Search Results (147)

Guineagrass (Megathyrsus maximus), a key tropical forage species, presents breeding constraints due to apomixis, polyploidy and a narrow sexual gene pool. This study quantified the genetic architecture of biomass and forage quality traits and identified apomictic testers using an incomplete North Carolina II mating design. A total of 175 F₁ families derived from 27 sexual female parents and nine apomictic male parents were evaluated. Agronomic traits were evaluated across three contrasting environments in Colombia, whereas nutritional quality traits were assessed in one location. Mixed models were used to estimate variance components, combining ability, heritability, and genetic interactions with locations. General combining ability accounted for 58.6% to 80.1% of the main genetic variance depending on the trait. Full-sib family mean broad-sense heritability was high for agronomic traits (H²_FS = 0.89–0.95) and moderate for nutritional quality traits (H²_FS = 0.56–0.66), supporting selection at the family level. Male half-sib family mean heritability was consistently high, indicating reliable estimation of apomictic tester effects. Mombaça (CIAT_6962) was the most consistent productivity tester, whereas CIAT_6799 and CIAT_6986 showed favorable predicted effects for nutritional quality traits under Palmira Location. These results provide a quantitative basis for recurrent selection using testers and family validation in guineagrass breeding. Full article

Industrial polypropylene portfolios comprise multiple commercial grades differentiated by molecular architecture, phase morphology, processability, and performance. In this study, 81 industrial polypropylene grades, including 38 homopolymers, 21 random copolymers, and 22 impact copolymers, were analyzed to evaluate the chemometric organization and structure–property relationships of a complete commercial portfolio. The dataset integrated melt flow index, xylene-soluble fraction, total ethylene content, ethylene content of the rubber phase, rubber-phase fraction, and mechanical, thermal, and optical performance variables obtained from routine industrial quality-control and product-certification activities. Principal component analysis, partial least squares discriminant analysis, and variable importance in projection analysis were used to examine portfolio organization, evaluate consistency with the predefined polypropylene families, and identify the descriptors contributing most strongly to family-level discrimination. The first two principal components explained 83.8% of the total variance. They revealed a low-dimensional organization consistent with the molecular and morphological differences among homopolymer, random copolymer, and impact copolymer grades. The full-descriptor PLS-DA model achieved 98.8% cross-validated accuracy and correctly classified 80 of the 81 grades using two latent variables. This performance reflects the internal consistency between the descriptor matrix and the existing industrial family classification rather than independently validated predictive capability for unknown grades. Homopolymer differentiation was mainly associated with molecular-weight-related flow behavior, random copolymer organization with ethylene-induced modification of crystallinity, and impact copolymer differentiation with heterophasic rubber-phase characteristics. The results provide a portfolio-specific chemometric workflow for grade organization and structure–property interpretation. However, the numerical domain boundaries and their transferability require validation using independent polypropylene portfolios from other producers. Full article

Renewable-powered agricultural water systems are often assessed as solar-pumping devices, but their sustainability depends on a service chain linking crop-water demand, hydraulic duty point, power electronics, storage, water quality, governance, operation and end-of-life management. This structured integrative review synthesizes peer-reviewed and practice-oriented evidence on photovoltaic pumping, hybrid renewable irrigation, grid-interactive pumps, micro-hydro assistance and renewable-powered brackish-water reverse osmosis (PV-RO). Evidence was screened across four source families and coded by service function, energy architecture, hydraulic duty and dominant sustainability pathway; recurring combinations were consolidated using explicit separation and merge rules. It develops an archetype-based screening framework for ex ante appraisal of irrigation, desalination and circularity risks. Seven technology-service archetypes are identified: direct PV pumping, PV-to-tank pumping, PV with electrical buffering, grid-interactive PV pumping, PV–wind hybrid irrigation, micro-hydro-assisted irrigation and PV-RO water making. The framework links each archetype to its operating envelope, evidence maturity, enabling subsystems, sustainability pathways, minimum indicators and ordinal triggers for deeper due diligence. Hydraulic storage is usually the lowest-regret reliability buffer for open-field irrigation, whereas batteries are justified mainly when pressure stability, fertigation timing or night-time operation has high agronomic value. PV-RO is a distinct water-making archetype and is environmentally defensible only where feed-water characterization, energy recovery, pretreatment, product-water agronomy, membrane management and permitted concentrate disposal are embedded in design. Two synthetic applications demonstrate archetype selection and due-diligence escalation. Responsible deployment requires service-oriented screening that integrates hydraulic design, groundwater governance, procurement quality assurance, circularity obligations and social inclusion before field implementation. Full article

Among the vast array of technologies available for surface modification of materials, sputtering emerges as one of the most versatile methods through coating deposition. Included in the family of physical vapor deposition (PVD) techniques, sputtering allows the production of coatings with a great variety of characteristics, based on a bottom-up approach that forms coatings from individual species (atoms or ions). This versatility is achieved by controlling: (i) the layer architecture, from monolithic to multilayers, (ii) the structures, from amorphous to nanocrystalline or nanocomposite, until highly crystallized, including epitaxial; (iii) the morphologies, from very porous through columnar or zig-zag to very dense and featureless; (iv) the chemical composition, allowing the deposition of metallic, polymeric, ceramic or composite materials types. In this paper, after a brief introduction of sputtering as a deposition technology, we will review the application of sputtering for depositing protective coatings to which an extra functionality is provided: (a) aesthetic color; (b) high-temperature lubrication; and (c) temperature sensing ability. Full article

Rapid estimation of the melt flow index (MFI) is essential for the timely control of industrial polypropylene polymerization because conventional plastometer measurements require offline sampling and introduce analytical delays. This work investigates the physicochemical limits of MFI model transferability using 425 reactor-grade polypropylene production runs spanning homopolymer, random copolymer, and impact copolymer architectures. Principal component analysis (PCA), partial least squares (PLS), PCR-Ridge, Random Forest, Extra Trees, and Gradient Boosting were evaluated using within-pool, repeated five-fold, and product group validation. The latent structure, predictive performance, and dominant process descriptors were strongly architecture-dependent. Hydrogen-related variables remained central to molecular weight control, whereas comonomer descriptors, catalyst and donor variables, hydrodynamic conditions, and second reactor variables gained importance as compositional and morphological complexity increased. Nonlinear ensembles improved prediction within heterogeneous pools, but product group validation still revealed transferability losses when models crossed architecture-dependent process–structure–property domains. Repeated cross-validation and preprocessing sensitivity analyses confirmed that the principal model rankings and architecture-dependent conclusions were stable under resampling and correlation filtering. These results show that the polymer architecture defines a practical applicability boundary for industrial MFI soft sensors and supports architecture-specific or architecture-routed calibration when universal models fail cross-family validation. Full article

Apartment floor plans have traditionally been interpreted through qualitative typological readings, but coded floor-plan datasets now enable reproducible quantitative analysis. This article examines architectural metadata from apartment units in Aurinkolahti, Helsinki, Finland, to explore typological repetition, spatial compactness, and selected indicators of domestic spatial quality. Rather than reconstructing full apartment geometries, the study treats each mapped layout as an architectural metadata record and distinguishes it from the number of built apartments represented by that layout. This stock-sensitive distinction allows repeated floor plans to be analyzed as components of housing production, not merely as individual cases. The workflow includes data cleaning, classification-coverage assessment, weighted and unweighted summaries, temporal grouping, compactness metrics, repetition indicators, kitchen-related quality markers, exploratory clustering, and statistical modeling. Results show typological concentration around a limited number of layout families and identify the 2021–2023 period as combining smaller weighted mean floor areas, higher repetition intensity, and lower kitchen natural-light shares. Coded floor-plan metadata are therefore positioned as a limited but useful intermediate form of architectural evidence: more structured than visual typological description, but not a substitute for direct plan analysis or comprehensive housing-quality assessment. Full article

Designers, engineers, and building officials face increasing pressure to accelerate and improve the accuracy of design review for buildings and infrastructure. Roof assemblies and rooftop structures are particularly challenging due to the complexity and fragmentation of regulatory requirements, especially in jurisdictions such as Florida, where compliance must be verified across both the residential and commercial volumes of the Florida Building Code (FBC). The resulting review process is technically demanding and time-intensive, imposing significant cognitive and operational burdens on practitioners and under-resourced public agencies. To address these challenges, this study proposes and evaluates an agentic artificial intelligence (AI) framework for automated code compliance checking of roof assemblies and rooftop structures. The framework employs a multi-agent architecture in which specialized AI agents collaboratively interpret regulatory provisions and evaluate roof design parameters across four core modules: data preprocessing and code ingestion, rule-based and semantic analysis, results visualization, and iterative validation. YOLO11m-seg and Mask R-CNN were used for element detection and segmentation, and the system was developed using 150 design projects, including roof plans, section details, and specifications. Four large language models from two families (Mistral and GPT) were comparatively evaluated on standardized compliance tasks. The framework was then tested on a held-out portfolio of 15 distinct roof-design projects comprising 60 code-compliance decisions derived from the FBC 2023, with performance measured by precision, recall, F1-score, and accuracy. GPT-5.4 achieved the highest overall performance (F1 = 0.97; accuracy = 97%). Because the reasoning and vision components were evaluated separately rather than as an integrated end-to-end pipeline, and the scope was limited to one jurisdiction and two drawing types, broader code coverage and production-setting validation are needed before claims of generality. Nonetheless, the results suggest that agentic AI can meaningfully support compliance review and reduce reviewer burden in roof-design permitting. Full article

Brassica napus L. is a major oilseed crop whose productivity is significantly affected by abiotic stresses such as drought. PYR/PYL/RCAR (PYL) proteins act as key abscisic acid (ABA) receptors and play central roles in stress responses. However, a comprehensive genome-wide analysis of the PYL gene family in B. napus is still lacking, limiting our understanding of their functions in plant and stress adaptation. This study reports the first comprehensive genome-wide analysis of the PYL gene family in B. napus (rapeseed), cultivar ZS11, identifying 25 BnPYL genes grouped into four subfamilies, I (four genes), I-II (five genes), II (five genes), III (11 genes), and their encoded proteins were predicted to be mainly localized in the chloroplast. Structural analysis revealed diverse exon–intron organization and 10 conserved motifs. All identified BnPYLs contained Polyketide_cyc2 domains (PF10604), supporting their annotation as members of the PYL family. Promoter analysis identified cis-regulatory elements related to light response, stress regulation, and hormonal signaling. Computational analysis of post-translational modifications suggested that phosphorylation sites are mainly localized at serine and threonine residues. Tertiary structure modelling revealed conserved three-dimensional architectures among BnPYL proteins, suggesting potential functional conservation. Expression profiling and RT-qPCR analyses revealed that several BnPYL genes respond to ABA-mediated drought stress, with BnPYL15 and BnPYL22 exhibiting the highest induction (4–5-fold) and BnPYL2, BnPYL5, BnPYL6, BnPYL17, BnPYL18, and BnPYL25 showing significant upregulation (2.0–4.5-fold), suggesting potential roles in enhancing drought tolerance in B. napus. Full article

LLM privacy risks arise across different lifecycle stages and architectural boundaries, and existing protection mechanisms provide only partial coverage. This paper analyzes the main families of privacy-preserving approaches for LLM systems through a two-axis structure that crosses lifecycle stages with system architecture layers. Some safeguards are operationally mature; others, such as confidential computing, have moved into production practice; stronger cryptographic methods, while most promising in principle, remain research-heavy in practice. No single mechanism provides complete end-to-end protection: different methods protect different assets, operate at different lifecycle stages, span distinct system layers, and carry distinct trust, performance, and deployment trade-offs. Practical LLM privacy is therefore a problem of layered system design rather than the search for a universal primitive, and hybrid architectures are emerging as the most realistic deployable pattern. Building on this analysis, we propose a six-dimensional evaluation framework for privacy in hybrid LLM deployments (a 0–5 ordinal scoring rubric designed for reproducible application, with explicit anchor language and per-score evidence requirements) and apply it to five representative confidential AI deployments, deriving the scores in full for two of them. The framework feeds a three-tier gap-closure roadmap and design principles for architecture-time use, connecting what privacy technologies promise, what they actually protect, and what is realistically deployable in modern LLM systems. Full article

Taraxacum kok-saghyz (T. kok-saghyz) is a promising alternative crop for natural rubber production, in which root development is closely associated with rubber synthesis; however, the molecular mechanisms governing root architecture formation remain largely unclear. NAC transcription factors play pivotal roles in plant root development, yet their functions in T. kok-saghyz have not been systematically investigated. In this study, a genome-wide analysis identified 34 NAC family members in T. kok-saghyz. Through transcriptomic analysis following methyl jasmonate (MeJA) treatment, 27 genes significantly responsive to MeJA signaling were screened. Sequence analysis revealed that all TkNAC proteins contain a conserved NAM domain. Subcellular localization assays confirmed that TkNAC16, TkNAC20, TkNAC23, and TkNAC30 are localized to the nucleus. Yeast two-hybrid and bimolecular fluorescence complementation assays demonstrated that TkNAC16/18/20/23/30 can form extensive heterodimers. Overexpression lines of T. kok-saghyz exhibited significantly increased root length, while leaf growth exhibited line- and stage-specific effects. Collectively, this study provides the first systematic identification of the NAC transcription factor family in T. kok-saghyz, elucidates their involvement in methyl jasmonate signaling responses, the construction of heterodimerization networks, and the positive regulation of root elongation. These findings provide crucial genetic resources and a theoretical basis for dissecting the molecular mechanisms underlying the coordinated improvement of root development and rubber yield in T. kok-saghyz. Full article

Climate change is intensifying soil salinization, posing a major threat to crop establishment and productivity, particularly in arid and semi-arid regions. Barley (Hordeum vulgare L.), one of the most salt-tolerant cereals, offers valuable genetic resources for improving salinity resilience at early growth stages. This study exploited the genetic diversity of the Nested Association Mapping (NAM) population Halle Exotic Barley-25 (HEB-25) to dissect salinity tolerance during germination and seedling developmental stages. First, the HEB-25 parental lines (25 wild barley genotypes and cv. Barke) were evaluated under salinity treatment to identify contrasting responses. Based on this screening, four HEB families (01, 04, 09, and 22) were selected out of 25 HEB families for detailed phenotypic and genomic analysis. Seeds of the selected HEB families were subjected to 40% seawater salinity stress and control treatments to assess germination percentage and seedling traits, including shoot length, root length, fresh weight (FW), dry weight (DW), DW/FW ratio, root–shoot ratio, and salt tolerance index (STI). Substantial variation was observed among families for all measured traits under salinity stress. STI values enabled clear differentiation among families: Family 01 exhibited the most consistent overall tolerance profile, Family 22 showed the strongest sensitivity in biomass traits, and Family 04 displayed a trait-specific response with sensitivity at the family-mean level but exceptional within-family diversity, harboring some of the highest individual TI values across the population. A genome-wide association study was conducted using 32,995 SNP markers. A total of 27 significant SNPs were identified, corresponding to 20 quantitative trait loci (QTLs). Of these, 12 QTLs were detected under control conditions, 16 under seawater treatment, and 21 based on tolerance indices, indicating both constitutive and stress-responsive genetic effects. Gene annotation within these regions revealed approximately 23 candidate genes associated with abiotic stress tolerance, including genes involved in ion transport, osmotic adjustment, kinases and stress signaling pathways. HEB_22_003, HEB_04_087, and HEB_01_013 represent the most promising genotypes for salinity breeding. These findings highlight the effectiveness of combining precise phenotyping with high-resolution genomic analysis in the HEB-25 population to uncover the genetic architecture of salinity tolerance at early developmental stages. We identified 20 salinity-responsive QTLs, including five major-effect loci on chromosomes 2H, 4H, 5H, and 7H that consistently explained the largest share of phenotypic variation. These loci co-localized with candidate genes linked to ion homeostasis, Ca²⁺-mediated signaling, protein glycosylation, epigenetic regulation, and root system plasticity, revealing key mechanisms underlying early-stage salt adaptation in barley. The strong and contrasting responses of Family 01 and Family 04 provide an excellent genetic framework for functional validation of tolerance alleles. Collectively, these genomic resources establish a robust foundation for QTL pyramiding, marker-assisted breeding, and the development of climate-resilient barley cultivars for saline agroecosystems. Full article

Background/Objectives: Pharmaceutical formulation involves designing a drug product by combining the properties of an active pharmaceutical ingredient (API) with suitable excipients and processing strategies to produce a safe, effective, and manufacturable dosage form. However, data in formulation science are often limited, expensive to generate, and frequently restricted by proprietary and confidentiality constraints. Interactive digital tools can support formulators during early drug product development by improving the structure, transparency, and efficiency of formulation decision-making. While the current system focuses on structured decision support, future extensions may incorporate machine-learning methods for recommendation and knowledge extraction. Methods: In this work, we developed the Formulation tool, an interactive decision-support and visualization system for formulation development based on a hierarchical formulation-strategy framework commonly used in pharmaceutical practice. The tool is designed to prioritize suitable formulation principles and associated processing routes, with oral solid formulation as the initial application domain. The evaluated scenarios also include pathway regions relevant to oral liquid formulations. Its modular architecture also makes it adaptable to other formulation scenarios. To assess practical applicability, the tool was evaluated in a structured expert study involving five expert users across six predefined formulation scenarios (n = 30 runs), covering three drugs under adult and pediatric conditions. Results: The tool showed agreement with the expected dosage-form families and overall formulation properties, with adult scenarios converging to oral solid regions and pediatric scenarios converging to oral liquid regions. At the downstream formulation-profile level, users converged either to the dominant expected pathway or to alternative feasible pathways within the same formulation region. Variability in full pathway completion was observed and was primarily associated with differences in user interaction behavior and exploratory usage patterns. The median task completion time was 113.5 s. Conclusions: In addition to organizing formulation knowledge, the Formulation tool records user interactions in a structured manner, which may support future learning from usage patterns. Because detailed downstream formulation constraints are often institution-specific and are typically not available in the public domain, the present evaluation focused on agreement at the dosage-form-family level and on overall formulation properties rather than on highly specialized constraint logic. The system is based on a constraint satisfaction problem (CSP) framework, which is well suited for modeling complex decision processes under explicit constraints. CSP has also been widely applied in intelligent scheduling systems, supporting its suitability for structured, constraint-rich decision-making tasks such as pharmaceutical formulation strategy development. Full article

Building details are often treated as technical externalities, subordinate to form, image and architectural narrative. Reading details as liminal spaces reverses that hierarchy. The joint concentrates transitions between the inside and outside, public and private, exposure and protection, and these transitions are constructed as intervals, experienced through thickness, reveal, edge condition, shadow, touch, and the small resistances that accompany crossing. The article develops its analysis through archival hand-drawn detail drawings from the Azrieli Architectural Archive. It defines building details as both technical assemblies and threshold devices, points where architecture becomes accountable to perception as well as to climate, labor, regulation, and everyday use. A semiotic reading of large-scale sheets shows how line weight, hatching, notation, and layout encode priorities, marking boundaries between what must be precisely resolved and what may remain adjustable. The archive is treated as a laboratory of “detail families,” recurring junction types such as windows, stairs, and envelope edges that reveal office-specific languages of joining. Two case studies, by the architects Ram Karmi and Arieh Sharon with Eldar Sharon, show how micro-variations in depth, overlap, and edge control tune thresholds, producing perceptual tipping points where comfort can shift into irritation, calm into unease, and openness into vulnerability. Although grounded in a local archive, the argument addresses a broader condition of contemporary practice: standardization and digital production chains can relocate authorship and responsibility away from the joint, precisely where buildings most affect everyday conduct. The paper proposes a liminal literacy of detailing as both a historiographic method and a design ethic aimed at making threshold decisions legible, contestable, and accountable in present-day workflows. Full article

Background: The Interleukin-6 (IL6)–Interleukin-6 receptor (IL6R)–Janus kinase (JAK)–signal transducer and activator of transcription (STAT) signaling pathway plays a crucial role in innate immunity by inducing the production of various immune effectors. However, its stepwise evolutionary assembly across metazoans remains incompletely characterized. Methods: This study systematically screened 18 metazoan phyla or subphyla for the presence of IL6 family cytokines, their receptors, JAKs, and STATs. Phylogenetic relationships were constructed using Neighbor-Joining methods, and domain architectures were predicted via SMART. Results: IL6 was found only in vertebrates, whereas IL6R could be traced to Mollusca. JAK and STAT appeared early in Porifera. IL6R, JAK1/2, STAT1 and STAT5A/B first co-existed in Mollusca. The IL-6 co-receptor gp130 was detected in fish, but was not reliably detected in available reptiles’ and birds’ genomes. Conclusions: The IL6-IL6R-JAK-STAT pathway was assembled incrementally: JAK and STAT were first detected in Porifera, IL6R was added in Mollusca to form the IL6R-JAK-STAT module, and finally, most IL6 family cytokines were present in vertebrates (fish). These findings might provide a pre-existing molecular framework that facilitated the subsequent evolution of the complete pathway in vertebrates. Collectively, this study provides a comprehensive evolutionary framework for the stepwise assembly of the IL6-IL6R-JAK-STAT signaling pathway across metazoans. Full article

Cucurbit crops—including cucumber (Cucumis sativus), watermelon (Citrullus lanatus), and melon (Cucumis melo)—are of major economic and nutritional importance worldwide. Yet their productivity and quality are severely compromised by foliar fungal diseases, particularly powdery mildew (PM), downy mildew (DM), and target leaf spot (TLS). While PM and DM have been extensively studied, TLS has emerged as an increasingly prevalent and damaging disease in key production regions, yet it remains comparatively understudied—especially with respect to its molecular basis and comparative pathobiology relative to PM and DM. Current reliance on chemical fungicides is hampered by escalating pathogen resistance and concerns over residual toxicity, whereas conventional breeding approaches face inherent limitations in pyramiding durable, broad-spectrum resistance against multiple pathogens. In this context, cucumber has emerged as a pivotal model species for dissecting foliar disease resistance mechanisms in cucurbits, supported by a high-quality reference genome, extensive resequencing datasets, diverse germplasm collections, and an efficient Agrobacterium-mediated transformation system. Despite these advantages, existing reviews predominantly address PM or DM resistance in isolation; comprehensive syntheses integrating TLS resistance advances—and critically, cross-disease comparisons of genetic architecture, transcriptional reprogramming, and defense signaling—are notably scarce. Furthermore, the translational pipeline—from gene discovery and functional validation to deployment in marker-assisted or genome-edited breeding—lacks systematic evaluation. Here, we provide a focused, cucumber-centered review that (i) synthesizes recent progress in mapping QTLs and GWAS loci, and characterizing key resistance-associated gene families (such as NLRs, RLKs, PR genes) conferring resistance to PM, DM, and TLS; (ii) integrates transcriptomic, epigenomic, and proteomic evidence to delineate conserved versus pathogen-specific host responses; (iii) highlights breakthroughs and unresolved questions in TLS resistance research, including the roles of novel susceptibility factors and non-canonical immune regulators; and (iv) critically assesses bottlenecks in translating resistance genes into practical breeding outcomes—such as linkage drag, functional redundancy, and genotype-by-environment interactions—and proposes empirically grounded strategies for accelerating molecular design of multi-disease-resistant cultivars. Collectively, this review aims to bridge fundamental insights with applied breeding goals, offering a conceptual and strategic framework for integrated management of foliar fungal diseases and the development of durable, broad-spectrum resistance in cucurbits. Full article