The SAUR (small auxin-up RNA) family constitutes a category of genes that promptly respond to the hormone auxin and play a pivotal role in diverse biological processes encompassing plant growth and the response to abiotic stress. Santalum album L., a semi-parasitic evergreen tree, is renowned for its economically valuable essential oils, positioning it among the most prized tree species. In this study, a meticulous identification and comprehensive analysis of 43 SAUR genes was conducted within S. album. Based on phylogenetic relationships, the SaSAUR genes were systematically categorized into five groups. A collinearity analysis revealed intriguing insights, disclosing 14 segmental duplications and 9 tandem duplications within the SaSAUR genes, emphasizing the pivotal role of duplication in the expansion of this gene family. Noteworthy variations in the expression levels of SaSAUR genes were observed by delving into the SaSAUR transcriptome data from various tissues, including leaves, roots, and heartwood, as well as under salt-stress conditions. Notably, SaSAUR08 and SaSAUR13 were significantly upregulated in heartwood compared with roots and leaves, while SaSAUR18 was markedly more expressed in roots compared with heartwood and leaves. Furthermore, SaSAUR27 and SaSAUR28 were found to respond closely to salt stress, hinting at their potential involvement in the salt-stress response mechanism. This research offers a comprehensive investigation of SAUR genes in S. album and establishes a foundation for future exploration of the SAUR gene family, particularly its relation to growth and salt-stress responses. Full article

The aim of this analysis was to investigate the socio-demographic and clinical profile, the effectiveness, and the association of pharmacological treatment in patients who underwent electroconvulsive therapy during the last 10 years in the largest psychiatric hospital in Romania. This study includes 249 patients aged between 18 and 73 years old. Recurrent depression was the most frequent diagnosis for which ECT was performed (T = 96, 38.55%), followed by schizophrenia (T = 72, 28.91%). The most frequent indication for ECT was treatment resistance (T = 154, 61.84%), followed by persistent suicidal ideation (T = 54, 21.68%) and catatonia (T = 42, 16.86%). In 111 (44.60%) cases included in this study, re-hospitalization was required after performing ECT, while 138 (55.40%) participants did not require any further hospital readmissions. Significant differences were found between these groups in terms of socio-demographic data, diagnosis, number of ECT sessions performed, and association of psychotropic medication during and after the procedure, therefore two separate patient profiles were found based on these characteristics. Patients necessitating re-hospitalization post-ECT were mainly males aged 25–44 diagnosed with schizophrenia and underwent a greater number of ECT sessions (7–12), whereas those not requiring re-hospitalization were predominantly females aged 45–64 with recurrent depressive disorder for which 4–6 ECT sessions were performed. Full article

Collision detection is very important for robot motion planning. The existing accurate collision detection algorithms regard the evaluation of each node as a discrete event, ignoring the correlation between nodes, resulting in low efficiency. In this paper, we propose a novel approach that transforms collision detection into a binary classification problem. In particular, the proposed method searches the k-nearest neighbor (KNN) of the new node and estimates its collision probability by the prior node. We perform the hierarchical navigable small world (HNSW) method to query the nearest neighbor data and store the detected nodes to build the database incrementally. In addition, this research develops a KNN query technique tailored for linear data, incorporating threshold segmentation to facilitate collision detection along continuous paths. Moreover, it refines the distance function of the collision classifier to enhance the precision of probability estimations. Simulation results demonstrate the effectiveness of the proposed method. Full article

Owing to their high intrinsic safety, dispersed fuel particles are an important fuel pattern for fourth-generation nuclear reactors. Due to the unique cladding layers and the random dispersion characteristics, dispersed fuel particles significantly differ from pressurized water reactors regarding operation-induced uncertainty. This study quantitatively analyzed overall uncertainty while considering a random distribution of dispersed fuel particles, material thickness, and fuel enrichment. The results demonstrated that, for all packing fractions, the uncertainty induced by the random dispersion of dispersed fuel particles was below 0.03%. For every packing fraction, the differences between the results obtained by the regular and the random distribution models increased, and then decreased, until reaching its maximum (1.297%) at 15%. K_eff decreased as the radius of the UO₂ kernel increased; K_eff increased as the thickness of the cladding layer increased; the uncertainty of K_eff was 1.003% when a random distribution of particles, material thickness, and fuel enrichment were taken into consideration; the uncertainty of the power distribution of reactor core assemblies was maximized (1.495%) at the edge of the reactor core. Quantitative analysis of uncertainty provides references for the optimization of design and safety margin analysis for reactors. Full article

The brain is the central organ of adaptation to stress because it perceives and determines threats that induce behavioral, physiological, and molecular responses. In humans, chronic stress manifests as an enduring consistent feeling of pressure and being overwhelmed for an extended duration. This can result in a persistent proinflammatory response in the peripheral and central nervous system (CNS), resulting in cellular, physiological, and behavioral effects. Compounding stressors may increase the risk of chronic-stress-induced inflammation, which can yield serious health consequences, including mental health disorders. This review summarizes the current knowledge surrounding the neuroinflammatory response in rodent models of chronic stress—a relationship that is continually being defined. Many studies investigating the effects of chronic stress on neuroinflammation in rodent models have identified significant changes in inflammatory modulators, including nuclear factor-κB (NF-κB) and toll-like receptors (TLRs), and cytokines, including tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1β, and IL-6. This suggests that these are key inflammatory factors in the chronic stress response, which may contribute to the establishment of anxiety and depression-like symptoms. The behavioral and neurological effects of modulating inflammatory factors through gene knockdown (KD) and knockout (KO), and conventional and alternative medicine approaches, are discussed. Full article

Natural biological nanocomposites, like nacre, demonstrate extraordinary fracture toughness, surpassing their base materials, attributed to their intricate staggered hierarchical architectures integrating hard and soft phases. The enhancement of toughness in these composites is often linked to the crack-deflection mechanism. Leveraging the core design principles that enhance durability, resilience, and robustness in organic materials, this paper describes the use of computational modeling and simulation to perform a three-point bending test on a 3D staggered nanocomposite intentionally crafted to mimic the detailed microstructure of nacre. We adopted a previously proposed interfacial zone model that conceptualizes the “relatively soft” layer as an interface between the “hard” mineral tablets and the microstructure’s interlayer spaces to examine how the microstructure and interface characteristics affect the mechanical responses and failure mechanisms. By comparing the model’s predictions with experimental data on natural nacre, the simulations unveil the mechanisms of tablet separation through adjacent layer sliding and crack deflection across interfacial zones. This study offers a robust numerical method for investigating the fracture toughening mechanisms and damage evolution and contributes to a deeper understanding of the complex interplays within biomimetic materials. Full article

This paper examines the distribution of eigenvalues for a $2\times 2$ random confusion matrix used in machine learning evaluation. We also analyze the distributions of the matrix’s trace and the difference between the traces of random confusion matrices. Furthermore, we demonstrate how these distributions can be applied to calculate the superiority probability of machine learning models. By way of example, we use the superiority probability to compare the accuracy of four disease outcomes machine learning prediction tasks. Full article

Early-onset breast cancer (EoBC), defined by a diagnosis <40 years of age, is associated with poor prognosis. This study investigated the mutational landscape of non-metastatic EoBC and the prognostic relevance of mutational signatures using 100 tumour samples from Alberta, Canada. The MutationalPatterns package in R/Bioconductor was used to extract de novo single-base substitution (SBS) and insertion–deletion (indel) mutational signatures and to fit COSMIC SBS and indel signatures. We assessed associations between these signatures and clinical characteristics of disease, in addition to recurrence-free (RFS) and overall survival (OS). Five SBS and two indel signatures were extracted. The SBS13-like signature had higher relative contributions in the HER2-enriched subtype. Patients with higher than median contribution tended to have better RFS after adjustment for other prognostic factors (HR = 0.29; 95% CI: 0.08–1.06). An unsupervised clustering algorithm based on absolute contribution revealed three clusters of fitted COSMIC SBS signatures, but cluster membership was not associated with clinical variables or survival outcomes. The results of this exploratory study reveal various SBS and indel signatures may be associated with clinical features of disease and prognosis. Future studies with larger samples are required to better understand the mechanistic underpinnings of disease progression and treatment response in EoBC. Full article

The work presents a detailed analysis of the possibilities of the thermal processing of clay raw material granulates in a fluidized bed reactor powered by coal fuel. Potential customers of calcined granulates include the following: plants producing refractory materials for the steel industry, producers of refractory concrete, sanitaryware plants, tile plants, large-size tile plants, industry abrasives, chemicals, paints, paper, food and medical industries and others. The advantage of the presented fluid bed calcination technology is the possibility of the continuous operation of the reactor and the short time of the material in the bed, compared to the previously used methods of calcination in a shaft and rotary kiln, which lasts less than twenty minutes in the temperature range of 650–850 °C. During the experimental studies of calcination in the fluidized bed layer, the influence of the type of coal, its particle size and the mass share of coal in the feed mixture on the calcination process and the final product obtained was analysed. As a result of the conducted research, it was proven that solid fuels such as anthracite and steam coal type 31.2 (flaming) can be successfully used in the fluidized bed calcination process of clay materials. The key parameter determining the fluidized bed calcination process is the fuel particle distribution. Full article

Ensuring the sustainable management of water and sanitation for all is the primary goal of Sustainable Development Goal 6 (SDG 6). SDG indicator 6.4.2 (level of water stress) is critical for monitoring the progress toward SDG 6. The assessment of the SDG indicator 6.4.2 is currently based on statistical data at the national scale, i.e., one value for one country, which cannot reflect spatial variability in water stress in a country. The lack of data at sub-national scales limits the assessment of water stress in sub-national regions. This study developed a method of disaggregating national statistical renewable water resources (TRWR) and freshwater withdrawals (TFWW) to estimate the SDG 6.4.2 water stress indicator at a sub-national scale by combining satellite remote sensing data and model simulated data. Remote sensing (RS)-based precipitation (P); the difference between precipitation and evapotranspiration (P-ET); and the difference between precipitation, evapotranspiration, terrestrial water storage change (P-ET-dS), and model-simulated naturized runoff and withdrawal water use were used as spatial and temporal surrogates to disaggregate the national-scale statistics of TRWR and TFWW to the grid scale. Gridded TRWR and TFWW can be used to calculate the water stress of any interest regions. Disaggregated TRWR, TFWW, and water stress estimation were validated at three different spatial scales, from major river basins and provinces to prefectures in China, by comparing the corresponding statistical data. The results show that the disaggregation for TRWR is generally better than for TFWW, and the overall accuracy for water stress estimation can reach up to 91%. The temporal evolution of disaggregated variables also showed good consistency with statistical time series data. The RS-based P-ET and P-ET-dS have great potential for disaggregating TRWR at different spatiotemporal scales, with no obvious differences with the results using the model simulation as a surrogate for the disaggregation of SDG indicator 6.4.2. The disaggregation accuracy can be further improved when the sub-regional statistical data of TRWR and TFWW are applied to the disaggregation approach. Full article

A smarter city should be a safer city. Nighttime safety in metropolitan areas has long been a global concern, particularly for large cities with diverse demographics and intricate urban forms, whose citizens are often threatened by higher street-level crime rates. However, due to the lack of night-time urban appearance data, prior studies based on street view imagery (SVI) rarely addressed the perceived night-time safety issue, which can generate important implications for crime prevention. This study hypothesizes that night-time SVI can be effectively generated from widely existing daytime SVIs using generative AI (GenAI). To test the hypothesis, this study first collects pairwise day-and-night SVIs across four cities diverged in urban landscapes to construct a comprehensive day-and-night SVI dataset. It then trains and validates a day-to-night (D2N) model with fine-tuned brightness adjustment, effectively transforming daytime SVIs to nighttime ones for distinct urban forms tailored for urban scene perception studies. Our findings indicate that: (1) the performance of D2N transformation varies significantly by urban-scape variations related to urban density; (2) the proportion of building and sky views are important determinants of transformation accuracy; (3) within prevailed models, CycleGAN maintains the consistency of D2N scene conversion, but requires abundant data. Pix2Pix achieves considerable accuracy when pairwise day–and–night-night SVIs are available and are sensitive to data quality. StableDiffusion yields high-quality images with expensive training costs. Therefore, CycleGAN is most effective in balancing the accuracy, data requirement, and cost. This study contributes to urban scene studies by constructing a first-of-its-kind D2N dataset consisting of pairwise day-and-night SVIs across various urban forms. The D2N generator will provide a cornerstone for future urban studies that heavily utilize SVIs to audit urban environments. Full article

This article focuses on the influence of Western progressive rock music on some innovative members of the Union of Soviet Composers, who were open to new trends and influences. These Soviet composers’ interest in progressive rock was not only intellectual, but also had serious practical implications. During the 1970s, several composers made attempts to create original works following various styles of prog rock. Occasionally, they incorporated elements of prog rock into their otherwise experimental compositions. One can see the influences of prog rock in the works of prominent composers such as A. Pärt, S. Gubaidulina, V. Martynov, V. Silvestrov, V. Artemiev, G. Kancheli, and A. Schnittke. After discussing the development of the prog rock tradition in the USSR and dwelling on the peculiarities of prog rock as a genre, I focus on three works created by Soviet composers under the influence of prog traditions: the 4th Symphony for orchestra and rhythm section by Latvian composer Imants Kalniņš, which follows the traditions of symphonic rock; an avant-garde rock opera titled “Flemish Legend” by Leningrader Romuald Grinblat, written to the lyrics by dissident bard Yulii Kim and heavily influenced by the twelve-tone system; and a suite of art-rock songs titled “On the Wave of My Memory” composed by pop composer David Tukhmanov, based on the poems of poets with a “decadent” reputation in the Soviet ideological context. All of these composers had to create within the Soviet ideological restrictions on modern and rock music, in particular, and all of them had to engage in their own trickster-like antics to produce and perform their works. Although they are little remembered today, these works stand as unexpected and singular achievements of Soviet composers during complex times. Full article

The vasoactive peptide bradykinin (BK) is an important member of the renin–angiotensin system. Its discovery is tightly interwoven with snake venom research, because it was first detected in plasma following the addition of viper venom. While the fact that venoms liberate BK from a serum globulin fraction is well described, its destruction by the venom has largely gone unnoticed. Here, BK was found to be cleaved by snake venom metalloproteinases in the venom of Echis ocellatus, one of the deadliest snakes, which degraded its dabsylated form (DBK) in a few minutes after Pro7 (RPPGFSP↓FR). This is a common cleavage site for several mammalian proteases such as ACE, but is not typical for matrix metalloproteinases. Residual protease activity < 5% after addition of EDTA indicated that DBK is also cleaved by serine proteases to a minor extent. Mass spectrometry-based protein analysis provided spectral proof for several peptides of zinc metalloproteinase-disintegrin-like Eoc1, disintegrin EO4A, and three serine proteases in the venom. Full article

This study aimed to enhance the friction and wear characteristics of materials for wind turbine sliding-bearing bushes operating under low-speed and heavy-load conditions. To this end, a high-entropy CoCrFeNiMo alloy coating was applied to the surface of 9Cr18 bearing steel, and Ni-Cr-Mo-Si alloy coating was applied to MTCrMoCu30 wear-resistant cast iron using laser cladding. The effects of varying loads on the friction and wear properties of these coatings were investigated, and the friction and wear properties were compared. Furthermore, the overall priority indices for both groups of bearing bush coatings were assessed. The findings indicated that the friction coefficient, wear quality, and wear rate of CoCrFeNiMo high-entropy alloy coating initially decreased and then increased with the increase in applied load, dominated by abrasive wear. By contrast, the friction coefficient of the Ni-Cr-Mo-Si alloy coating increased, and wear quality and wear rate initially increased and then decreased, indicating the coexistence of adhesive wear and abrasive wear. Therefore, Ni-Cr-Mo-Si alloy coating exhibited a high overall priority index and favorable friction and wear properties. Full article

Laser-directed energy deposition (DED), a metal additive manufacturing method, is renowned for its role in repairing parts, particularly when replacement costs are prohibitive. Ensuring that repaired parts avoid residual stresses and deformation is crucial for maintaining functional integrity. This study conducts experimental and numerical analyses on trapezoidal shape repairs, validating both the thermal and mechanical models with experimental results. Additionally, the study presents a methodology for creating a toolpath applicable to both the DED process and Abaqus CAE software. The findings indicate that employing a pre-heating strategy can reduce residual stresses by over 70% compared to no pre-heating. However, pre-heating may not substantially reduce final distortion. Notably, final distortion can be significantly mitigated by pre-heating and subsequently cooling to higher temperatures, thereby reducing the cooling rate. These insights contribute to optimizing DED repair processes for enhanced part functionality and longevity. Full article

Sub-critical water is an environment-friendly solvent. It is widely used for the extraction of various organic compounds. It can be used to dissolve and transport organic matter in oil shale. In this study, the conversion of oil shale was synergistically catalyzed by the addition of Fe or Ni to the Fe inherent in samples under sub-critical water conditions. Oil shale can be converted to gas, oil and residues of oil. Thermogravimetric (TG) analysis results presented that the weight loss of raw oil shale was up to 15.85%. After sub-critical water extraction, the weight loss rate of the residues was reduced to 8.41%. With the application of a metal catalyst, Fe or Ni, the weight loss of residues was further reduced to 7.43% and 6.57%, respectively. According to DTG curves, it was found that there were two weight-loss rate peaks. The decomposition process of kerogen in oil shale could be divided into two cracking processes. One is decomposed at a high velocity at around 420 °C, and another is decomposed at a low velocity at around 515 °C. Gas chromatography (GC) results of gas products indicated that Fe or Ni could contribute to producing normal alkanes, such as methane, ethane, propane, etc., which are produced by the hydrogenation of alkenes via hydrogen transfer during the conversion process of kerogen. Gas chromatography-mass spectrometry (GC–MS) was conducted to analyze the components of the liquid products. The results showed that n-alkanes, iso-alkane, oxygenated hydrocarbons and aromatic compounds were the major components of the kerogen cracking products. When Ni was introduced as a catalyst, the contents of aromatic compounds and oxygenated hydrocarbons in the liquid products were increased from 19.55% and 6.87% to 22.38% and 13.77%, respectively. This is due to the synergistic effect of the addition of Ni with the inherent Fe in oil shale under sub-critical water which ensures kerogen is more easily cracked to produce aromatic compounds and oxygenated hydrocarbons. Full article

Utilizing a laboratory model test, this study seeks to evaluate the distribution patterns of volumetric moisture content, soil pressure, and pore water pressure within the body of a red mud dam, given varying initial conditions of slope types and ratios, during continuous heavy rainfall. The objective is to investigate the failure mechanisms of a red mud dam under distinct operational conditions during rainfall, thereby offering insights for landslide prevention and ensuring dam construction quality. The results suggest that a stepped red mud dam acts as a buffer platform, altering the seepage direction within the dam and minimizing the water seepage path. When the slope ratio is 1:1, the transient saturated zone is located on the slope face of the dam’s body, near the top of the slope, with the saturation time at the first monitoring point occurring 300 s earlier than in a dam with a slope ratio of 1:2. Rainfall affects the distribution of internal forces in the red mud dam body. After rainfall, in the transient saturated zone of the stepped dam body, vertical soil pressure decreases 25% and horizontal soil pressure decreases 6.5%; in the transient saturated zone of the dam with a slope ratio of 1:1, vertical soil pressure decreases 14.8% and horizontal earth pressure decreases 29%; in the transient saturated zone of a dam with a slope ratio of 1:3, the change in soil pressure is small. Full article

Based on an adaptive neural control scheme, this paper investigates the consensus problem of random Markov jump multi-agent systems with full state constraints. Each agent is described by the fractional-order random nonlinear uncertain system driven by random differential equations, where the random noise is the second-order stationary stochastic process. First, in order to deal with the unknown functions with Markov jump parameters, a radial basis function neural network (RBFNN) structure is introduced to achieve approximation. Second, for the purpose of keeping the agents’ states from violating the constraint boundary, the tan-type barrier Lyapunov function is employed. By using the stochastic stability theory and adopting the backstepping technique, a novel adaptive neural control design method is presented. Furthermore, to cope with the differential explosion problem in the design course, the extended state observer (ESO) is developed instead of neural network (NN) approximation or command filtering techniques. Finally, the exponentially noise-to-state stability in the mean square is analyzed rigorously by the Lyapunov method, which guarantees the consensus of the considered multi-agent systems and all the agents’ outputs are bounded in probability. Two simulation examples are provided to verify the effectiveness of the suggested control strategy. Full article

Image restoration under adverse weather conditions poses a challenging task. Previous research efforts have predominantly focused on eliminating rain and fog phenomena from images. However, snow, being another common atmospheric occurrence, also significantly impacts advanced computer vision tasks such as object detection and semantic segmentation. Recently, there has been a surge of methods specifically targeting snow removal, with the majority employing visual Transformers as the backbone network to enhance restoration effectiveness. Nevertheless, due to the quadratic computations required by Transformers to model long-range dependencies, this significantly escalates the time and space consumption of deep learning models. To address this issue, this paper proposes an efficient snow removal Transformer with a global windowing network (SGNet). This method forgoes the localized windowing strategy of previous visual Transformers, opting instead to partition the image into multiple low-resolution subimages containing global information using wavelet sampling, thereby ensuring higher performance while reducing computational overhead. Extensive experimentation demonstrates that our approach achieves outstanding performance across a wide range of benchmark datasets and can rival methods employing CNNs in terms of computational cost. Full article

Under the backdrop of China’s national strategy to achieve carbon neutrality by 2060, efforts are underway across governmental, corporate, societal, and individual sectors to actively explore energy-saving renovations in existing buildings. Given that residential buildings constitute a significant proportion of the total energy consumption throughout the lifecycle of buildings in China, sustainable renovation of residential structures can contribute significantly to implementing China’s carbon emission reduction policies. While there exists a plethora of technological means in the market aimed at improving the energy performance of residential buildings, there still needs to be a more systematic discussion on the framework for sustainable renovation of existing Chinese residential buildings, with knowledge dissemination still needing to be more cohesive. In this context, this paper provides a comprehensive review of the field, utilizing bibliometric methods. Through a systematic review of selected peer-reviewed literature from the Web of Science and Scopus databases, the study focuses on the sustainable renovation of existing Chinese residential buildings, categorizing the process into three main stages: sustainable renovation, building performance simulation and suitability assessment. The paper also reviews the research methods adopted by previous researchers in the renovation, simulation and assessment stages, considering various optimization algorithms, variables, objectives, and software tools. Subsequently, the paper synthesizes a research framework comprising these three stages combined for different research objectives, aiming to assist policymakers, designers, and researchers in gaining a comprehensive understanding of the implementation status of sustainable renovation in existing Chinese residential buildings, identifying barriers to implementation, and formulating more efficient renovation policies and strategies for the future. Full article

Regenerated water serves as a supplementary source for circulating cooling water systems, but it often fosters microbial growth within pipelines. Given its widespread use as a corrosion inhibitor, understanding HEDP’s efficacy in microbial environments and its impact on microorganisms is imperative. This study established an iron bacterial system by isolating and enriching iron bacteria. Through a comprehensive approach incorporating corrosion weight loss analysis, XPS analysis, SEM electron microscopy, as well as microbial and electrochemical testing, the corrosion inhibition behavior and mechanism of HEDP within the iron bacterial system were investigated. The findings reveal that within the iron bacterial system, HEDP achieves a corrosion inhibition rate of 76% following four distinct stages—weakening, strengthening, stabilizing, and further strengthening—underscoring its robust corrosion inhibition capability. Moreover, HEDP enhances the density of biofilms and elevates the activation energy of carbon steel interfaces. It alternates with oxygen to continuously suppress the activity of IRB while gradually inhibiting the activity of IOB. This process culminates in a corrosion inhibition mechanism where cathodic inhibition predominates, supported by anodic inhibition as a complementary mechanism. Full article

Background: As a result of demographic change, chronic and oncological diseases are gaining importance in the context of public health. Palliative care plays a crucial role in maintaining the quality of life of those affected. International guidelines demand access to palliative care not only for the elderly but also for younger people who face severe illnesses. It can be assumed that palliative care will become increasingly important for them. In order to develop public health strategies which are able to promote palliative care, it is important to assess the knowledge of, and attitude towards, palliative care as found among members of the general public and its specific target groups. In particular, little is known about young adults’ knowledge and perceptions of palliative care. Objectives and design: This work aimed to assess the understanding and viewpoints regarding palliative care among the general population and among young adults aged 18 to 24. We therefore conducted a systematic review, which, for this target population, could be seen as a novel approach. Methods: Exclusion and inclusion criteria were developed using the PICOS process. Literature was researched within MEDLINE (via PubMed), Google Scholar and Web of Science. A search string was developed and refined for all three databases. Grey literature was included. Duplicates were excluded using Mendeley. The literature was independently screened by two researchers. Narrative synthesis was used to answer the main research question. Results: For the general public, palliative care is still associated with death and dying and comforting sick people towards the end of their lives. Multiple social determinants are linked to better knowledge of palliative care: higher education, higher income, female gender, having relatives that received palliative care, and permanent employment. The population’s knowledge of palliative care structures increases, the longer such structures have been established within a country. Young adults are familiar with the term palliative care, yet their understanding lacks nuance. They associate palliative care with death and dying and perceive palliative care to be a medical discipline primarily for the elderly. Nevertheless, young adults demand participation within the planning of interventions to destigmatize palliative care. Conclusions: The general public still lacks a detailed understanding of palliative care. Palliative care faces stigma at multiple levels, which creates barriers for those who set out to implement it. However, addressing young adults as a crucial peer group can help break down barriers and promote access to palliative care. Full article