Search Results (120)

The average pairwise dissimilarity (APD) between one plant sample and other assayed samples based on genetic markers was developed in 2006 to assess genetic distinctness and genetic redundancy in a plant germplasm collection. With the availability of abundant genomic variants across a genome, APD can be expanded to measure individual genomic distinctness. This study was conducted to assess the applicability of APD estimates in measuring the individual genomic distinctness of 1789 indica and 854 japonica rice samples based on published genome-wide single-nucleotide polymorphism (SNP) and structural variant (SV) data. It was found that the acquired APD estimates were weakly or not correlated between the SNP and SV data sets in the indica or japonica samples, respectively. For the indica samples, the APD estimates based on the SNP and SV data ranged from 0.1779 to 0.3277 and from 0.2297 to 0.4096, respectively. For the japonica samples, the SNP-based and SV-based APD estimates varied from 0.1774 to 0.3029 and from 0.1534 to 0.3459, respectively. These APD estimates were highly negatively correlated with the estimates of individual inbreeding coefficients and can identify the most genomically distinct rice germplasm that are compatible with those revealed through principal component analysis. Also, a reliable APD estimation was found to require 5000 to 10,000 random genomic SNPs or SVs. These findings together are significant, not only in demonstrating the informativeness of APD estimates in the identification of individuals with variable genomic distinctness, but also in providing guidance for APD applications to measure individual genomic distinctness. Full article

Based on the Hilbert–Riemann theory, this paper develops a simplified model to address interfacial fracture in bi-layer laminated solar cells with significantly dissimilar thermal properties. The model is used to analyze interfacial normal stress distributions and identify critical stress points, taking into account the substantial mismatch in the coefficients of thermal expansion between the semiconductor and encapsulation layers. The predicted temperature and stress fields are validated through finite element simulations. Furthermore, by investigating commonly used encapsulation films and solar cell modules, the coupled effects of the thermal expansion coefficient and elastic modulus are elucidated. The results demonstrate that, under a constant layer thickness, the position of the stress critical point is governed by two dimensionless parameters: the ratio of thermal expansion coefficients and the ratio of elastic moduli. This work offers an efficient and practical approach for predicting thermal stress concentration trends in laminated solar cell structures, thereby providing useful insights for the design and fabrication of solar modules. Full article

High-fluoride hot springs serve as a natural laboratory for investigating microbial adaptation and variations in community structure under extreme environments. This study utilized water chemistry analysis and 16S rRNA gene sequencing to investigate the correlation between high-fluoride hot springs and microbial community structure and diversity. The results show that the five hot springs exhibited an average F⁻ content of 15.04 mg/L, with weakly alkaline pH, high total dissolved solids, and Na⁺ as the dominant cation. The hydrochemical type was classified as HCO₃⋅SO₄-Na, consistent with the chemical characteristics of high-fluorine water. Microbial abundance and diversity were significantly reduced in the hot springs as compared to the surface water and groundwater samples. The dominant phyla in the study area included Pseudomonadota, Cyanobacteriota, Bacteroidota, and Actinomycetota. The genus-level composition varied significantly across samples, with no dominant genus observed universally. The specific genera present in different samples exhibit unique functional attributes, such as Tepidimonas, Rhodobacter, Hyphomonas, Parvibaculum, Polynucleobacter and Limnohabitans. Cluster analysis confirmed that dissimilarity coefficients highlight the significant influence of microbial abundance on inter-sample differences among hot springs. Redundancy analysis of the top 11 phyla by abundance in water samples revealed that the presence of F⁻ exerts inhibitory effects on microbial growth. Full article

Physical therapy is a critical component of medical rehabilitation, aiding recovery from conditions such as stroke, spinal cord injuries, and musculoskeletal disorders. Effective rehabilitation requires precise monitoring of patient performance to ensure exercises are executed correctly and progress is accurately assessed. This paper presents a novel automated system for controlling the rehabilitation process and evaluating physical therapy exercise quality using computer vision and a customized Human Skeleton-based Balanced Time Warping algorithm. The proposed method quantitatively assesses the similarity between a physiotherapist and patient performance by analyzing skeletal motion data extracted from RGB-D video sequences without requiring pre-alignment or sensor-specific calibration. A motion-dependent, weighted Euclidean distance between 3D skeletal models is used to compute pose dissimilarity, while a modified DTW approach aligns temporal sequences and evaluates dynamic consistency. The total dissimilarity measure is a balanced combination of posture (DP) and dynamics (DT) components. Evaluated on a custom dataset of 136 video recordings from 23 participants performing exercises in sitting and standing positions under varying performance accuracy levels (“good,” “intermediate,” and “bad”), the system demonstrates the strong clustering of accuracy levels. Proposed dissimilarity, together with a fixed reference element (physiotherapist), induces a natural non-strict order on the set of distances between patients and physiotherapists. A high value of Spearman’s rank correlation coefficient between computed dissimilarity and execution accuracy (0.977) indicates that this method is suitable for assessing exercise performance accuracy and for adequately evaluating the patient’s rehabilitation progress. The method enables objective, real-time feedback, reduces therapist workload, and supports remote monitoring, offering a scalable solution for personalized rehabilitation. Future work will involve clinical validation with post-stroke and cardiac patients. Full article

This study addresses the technical challenges of cracking and surface crack initiation in Ni60 alloy cladding layers fabricated by laser cladding additive manufacturing on FeMnNiSi alloys. An innovative FeMnNiSi-Inconel625-Ni60 laminate design was proposed, achieving metallurgical bonding of the dissimilar materials through an Inconel625 transition layer. This effectively addresses the interfacial stress concentration issue caused by differences in thermal expansion coefficients in conventional processes. The results demonstrate that the interfacial microstructure is regulated by synergistic Nb-Mo element segregation, promoting the precipitation of γ″ phase and the formation of a nanoscale Laves phase. This phase not only inhibits carbide aggregation and growth, refining grain size, but also deflects crack propagation paths by pinning dislocations, achieving a dual mechanism of stress reduction and crack arrest. The Ni60 cladding layer in the laminated structure exhibits an average surface microhardness of 641.31 HV_0.3, 3.88 times that of the substrate (165.22 HV_0.3), while the Inconel625 base layer shows 340.71 HV_0.3, 2.06 times the substrate’s value. Wear testing reveals the laminated cladding layer has a wear volume of 0.086 mm³ (0.243 mm³ less than the substrate’s 0.329 mm³) and a wear rate of 0.86 × 10⁻² mm³/(N·m), 73.86% lower than the substrate’s 3.29 × 10⁻² mm³/(N·m), indicating superior wear resistance. The electrochemical test results show that under the same corrosion conditions, the self-corrosion potential and polarization resistance of the FeMnNiSi-Inconel625-Ni60 cladding layer are significantly higher than those of the substrate, while the corrosion current density is significantly lower than that of the substrate. The frequency stability region at the highest impedance modulus |Z| is wider than that of the substrate, and the corrosion rate is 71.86% slower than that of the substrate, demonstrating excellent wear resistance. This study not only reveals the mechanism by which Laves phases improve interfacial properties through microstructural regulation but also provides a scalable interface design strategy for heterogeneous material additive manufacturing, which has important engineering value in promoting the application of laser cladding technology in the field of high-end equipment repair. Full article

Herein, we report a combined computational and experimental investigation into the recently reported universal pyrazole-based reversible addition-fragmentation chain transfer (RAFT) agents (Z−C(=S)−S−R, where Z is 3,5-dimethyl-1H-pyrazol-1-yl), which can mediate controlled radical polymerization of a broad scope of monomers without the need for an additional initiator or catalyst. The results reveal that the high molar absorption coefficient and efficient photolysis kinetics of pyrazole-based chain transfer agents (CTAs) under blue light (${\lambda }_{\max }$ = 465 nm) enable rapid radical generation, underpinning ultrafast polymerization of acrylates, acrylamides, methacrylates, and N-vinylpyrrolidone (NVP). While the efficient light absorption is attributed to structural dissimilarity between the Z group and the S–R group (which breaks the local symmetry of the C=S group), the fast photolysis originates from favorable $\pi$ electron donation from the Z group to the C=S group. Meanwhile, the $\pi$ electron donation is still weaker than in xanthates, which explains the excellent control of a wide range of monomers, except methacrylates. This work establishes design principles for next-generation CTAs for ultrafast and monomer-universal photoiniferter RAFT polymerization. Full article

Accurate photovoltaic (PV) power output forecasting is critical for ensuring stable operation of modern power systems, yet it is constrained by high-dimensional redundancy in input weather data and the inherent heterogeneity of output scenarios. To address these challenges, this paper proposes a novel cascaded data-driven forecasting approach that enhances forecasting accuracy through systematically improving and optimizing the feature extraction, scenario clustering, and temporal modeling. Firstly, guided by weather data–PV power output correlations, the Deep Autoencoder (DAE) is enhanced by integrating Pearson Correlation Coefficient loss, reconstruction loss, and Kullback–Leibler divergence sparsity penalty into a multi-objective loss function to extract key weather factors. Secondly, the Fuzzy C-Means (FCM) algorithm is comprehensively refined through Mahalanobis distance-based sample similarity measurement, max–min dissimilarity principle for initial center selection, and Partition Entropy Index-driven optimal cluster determination to effectively cluster complex PV power output scenarios. Thirdly, a Long Short-Term Memory–Temporal Pattern Attention (LSTM–TPA) model is constructed. It utilizes the gating mechanism and TPA to capture time-dependent relationships between key weather factors and PV power output within each scenario, thereby heightening the sensitivity to key weather dynamics. Validation using actual data from distributed PV power plants demonstrates that: (1) The enhanced DAE eliminates redundant data while strengthening feature representation, thereby enabling extraction of key weather factors. (2) The enhanced FCM achieves marked improvements in both the Silhouette Coefficient and Calinski–Harabasz Index, consequently generating distinct typical output scenarios. (3) The constructed LSTM–TPA model adaptively adjusts the forecasting weights and obtains superior capability in capturing fine-grained temporal features. The proposed approach significantly outperforms conventional approaches (CNN–LSTM, ARIMA–LSTM), exhibiting the highest forecasting accuracy (97.986%), optimal evaluation metrics (such as Mean Absolute Error, etc.), and exceptional generalization capability. This novel cascaded data-driven model has achieved a comprehensive improvement in the accuracy and robustness of PV power output forecasting through step-by-step collaborative optimization. Full article

Background: Gloriosa superba L., commonly known as Glory Lily, is a medicinally valuable perennial climber native to tropical and subtropical regions of India. It is known for its rich alkaloid content, including colchicine and colchicoside, which contribute to its therapeutic potential in treating various ailments. Despite its pharmacological significance, genomic research on G. superba remains limited due to the lack of genetic markers, hindering molecular studies and breeding advancements. Methods: This study utilized a previously reported de novo transcriptome assembly of G. superba, identifying 14,672 EST-SSRs as genomic markers to assess genetic variations across different accessions. Genetic diversity was examined using SSR markers, while 20 morphological traits were systematically evaluated across 19 G. superba accessions from diverse geographic regions to provide insights into trait variability. Results: The most highly variable traits included plant height, number of leaves per plant, number of branches per plant, fresh pod yield, fresh seed yield, dry seed yield, number of pods per plant, leaf width, and internodal length, with coefficients of variation (CV) ranging from 63.53% to 22.45%. Intermediate CV values (10.05% to 18.75%) were observed in eight traits, while three traits (days to flowering, days to 50% flowering, and colchicine content) had low variation (<5%). Principal component analysis (PCA) accounted for 51.3% of phenotypic variation, with PC1 and PC2 contributing 29.4% and 21.9%, respectively. Clustering analysis grouped the 19 G. superba accessions into two main clusters and four sub-clusters, highlighting significant genetic divergence, with the highest dissimilarity (81.45%) observed between accessions from Arrupukottai and Pachmarhi. SSR analysis using 112 markers revealed high polymorphism but a relatively low heterozygosity index (H = 0.277) and PIC values of individual SSRs ranged from 0.26069 in RGM-51635 to 0.4534 in RGM-24219. Conclusions: The genetic divergence observed among the collected G. superba ecotypes provides valuable insights for future breeding programs aimed at enhancing cultivation efficiency and developing superior varieties with improved yield and colchicine content. Full article

Lettuce (Lactuca sativa) is the most consumed leafy vegetable in the world, with great economic and social importance in Brazil. In breeding programs, selecting genotypes with high agronomic potential is essential to meet market demands and cultivation conditions. In this context, plant phenotyping by means of multispectral imaging emerges as a modern, efficient and non-destructive tool, which enhances the analysis of phenotypic characteristics quickly and accurately. Therefore, the aim of the present study was to group different lettuce situations according to their group using image-based phenotyping, in addition to morphological descriptors and agronomic evaluations. The experiment was carried out in an experimental area of the Federal University of Uberlândia, Campus of Monte Carmelo, MG, Brazil, in randomized blocks with three replicates and 17 treatments (lettuce populations of the F₂ generation, resulting from the cross between different lettuce cultivars and/or lines). Morphological descriptors and agronomic characteristics were obtained in the field. The vegetation indices GLI, NDVI, GNDVI, NGRDI and NDRE were calculated from images acquired at 49 days after transplanting. Means were compared using the Scott–Knott test (p ≤ 0.05), and the results were presented in box plots. Genetic dissimilarity was confirmed by multivariate analysis, which resulted in a cophenetic correlation coefficient of 96.11%. In addition, validation between field-collected data and image-obtained data was performed using heat maps and Pearson’s correlation. Populations UFU 003, UFU 006, UFU 009, UFU 011, UFU 012, UFU 013, UFU 014, UFU 016 and UFU 017 stood out, with high agronomic potential. Image-based phenotyping was correlated with agronomic traits and, therefore, can be considered an alternative to grouping different lettuce populations. Full article

This work aims to characterize flow-accelerated corrosion of carbon steel A36 coupons exposed to simulated treated reverse-osmosis seawater under ambient conditions and a Reynolds number range of 6000 to 25,000 using a standard corrosion testing method. The flow behavior in the corrosion compartment and the turbulent parameters were determined by computational fluid dynamics simulation. Using selected flow parameters, complemented with experimental corrosion rate measurements, the oxygen mass transfer coefficients (m_c) and the rate constant for the cathodic reaction (k_c) at the coupon surface were determined. As expected, m_c depends only on the fluid conditions, while k_c is highly influenced by interface resistance, leading to significantly different runs with and without a corrosion inhibitor. The dissimilar fluid flow distribution on intrados and extrados generates irregular corrosion patterns, depending on the angular position of the coupon inside the corrosion compartment. Morphological studies using scanning electron microscopy and atomic force microscopy support simulation results. Full article

Objectives: The aim of our study is to evaluate whether texture analysis of 68Ga-DOTATOC PET/CT images can predict clinical outcome in patients with neuroendocrine tumors (NET). Methods: Forty-seven NET patients who had undergone 68Ga-DOTATOC PET/CT were studied. Primary tumors were localized in the gastroenteropancreatic (n = 35), bronchopulmonary (n = 8), and other (n = 4) districts. NET lesions were segmented using an automated contouring program and subjected to texture analysis, thus obtaining the conventional parameters SUVmax and SUVmean, volumetric parameters of the primary lesion, such as Receptor-Expressing Tumor Volume (RETV) and Total Lesion Receptor Expression (TLRE), volumetric parameters of the lesions in the whole-body, such as wbRETV and wbTLRE, and texture features such as Coefficient of Variation (CoV), HISTO Skewness, HISTO Kurtosis, HISTO Entropy-log₁₀, GLCM Entropy-log₁₀, GLCM Dissimilarity, and NGLDM Coarseness. Patients were subjected to a mean follow-up period of 17 months, and survival analysis was performed using the Kaplan–Meier method and log-rank tests. Results: Forty-seven primary lesions were analyzed. Survival analysis was performed, including clinical variables along with conventional, volumetric, and texture imaging features. At univariate analysis, overall survival (OS) was predicted by age (p = 0.0079), grading (p = 0.0130), SUVmax (p = 0.0017), SUVmean (p = 0.0011), CoV (p = 0.0037), HISTO Entropy-log₁₀ (p = 0.0039), GLCM Entropy-log₁₀ (p = 0.0044), and GLCM Dissimilarity (p = 0.0063). At multivariate analysis, only GLCM Entropy-log₁₀ was retained in the model (χ² = 7.7120, p = 0.0055). Kaplan–Meier curves showed that patients with GLCM Entropy-log₁₀ >1.28 had a significantly better OS than patients with GLCM Entropy-log₁₀ ≤1.28 (χ² = 10.6063, p = 0.0011). Conclusions: Texture analysis of 68Ga-DOTATOC PET/CT images, by revealing the heterogeneity of somatostatin receptor expression, can predict the clinical outcome of NET patients. Full article

The Fauzderhat coast of Chattogram (Bangladesh) is increasingly affected anthropogenic pressures, necessitating an understanding of its ecological conditions to inform effective ecosystem management. Despite this urgency, the local succession patterns and environmental impacts on macrobenthic communities remain poorly understood. This study examines the saltmarsh bed macrobenthos in Fauzderhat, documenting 81,724 individuals from 54 species. These include ten families and twenty-two species of annelids, ten and twelve species of arthropods, and ten and eleven species of mollusks, as well as six and nine species from different phyla. Seasonality showed significantly different patterns of changes, with the number of species and abundance peaking during the monsoon (53 species) and post-monsoon (21,969) conditions, respectively, and being lowest in the post-monsoon condition (39 species) and winter (18,265 individuals). Species richness, diversity, and evenness were significantly higher in monsoon and lower in post-monsoon conditions, with the differences being only significant in the former. Cluster analysis and line graphs indicated that average species abundance was lowest post-monsoon, increased through the winter and pre-monsoon conditions, then declined again during monsoon conditions. SIMPER analysis revealed the highest dissimilarity between pre-monsoon and post-monsoon conditions while winter and post-monsoon conditions showed the lowest dissimilarity of microbenthic assemblages. Correlation coefficients showed the macrobenthos were positively correlated with soil salinity, dissolved oxygen, and pH, while they were negatively correlated with sand, Inundation Period, and nutrients. CCA showed that monsoon conditions (higher water temperature, inundation period, and tidal height) created unfavorable environments for most species, except for several species. Conversely, winter favored species like M. oligobranchia. Post-monsoon nutrient levels increased stress, reducing species presence, while pre-monsoon conditions supported balanced diversity. Full article

The hybridization of additive manufacturing (AM) with conventional manufacturing processes in tooling applications allows the customization of the tool. Examples include weight reduction, improving the vibration-dampening properties, or directing the coolant to the critical zones through intricate conformal cooling channels aimed at extending the tool life. In this regard, metallurgical challenges like the need for a post-processing heat treatment in the AM segment to meet the thermal and mechanical properties requirements persist. Heat treatment can destroy the dimensional accuracy of the pre-manufactured heat-treated wrought segment, on which the AM part is built. In the case of dissimilar joints, heat treatment may further impact the interface properties through the ease of diffusional reactions at elevated temperatures or buildup of residual stresses at the interface due to coefficient of thermal expansion (CTE) mismatch. In this communication, we report on the laser powder bed fusion (L-PBF) processing of MAR 60, a weldable carbon-free maraging powder, to manufacture a hybrid tool holder for general turning applications, comprising a wrought segment in 25CrMo4 low-alloy carbon-bearing tool steel. After L-PBF process optimization and manipulation, as-built (AB) MAR 60 steel was characterized with a hardness and tensile strength of ~450 HV (44–45 HRC) and >1400 MPa, respectively, matching those of pre-manufactured wrought 25CrMo4 (i.e., 42–45 HRC and 1400 MPa). The interface was defect-free with strong metallurgical bonding, showing slight microstructural and hardness variations, with a thickness of less than 400 µm. The matching strength and high Charpy V-notch impact energy (i.e., >40 J) of AB MAR 60 eliminate the necessity of any post-manufacturing heat treatment in the hybrid tool. Full article

As the trend towards the densification of integrated circuit (IC) devices continues, the complexity of interfaces involving dissimilar materials and thermo-mechanical interactions has increased. Highly integrated systems in packages now comprise numerous thin layers made from various materials. The interfaces between these different materials represent a vulnerable point in ICs due to imperfect adhesion and stress concentrations caused by mismatches in thermo-mechanical properties such as Young’s modulus, coefficients of thermal expansion (CTE), and hygro-swelling-induced expansion. This study investigates the impact of thermal variations on the fracture behavior of three bi-material interfaces used in semiconductor packaging: epoxy molding compound–silicon (EMC–Si), silicon oxide–polyimide (SiO₂–PI), and PI–EMC. Using double cantilever beam (DCB) tests, we analyzed these interfaces under mode I loading at three temperatures: −20 °C, 23 °C, and 100 °C, under both quasi-static and cyclic loading conditions. This provided a comprehensive analysis of the thermal effects across all temperature ranges in microelectronics. The results show that temperature significantly alters the failure mechanism. For SiO₂–PI, the weakest point shifts from silicon at low temperatures to the interface at higher temperatures due to thermal stress redistribution. Additionally, the fracture energy of the EMC–Si interface was found to be highly temperature-dependent, with values ranging from 0.136 N/mm at low temperatures to 0.38 N/mm at high temperatures. SiO₂–PI’s fracture energy at high temperature was 42% less than that of EMC–Si. The PI–EMC interface exhibited nearly double the crack growth rate compared to EMC–Si. The findings of this study provide valuable insights into the fracture behavior of bi-material interfaces, offering practical applications for improving the reliability and design of semiconductor devices, especially in chip packaging. Full article

The relevance of the study is related to the need to join dissimilar copper and nickel alloys by laser direct energy and material deposition (LDED). The purpose of research is studying the distribution of elements, structure, and properties of contact zone of nickel-based super alloy and CuCr1 bronze obtained by direct energy and material deposition with preliminary formation of relief of contact surface. For the purposes of research, samples were made from UNS C18200 copper alloy CuCr1 without relief, with a relief of 0.5 mm depth, and with a relief of 1 mm depth. The Ni₅₀Cr₃₃W_4.5Mo_2.8TiAlNb (EP648) alloy powder was deposited onto the bronze samples with a micro-relief. The deposition was produced by direct injection of energy and material. The influence of interphase interaction of CuCr-chromium carbide system on the possibility of initiation of a crack in the area of carbide secretions is not significant and does not exceed 3.1% according to CIC criterion from the background level for CuCr1 (CIC = 1.54% for CuCr1-Al₄C₃ interface and CIC = 3.1% for CuCr1-Cr₂₃C₆ interface). An X-ray analysis revealed the presence of tensile residual macro-stresses, arising from differences in thermal expansion coefficients in the CuCr1-EP648 interface area, which may be the main cause of crack formation. Cracks are generated and run along the grain boundaries, on which traces of excretion are visible. The contact surface in the CuCr1-EP648 interface area has no visible defects, which indicates the good adhesion of materials when applying an initial layer of EP648 by LDED. The presence of a 0.5-mm micro-relief on CuCr1 has a positive effect on the strength of the connection, as it increases the surface area of the contact CuCr1-EP648 and therefore reduces the contact stress of the breakout. Full article