Search Results (16,891)

Information asymmetry between complex source texts and general-audience comprehension remains a critical challenge in Artificial Intelligence. However, existing supervised simplification methods suffer from the scarcity of parallel training data, while standard text summarization methods often discard essential details to reduce length. Furthermore, zero-shot large language models frequently lack fine-grained controllability over linguistic complexity. To address these technical limitations, we present a framework to resolve information asymmetry by casting text simplification as a controllable denoising language modeling task. Unlike summarization, our approach preserves full semantic coverage while reducing difficulty. Our algorithm targets the problem of identifying and rewriting complex spans without labeled data through three mechanisms: (1) Asymmetry-Aware Masking, which uses model-based reconstruction difficulty (Negative Log-Likelihood) to isolate high-complexity terms; (2) paraphrase context prompting to enforce semantic invariance; and (3) an adaptive decoding strategy that dynamically penalizes complex tokens based on input difficulty. On ASSET (Abstractive Sentence Simplification Evaluation and Tuning dataset), our best setting reaches SARI (System output Against References and against the Input) 42.90 with FKGL (Flesch–Kincaid Grade Level) 7.10 (Sentence Similarity 0.948), and performs consistently on TurkCorpus (SARI 41.10), while requiring no parallel data or fine-tuning. Full article

Background: Digital implant impressions using intraoral scanners are increasingly adopted; however, their accuracy remains challenging in complete-arch and extended edentulous scenarios due to limited anatomical reference points and cumulative stitching errors. Various splinting techniques, scan-body modifications, and auxiliary geometric devices have been proposed to enhance digital accuracy, yet the available evidence is highly heterogeneous and lacks comprehensive synthesis. Methods: This scoping review was conducted according to PRISMA-ScR guidelines. A systematic search of PubMed/MEDLINE, Embase, Scopus, and Web of Science databases identified studies evaluating materials, designs, or techniques intended to splint, stabilize, or geometrically augment intraoral scan bodies in digital implant workflows. In vitro, clinical, and mixed-design studies were included. Data were extracted descriptively and synthesized narratively. Results: Seventy-three studies met the inclusion criteria, the majority of which were in vitro investigations focused on fully edentulous arches. Splinting strategies included direct resin-based connections, rigid or semi-rigid auxiliary geometric devices, modified scan bodies with extensional geometries, and artificial landmarks. Most studies reported improved trueness, precision, or scanning efficiency when rigid or geometrically enriched devices were used, particularly in long-span or angulated implant configurations. However, flexible or optically interfering splints occasionally reduced accuracy, and outcomes were strongly scanner-dependent. Conclusions: Splinting and auxiliary scanning strategies generally enhance the accuracy of complete-arch digital implant impressions, especially when rigid, well-engineered, or geometrically complex designs are employed. Modified scan bodies and calibrated auxiliary devices appear particularly promising, while flexible splints may be counterproductive. Standardized protocols and further in vivo validation are required to optimize digital implant workflows. Full article

Intergenerational wealth transfer represents a central mechanism through which genealogical bonds, family continuity, and economic stability are maintained across generations. This article examines inheritance law and financial regulation from a genealogical perspective, focusing on the role of family property as both a legal institution and a socio-economic structure rooted in kinship and lineage. By integrating approaches from genealogy, legal studies, and financial analysis, the study explores how inheritance frameworks shape intergenerational relations, preserve family identity, and influence patterns of economic inequality. The article analyzes inheritance law as a key instrument through which genealogical continuity is institutionalized, highlighting the ways in which legal norms regulate the transmission of assets, rights, and obligations within families. Particular attention is given to the interaction between financial regulation and family-based wealth, demonstrating how legal structures affect long-term economic sustainability and social cohesion. The study adopts a qualitative and theoretical methodology, supported by comparative references to selected legal traditions, in order to illustrate how inheritance systems reflect broader cultural, historical, and genealogical values. By situating inheritance and wealth transfer within the broader framework of genealogical relations, this article contributes to interdisciplinary discussions on family, law, and the economy. It argues that inheritance law should be understood not merely as a financial or legal mechanism, but as a genealogical process that shapes intergenerational bonds, social structures, and economic outcomes over time. Full article

Fourier Decomposition (FD) and Koopman Mode Decomposition (KMD) are important tools for time series data analysis, applied across a broad spectrum of applications. Both aim to decompose time series functions into superpositions of countably many wave functions, with strikingly similar mathematical foundations. These methodologies derive from the linear decomposition of functions within specific function spaces: FD uses a fixed basis of sine and cosine functions, while KMD employs eigenfunctions of the Koopman linear operator. A notable distinction lies in their scope: FD is confined to periodic functions, while KMD can decompose functions into exponentially amplifying or damping waveforms, making it potentially better suited for describing phenomena beyond FD’s capabilities. However, practical applications of KMD often show that despite an accurate approximation of training data, its prediction accuracy is limited. This paper clarifies that this issue is closely related to the number of wave components used in decomposition, referred to as the degree of a KMD. Existing methods use predetermined, arbitrary, or ad hoc values for this degree. We demonstrate that using a degree different from a uniquely determined value for the data allows infinite KMDs to accurately approximate training data, explaining why current methods, which select a single KMD from these candidates, struggle with prediction accuracy. Furthermore, we introduce mathematically supported algorithms to determine the correct degree. Simulations verify that our algorithms can identify the right degrees and generate KMDs that can make accurate predictions, even with noisy data. Full article

Background/Objectives: Residents of high-altitude regions are chronically exposed to hypoxic and cold environments, which may alter energy metabolism and nutritional requirements, leading to distinct macronutrient intake patterns. However, existing evidence remains fragmented. This systematic review aimed to summarize macronutrient and energy intake among high-altitude populations and compare reported intake levels with dietary reference values to identify potential nutritional risks. Methods: A systematic search of PubMed and Web of Science was conducted for studies published between January 1990 and March 2025. Observational studies reporting dietary intake or dietary patterns among populations living at altitudes of ≥1500 m were eligible. Two reviewers independently screened studies, extracted data, assessed study quality using standardized tools, and synthesized results narratively. Study quality was assessed using the Quality Assessment Tool for Studies with Diverse Designs (QATSDD), with studies scoring ≥60% of the maximum score considered to indicate moderate or higher methodological quality. This review was not registered. Results: A total of 14 studies were included. Energy intake was generally within or close to recommended levels, with suboptimal intake observed in specific regions and population groups. Carbohydrate intake remained high, reflecting grain-based diets, while protein intake usually met or exceeded recommendations. Fat intake showed an increasing trend, particularly among pregnant and lactating women. Several studies reported emerging “modern” dietary patterns characterized by higher consumption of meat, fats, and processed foods, alongside limited dietary diversity. Conclusions: Overall, high-altitude populations exhibit distinctive macronutrient profiles shaped by environmental adaptation and nutritional transition, underscoring the need for altitude-specific dietary guidance and targeted public health interventions. Full article

Earthworms are widely used as biological indicators of soil contamination and are often referred to as the ‘intestine of the soil’; however, their effectiveness can vary across regions and environmental conditions. The performance of earthworms as indicators of soil pollution may vary among regions, and there is a need to assess their reliability under specific environmental conditions. So, in this study, soil and earthworm samples were collected from 19 locations across Punjab, Pakistan, to assess heavy metal pollution and bioaccumulation using geoaccumulation indices (Igeo) and bioaccumulation factors (BAF). Soil and earthworm tissues were digested and analyzed for heavy metals such as Sr, Zn, Ca, Cu, Fe, Mn, Co, Cr, Pb, Cd and Ni using ICP-MS. According to Igeo, cadmium frequently classified soils as strongly to extremely polluted, with values up to 4.5 in Bahawalnagar, whereas most other metals fell within the unpolluted to moderately polluted classes. Earthworms showed clear bioaccumulation (BAF > 1) for several essential or poorly regulated elements, particularly Ca, Mn, Cu and Sr; the maximum BAF for Ca reached 8.18 in Faisalabad. In contrast, group-1 carcinogenic metals (Pb, Cd and Cr) generally did not exhibit strong bioaccumulation. Relationships between BAF and soil metal concentrations or abiotic properties (moisture, pH, electrical conductivity, total dissolved and suspended solids) were generally weak (R² typically ≤ 0.32), indicating that these factors explain only a modest fraction of the variation in metal uptake. Overall, the results highlight cadmium as the primary soil contamination risk in the surveyed areas. Because bioaccumulation showed weak relationships with soil metal concentrations and physicochemical parameters, earthworms in this study demonstrated limited effectiveness as bioindicators of toxic heavy metal accumulation. The limited internal accumulation of highly toxic metals suggests possible physiological regulation or tolerance, although the long-term ecological implications require further investigation. Further controlled studies are necessary to better evaluate their ecological role and potential applications in soil remediation, waste management, and vermicompost production. Full article

Background: Access to affordable essential medicines is critical for effective management of hypertension (HTN) and diabetes mellitus (DM). In Zimbabwe, frequent stock-outs in public facilities position private pharmacies as important alternative sources of these medicines. Aim: To assess availability, pricing, and stock-out levels of essential HTN and DM medicines in private retail pharmacies in Gweru Urban District, Zimbabwe. Methods: A cross-sectional survey was conducted in 40 registered private pharmacies. Data on medicine availability, retail prices, monthly stock-outs, and supply-chain factors were collected using a structured interviewer-administered questionnaire, stock cards, and observational checklists. Local prices were compared with international reference prices (IRPs). Chi-square analyses evaluated associations between pharmacy characteristics, medicine prices, availability, and stock-out durations. Results: Most tracer medicines for HTN and DM were available in ≥80% of pharmacies, with average stock-outs generally <3 days per month. Pharmacy characteristics were not significantly associated with availability or stock-outs. Medicines with <80% availability and those priced at ≥USD 5 were significantly associated with prolonged stock-outs of ≥7 days (p = 0.006 and p = 0.001, respectively). Local retail prices exceeded IRPs and public facility prices, suggesting potential affordability barriers in the context of an economic crisis, where most health expenditures are out-of-pocket. Key drivers of stock-outs included wholesaler shortages, delivery delays, limited procurement funds, and substitution with alternative medicines. Conclusions: While medicine availability and short-term stock-outs were generally favourable, high retail prices pose a major potential barrier to access. The cost burden is amplified by the common HTN-DM comorbidity, requiring multiple medications per person, thereby further increasing out-of-pocket expenses. High prices may limit adherence, reduce functional capacity, and negatively impact productivity. Policy interventions targeting pricing regulations and value-chain optimization are urgently needed to enhance equitable access to essential NCD medicines in urban Zimbabwe. Full article

Background: The coexistence of antibiotic resistance genes (ARGs) and heavy metals in livestock manure poses critical challenges to vermicomposting technology. Objectives: This study aimed to clarify the zinc (Zn)-driven ARG dynamics over 60-day vermicomposting for livestock manure and provide a reference for taking appropriate measures to reduce the spread of ARGs in the environment. Methods: In a vermicomposting system using Eisenia fetida and treated with varying concentrations of Zn, high-throughput sequencing was employed to analyze microbial succession, while quantitative real-time PCR (qPCR) was performed to track the fluctuation patterns of ARG (tet-, erm-, qnr-, str-, chl-, bla-, mcr-ARGs) and mobile genetic element (MGE, intI1 and intI2) abundances over the 60-day treatment period. Results: Generally, sul- (10⁻³–10⁻¹ copies/16S rRNA), tet- (10⁻³–10⁻² copies/16S rRNA), and str-ARGs (10⁻³–10⁻² copies/16S rRNA) are dominant in dairy manure. Vermicomposting significantly reduced total ARGs (88.62% removal), but Zn stress triggered concentration-dependent shifts. Low Zn (100–250 mg/kg) elevated tet-, erm-, and chl-ARGs via co-selective pressure and disrupted bacterial succession, while high Zn (500–1000 mg/kg) suppressed qnr- and mcr-ARGs but intensified horizontal transfer via cross-resistance. Conclusions: Vermicomposting maintained a greater ARG removal capacity across the Zn gradient (100–1000 mg/kg) than natural composting, proving an effective approach for reducing the threat of antibiotic resistance in bacteria even under high Zn stress. The link between Zn residues and the increased ARG dissemination risks underscores the challenge of co-contaminants, providing essential insights for developing vermicomposting strategies to mitigate ARG risks and ensure sustainable manure management. Full article

Photovoltaic (PV) systems are subject to nonlinear performance degradation caused by operational and environmental factors, which limits reliable energy production. Most existing studies focus on power output forecasting and fail to isolate intrinsic efficiency losses from meteorological variability. This study proposes a degradation-aware deep learning framework for predicting PV performance loss using multi-sensor time-series data. Performance degradation is formulated as a reference-based performance loss ratio derived from the deviation between observed power output and an ideal physics-informed reference model. A hybrid convolutional neural network (CNN) and long short-term memory (LSTM) architecture is employed to jointly capture local feature representations and long-term temporal degradation dynamics. Model evaluation is conducted using a synthetically generated yet physically consistent dataset, informed by real PV measurements to ensure real-world relevance. Experimental results demonstrate that the proposed CNN–LSTM model outperforms baseline approaches, including persistence, linear regression, and XGBoost, particularly in terms of mean absolute error (MAE) and normalized root mean square error (RMSE). Additional analyses confirm stable error behavior and temporal generalization, highlighting the suitability of the proposed approach for degradation-aware performance monitoring and predictive maintenance in PV systems. Full article

The purpose of this study is to investigate the impact of new-type urbanization on land use efficiency and its spatial spillover effects, aiming to provide theoretical support and practical references for improving land resource allocation and optimizing regional development strategies. Using panel data from 61 counties in Zhejiang Province between 2010 and 2022, this research applies a two-way fixed effects model, supplemented by mediation effect analysis and spatial econometric models, to empirically examine these relationships. The results indicate that: (1) both the level of new-type urbanization and land use efficiency show an overall upward trend, exhibiting a spatial pattern characterized by “coastal regions outperforming inland areas, and northern Zhejiang surpassing the south”; (2) new-type urbanization exerts a significantly positive impact on land use efficiency, with industrial structure upgrading serving as a partial mediator in this relationship; (3) significant spatial spillover effects are observed—new-type urbanization not only enhances local land use efficiency but also generates positive spillovers to neighboring regions through spatial diffusion mechanisms; (4) the influence of new-type urbanization on land use efficiency displays regional heterogeneity, with stronger promoting effects observed in coastal and low-efficiency areas, whereas marginal effects diminish in non-coastal and high-efficiency regions. In conclusion, strategic priorities should be established to enhance the quality of new-type urbanization, foster green and intensive development, optimize the industrial structure, and strengthen land conservation practices. Furthermore, region-specific policies are essential to improve land use efficiency across diverse areas, which will ultimately contribute to coordinated regional development. Full article

Facial profile esthetics play a pivotal role in orthodontic diagnoses, treatment planning, and patient satisfaction; however, the perception of facial attractiveness is inherently subjective and varies according to professional expertise and sociocultural background. This study aimed to compare the perceived attractiveness of standardized sagittal facial profiles across skeletal Class I, II, and III patterns and to investigate the influence of professional training and sociodemographic variables on facial profile evaluations. It was hypothesized that straight facial profiles would be perceived as the most attractive across all observer groups, while deviations from the orthognathic profile would be rated as less attractive, with significant differences based on professional training and sociodemographic variables. This cross-sectional descriptive study included 509 participants, comprising orthodontists, orthodontic Ph.D. students, general dentists, specialist dentists, first- and fifth-year dental students, and laypersons. Seven standardized sagittal facial profile silhouettes (S1–S7) were digitally generated from a standardized lateral facial photograph and evaluated using a seven-point visual analog scale. Participants were also asked to identify the sagittal facial profile range (S8) they ideally preferred to possess. Intergroup comparisons were performed using non-parametric statistical tests (Mann–Whitney U and Kruskal–Wallis). The straight profile (S3) emerged as the most attractive and most frequently preferred across all participant groups, confirming its role as the dominant esthetic reference. Retrusive profiles, particularly bimaxillary retrusion (S2), mandibular retrognathism (S5), and maxillary retrusion (S6), were consistently rated as the least attractive. Significant differences in esthetic perceptions were observed according to the professional expertise, educational level, age, and nationality, whereas gender had no clinically meaningful effect. Orthodontic training was associated with increasingly critical evaluations, especially for protrusive and convex profiles, while laypersons demonstrated greater esthetic tolerance. Both anatomical characteristics and sociocultural experience shape the perception of facial profile esthetics. While the straight profile represents a widely shared aesthetic ideal, increasing orthodontic expertise accentuates discrepancies between professional standards and public preferences. These findings underscore the necessity of integrating patient-centered and culturally sensitive considerations into contemporary orthodontic treatment planning. Full article

Background: Haemoglobinopathies such as beta-thalassemia (β-thal), alpha-thalassemia (α-thal) and sickle cell disease (SCD) are characterised by pathogenic gene variations (mutations) in the globin genes. Patients with haemoglobinopathies have the same disease-causing coding variations with very different disease phenotypes, from requiring blood transfusions to being non-symptomatic. The gap between the expected clinical outcomes based on primary coding mutations (the genotype) and the actual observed symptoms (the phenotype) often remains unexplained. We refer to the contribution of secondary genetic modifiers—specifically, non-coding variants of the genome that alter globin gene expression and pathophysiology—as the “missing heritability” of the clinical presentation [Primary Mutation + Missing Heritability (Non-Coding Variants) = Actual Clinical Phenotype]. Objectives: This systematic review aims to find evidence connecting genetic differences outside of the protein-coding region, as in promoters, enhancers or untranslated regions (UTRs), to the clinical severity (phenotype) of beta-thalassemia, alpha-thalassaemia and SCD. We summarise the molecular basis of phenotypic variation among haemoglobinopathy patients with identical variations to reveal their missing heritability and to enhance our understanding of prognostic strategies. Methods: This systematic review was performed in accordance with the PRISMA 2020 guidelines. We used search terms related to haemoglobinopathies, non-coding variation, SNP, promoters, enhancers and clinical severity to search major databases (PubMed and Google Scholar) as of October 2025. A total of 527 (out of 572) abstracts were fit for initial screening to identify the eligible reports. Due to heterogeneity in study designs and reported outcomes, findings were synthesised descriptively and grouped by variant mechanism (cis-acting and trans-acting). The final analysis included 89 articles that demonstrated a direct association between a non-coding genomic variant and a quantitative measure of clinical severity. Results: Two main groups of non-coding variants (NCVs) that modulate foetal haemoglobin (HbF) induction were identified. The first major group comprises cis-acting variants within globin gene clusters (HBG2 promoter XmnI polymorphism, HBB promoter mutations and α-globin enhancer variants), while the second major group comprises trans-acting quantitative trait loci (QTLs) (BCL11A and HBS1L-MYB loci). Non-globin NCVs in the UGT1A1 promoter were also found to influence the severity measures in β-thal and SCD. NCVs primarily alter the binding of transcription factors and the looping dynamics of chromatin, modulating the α/β chain balance ratio and γ-globin repression. The XmnI polymorphism is the most prominent cis-acting modifier associated with β-thal intermedia. The promoter polymorphisms in TNF-α and VCAM1 are associated with vascular complications in SCD. Conclusions: NCVs are fundamental when determining the clinical measures of haemoglobinopathies, in addition to coding variants. NCV screening should be integrated for clinical prognosis for the accurate prediction of haemoglobinopathy severity and associated high-risk complications. NCVs may represent promising targets for next-generation gene editing and therapeutic intervention strategies aimed at modifying the severity of β-thal, α-thal and SCD. Full article

Under rural revitalization and low-carbon development, the sustainable transformation of vernacular architecture has become an important research focus. Taking the Linpan as the research object, this study proposes an integrated design methodology that combines typological translation with ecological material logic for contemporary architectural design. The methodology decodes the Linpan spatial prototype—characterized by the “house–forest–field–water” structure—by abstracting key spatial relationships and translating them into contemporary architectural formal strategies, while incorporating locally grounded ecological materials to coordinate environmental performance and cultural continuity. The proposed approach is validated through the Daoming Zhuli project in Chengdu, where typological translation generates courtyard-centered layouts, semi-open transitional spaces, and bamboo-based envelope systems adapted to a humid subtropical climate. A scenario-based material comparison indicates that the use of local materials can significantly reduce embodied carbon emissions while reinforcing regional identity. In addition, comparative analyses of other vernacular settlements, including Huizhou ancient villages, Fujian Tulou, and Ait Benhaddou, are conducted to examine the methodological transferability across different climatic, spatial, and cultural contexts. This study contributes a design-oriented framework linking spatial typology and material selection, providing guidance for the sustainable renewal of Linpan and references for the contemporary adaptation of vernacular architecture in international contexts. Full article

Norovirus is a major cause of acute viral gastroenteritis in humans. Molecular biology-based detection methods play a pivotal role in ensuring accurate and specific diagnosis. The inclusion of Qβ phage particles as armored positive controls in these assays can further enhance their reliability and specificity. Herein, we discuss rational design strategies to improve the stability of Qβ bacteriophage capsid proteins armored with RNA using Discovery Studio 2019 protein design software. Amino acid mutation sites were deter-mined based on changes in folding free energy differences (ΔΔGmut). These single-site mutations were subsequently evaluated using molecular dynamics simulations. Wild-type and mutant recombinant expression plasmids were constructed and transformed into Escherichia coli BL21 (DE3) for cloning and expression. The stability of Qβ virus-like particles (VLPs) was assessed using real-time fluorescence RT-qPCR. The results showed that structurally intact and uniformly distributed wild-type and single-site mutant VLPs were successfully obtained. Stability analyses indicated that at 4 °C, 25 °C, 37 °C, 45 °C, and 60 °C, the single-site mutant exhibited a significantly lower rate of degradation than the wild-type. In conclusion, rational design enables the generation of single-site mutant VLPs with enhanced stability, providing a safer and more stable standard reference material for the molecular detection of foodborne viruses. Full article

Electrochemical biosensors have emerged as indispensable detection tools with rapid advancements in recent years, offering high sensitivity, specificity, and cost-effectiveness for quantifying diverse analytes, including amino acids, proteins, pathogens, cells, antigens, and organic/inorganic compounds, thereby advancing analytical detection technologies across multiple fields. Aptamers, synthetic in vitro-evolved ligands with exceptional binding affinity and stability, serve as superior biorecognition elements for electrochemical sensing interfaces. Compared with other bioreceptors such as antibodies, they are generally easier and faster to produce, more uniform between batches, and easier to modify chemically; they also maintain greater stability than protein antibodies or enzymes across varying pH, temperature, and ionic conditions, enabling targeted recognition and measurable signal transduction. This review systematically summarizes recent advances in electrochemical aptasensors across three core domains: biomedical diagnostics (covering tumor markers, infectious disease pathogens, cardiovascular and metabolic biomarkers), food safety monitoring (targeting antibiotics, mycotoxins, foodborne pathogens, and pesticide residues), and environmental hazard detection (including heavy metals, toxic compounds, and biotoxins). Key technological innovations such as nanomaterial modification, signal amplification strategies, and novel sensor architectures are highlighted. Additionally, it critically discusses prominent challenges, including complex matrix interference, limited aptamer repertoires, poor reproducibility, and lack of standardization, along with future prospects. This work aims to provide a comprehensive reference for the rational design, optimization, and clinical/field application of next-generation electrochemical aptasensing technologies. Full article