in two sequential stages: the first stage merges adjacent tokens to maximize information retention, while the second stage executes pruning to safeguard token diversity, thereby equilibrating compression intensity and information integrity. Extensive evaluations on mainstream Speech LLMs demonstrate that SA-MAP consistently establishes new state-of-the-art (SOTA) benchmarks, outperforming established baselines. Notably, when applied to Qwen2-Audio and Kimi-Audio, SA-MAP achieves a 50% lossless token reduction in understanding tasks, and a 40% compression ratio in ASR with only marginal degradation in Word Error Rate (WER). The code is available at https://github.com/Tencent/AngelSlim/tree/SA-MAP.

Abstract: TLS are ectopic, non-encapsulated aggregates of immune cells that develop de novo in non-lymphoid tissues in response to persistent antigenic stimulation, and have emerged as clinically relevant features of many solid tumours. However, conventional TLS assessment based on presence/absence, density, or simplified maturation scales does not adequately explain why TLS are associated with favourable, neutral, or even adverse clinical outcomes across tumour types and treatment settings. In this review, we synthesize current biological, spatial, and clinical evidence and argue that TLS should be interpreted not as static histologic findings, but as functional immune niches shaped by three interacting axes: structural maturity, spatial localization, and functional immune context. We discuss how mature germinal centre-positive TLS often reflect coordinated B-cell–T-cell cooperation and sustained antigen-driven antitumour immunity, whereas partially organised or suppressive TLS may display transitional or immunoregulatory properties. On this basis, we propose a pragmatic, pathology-oriented conceptual framework that groups TLS into three simplified functional states: TLS-A, representing mature effector TLS with germinal centre activity; TLS-B, representing organised but incompletely matured or functionally intermediate TLS; and TLS-C, representing TLS dominated by regulatory or suppressive immune programs. We further place these states within recurrent tumour microenvironment archetypes and outline the rationale for a “functional TLS score” integrating histopathologic and molecular readouts. Rather than introducing a definitive biological taxonomy, this framework is intended as a translational model for harmonising TLS interpretation, refining biomarker development, and supporting future studies on prognosis, immunotherapy response, and standardised pathology reporting in solid tumours.

Abstract: The study examined the extent of bribery within the public healthcare system in Greece and the influence of its determinants at the macro-, meso-, and micro-levels, highlighting institutional and cultural influences, systemic weaknesses, inequalities, and high-risk groups. Structured questionnaires were administered to a representative sample of adult users of healthcare services in public hospitals located in urban areas. The analysis included descriptive statistics to examine variable distributions and trends, bivariate non-parametric tests to assess associations between informal payments and selected demographic and socioeconomic characteristics, as well as binary logistic regression modelling to estimate the probability of exposure to informal payments based on specific individual characteristics. The study sample comprised 2,072 adults, of whom 59.5% were female and 40.5% male, with the largest age group being 36–55 years. A proportion of 23.2% resided outside the metropolitan areas of Athens and Thessaloniki, while nearly 50% reported a monthly household income of up to €1,500, indicating a substantial representation of socio-economically disadvantaged groups. The analysis revealed the existence of a significant problem of informal payments within the Greek public healthcare system and identified specific institutional, cultural, and organizational determinants, as well as demographic and socioeconomic groups that are particularly vulnerable to such practices. The phenomenon disproportionately affects economically, educationally, and geographically disadvantaged populations. Addressing informal payments in healthcare is essential to preventing the erosion of the social fabric of the country and requires comprehensive transparency-oriented policies, the strengthening of equitable access to services, and targeted interventions for high-risk groups, in order to ensure the sustainability of the public healthcare system and the promotion of equitable and healthy living conditions for the population.

Abstract: In Senegal, scaling up vector control has significantly reduced malaria, but coastal transmission remains a challenge due to secondary vectors like Anopheles melas. This exophilic and zoophilic species evades conventional indoor interventions, yet its bionomics and insecticide resistance profiles remain poorly characterized due to difficulties in laboratory colonization. Anopheles melas larvae were collected from brackish breeding sites in Mbine Coly (Mbour District). A laboratory colony was established from 26 PCR-confirmed founder females and stabilized up to the F17 generation by optimizing water salinity (10 g/L) and transitioning to communal oviposition. Standardized WHO tube bioassays were conducted on generations F2 to F9 to evaluate susceptibility to pyrethroids, organophosphates, and carbamates, alongside synergist tests using 4% piperonyl butoxide (PBO). The colony showed confirmed resistance to alpha-cypermethrin (81.7% mortality) and suspected resistance to deltamethrin (91.3%) and permethrin (94.3%). Pre-exposure to PBO fully restored susceptibility to deltamethrin and permethrin (100%), and significantly increased alpha-cypermethrin mortality to 96.3% (p < 0.001), demonstrating a major cytochrome P450-mediated metabolic resistance. High-intensity resistance was confirmed for alpha-cypermethrin at 5X diagnostic doses. Conversely, the population was 100% susceptible to pirimiphos-methyl and bendiocarb. This study reports the successful long-term colonization of a wild An. melas strain for the first time and provides the first comprehensive evidence of multi-insecticide resistance in this population. The presence of high-intensity, metabolic pyrethroid resistance strongly justifies the immediate deployment of next-generation PBO-LLINs and the integration of organophosphates or carbamates in indoor residual spraying rotations to manage resistance in coastal Senegal.

Abstract: High-volume injection mold systems used for plastic part production operate under severe coupled thermo-mechanical boundary conditions. During each molding cycle, core inserts are subjected to repeated injection pressure, transient thermal effects, and mechanical constraints imposed by the polymer and the surrounding mold assembly. These combined actions generate localized stress concentrations in critical insert regions, promoting crack initiation and eventual core insert breakage. To describe the behavior of hot-work tool steel core inserts under these operating conditions, experimental process measurements, structural analysis, and damage modelling must be linked within a service-life assessment framework. This integrated approach supports the interpretation of the observed failure case and helps identify the root cause of premature core insert breakage.

Abstract: Spatially explicit crop-yield information is needed for regional environmental modeling, sustainability assessment, and agricultural decision support, yet official yield statistics are commonly reported only at aggregated administrative scales. This study introduces the nayd R package, a reproducible geospatial workflow for converting county-level harvested area and yield statistics into spatially explicit production units and zonal clusters while preserving consistency with official records. County-level statistics from the USDA National Agri-cultural Statistics Service were integrated with USDA Cropland Data Layer crop masks, multi-sensor NDVI products, and satellite-derived evapotranspiration from OpenET SSEBop. An NDVI-based eligibility filter refined crop masks toward reported harvested area, while normalized NDVI and evapotranspiration layers were combined into spatial weighting surfaces and aggregated into contiguous production units and graph-based clusters. Case studies for cotton and winter wheat in Texas showed that the eligibility filter removed approximately 20–40% of CDL-classified pixels while maintaining consistency with reported harvested area and preserving plausible spatial gradients associated with ir-rigated and dryland systems. Evaluation against independent Texas A&M AgriLife vari-ety-trial data yielded normalized RMSE values of approximately 11–15% for cotton and 9–12% for winter wheat. The workflow provides an open-source framework for generating statistically consistent production zones for regional crop modeling, environmental as-sessment, and sustainable agricultural planning.

Abstract: Aerosol Jet Printing, AJP, has emerged as a versatile direct ink writing technology enabling high-resolution, non-contact patterning of diverse biomaterials across a broad viscosity range. This capability facilitates the fabrication of complex micro- and mesoscale architectures on planar and non-planar substrates, advancing applications in biosensing, microfluidics, tissue engineering, and drug delivery fields. Herein, we review the integration of this high resolution, rapid prototyping method with bioinks, including proteins, DNA, collagen, gelatin, and silk fibroin, and analyze how processing parameters influence structural and functional outcomes designed for applications for the above mentioned bechnological fields. The ability by aerosol jet printing to combine structural, electrical, and biological functionalities within single platforms supports the development of multifunctional biomedical devices with higher potential with respect to analogies produced using other direct ink writing techniques. While challenges such as bioink stability and process scalability, as well as the lack of deeper analyses about the efficiency of real applicability of aerosol jet printed biotools, still remain open, AJP demonstrates significant promise as an enabling technology for next-generation biofabrication, offering new avenues for personalized and flexible biomedical applications.

Abstract: Backgruond: During adolescence, depression is a major concern due to its high prevalence and long-term impact on well-being. Effective intervention requires accurate assessment through culturally and linguistically adapted instruments with strong psychometric properties. Aims: This study aims to adapt and evaluate the metric properties of the Beck Depression Inventory (BDI-II) in the Moroccan context and to perform a cross-cultural Spain-Morocco analysis according to sex and age. Method: A total of 1,141 students, 514 residents in Spain and 627 in Morocco, aged between 14 and 19 years, completed the BDI-II and BASC-S3 questionnaires. Results: The Spanish and Moroccan versions of the BDI-II showed adequate metric properties and invariance across gender and age within and between countries. Intra-country comparisons revealed that in Spain there were only sex differences in somatic-vegetative symptomatology, whereas in Morocco these differences by sex were only found in cognitive-affective symptomatology. No differences were observed according to age. Cross-country comparison showed differences between Spain and Morocco in both types of symptoms. Conclusions: The use of this adaptation of the BDI-II will favour more accurate assessments in Moroccan and Spanish adolescents. Understanding cultural differences in the manifestation of depressive symptomatology will help to improve their psychological care.