Search Results (349)

We demonstrate the potential of using the convolutional equivalent layer to jointly process large gravity-gradient datasets. Based on the equivalent-layer principle, we assume a single fictitious physical property distribution on a planar layer can approximate all components of the gravity-gradient tensor. Estimating this distribution using the classical technique ensures physical consistency among components. However, the classical approach becomes computationally prohibitive for large datasets due to the need to solve a large-scale inversion with a massive sensitivity matrix. To overcome this limitation, we exploit the block-Toeplitz Toeplitz-block structure of the sensitivity matrix for data on a regular horizontal grid. This structure significantly reduces computational cost—by orders of magnitude—compared to the classical method. Applications to synthetic and real datasets show that our method offers a computationally efficient alternative for processing large gravity-gradient data from various acquisition systems (AGG and FTG), even when data are irregularly spaced or flight lines are misaligned. On a standard laptop configuration, our method processed over 290,000 AGG data points in a few tens of seconds. It also handled between 726,000 FTG and 1,250,000 AGG data points within seconds to a couple of minutes, demonstrating practical computational efficiency for large-scale datasets. Full article

Porcine reproductive and respiratory syndrome virus remains one of the most economically significant pathogens in swine production, with PRRSV-2 being the dominant variant in the United States. While lineage classification has traditionally relied on ORF5 sequencing, recent studies suggest that this single-gene approach may overlook key evolutionary events such as recombination. In this study, we performed whole-genome sequencing and phylogenetic analysis of seven PRRSV-2 isolates collected in the U.S. between 2006 and 2024. Using reference-guided assembly, lineage assignment, and recombination detection with RDP5 and SIMplot, we identified discordant phylogenetic placements between ORF5 and whole genomes in four of the seven isolates. These discordances were explained by multiple recombination events affecting different genomic regions, particularly ORF2–ORF7. In contrast, three isolates showed phylogenetic concordance and no strong evidence of recombination. Our findings demonstrate that recombination plays a significant role in shaping PRRSV-2 evolution and highlight the limitations of ORF5-based lineage classification. Whole-genome surveillance is therefore essential to accurately track viral diversity, detect recombinant strains, and inform control strategies. This work underscores the need for a broader adoption of full-genome analysis in routine PRRSV surveillance and research. Full article

Background/Objectives: Colorectal cancer (CRC) is one of the most prevalent cancers worldwide. Even though the screening programs have decreased the incidence rates, the prognosis for CRC varies depending on the stage at diagnosis. Thus, early diagnosis is still a big challenge due to screening methods, and subsequent diagnosis is not very sensitive. Methods: In this work, LC-MS-based metabolomics, a powerful and sensitive tool to study complex dynamic changes, was used to analyze 211 human fecal samples from control individuals (CTRL), adenoma (AA), and CRC patients. Results: Multivariate and univariate statistical analysis highlighted cholesteryl esters (CEs) and fecal haemoglobin, quantified by fecal immunochemical test (FIT), as relevant biomarkers that clearly differentiate CRC from AA and CTRL. Predictive models based on random forest and the area under the curve (AUC) of the receiver operating characteristic curve (ROC) demonstrate that CEs, together with FIT measurement, improved the CRC and CTRL classification, but not AA. This study revealed that the AA group is a transitional stage with high heterogeneity. The increased tendency observed in CEs from CTRL to CRC might be related to the imbalance of cholesterol homeostasis due to cancer cells requiring a high cholesterol level for cell development and proliferation. The free cholesterol is probably obtained from CEs, as it is the most cost/effective way to obtain the needed cholesterol. Conclusions: The accumulation of CEs is produced by two possible approaches: (1) dysfunction of cholesterol absorption in the small intestine and/or (2) transported inside exosomes from cell to cell to promote proliferation. Full article

Flying wing Unmanned Aerial Vehicles (UAVs) are an interesting flight configuration, considering its benefits over aerodynamic, structural and added stealth aspects. The existing configurations are thoroughly studied from the literature survey and useful observations with respect to design and analysis are obtained. The proposed design method includes distinct calculations of the UAV and modelling using 3D experience. The created innovative models are simulated with the help of computational fluid dynamics techniques in ANSYS Fluent to obtain the aerodynamic parameters such as forces, pressure and velocity. The optimization process continues to add more desired modifications to the model, to finalize the best design of flying wing frame for the chosen application and mission profile. In total, nine models are developed starting with the base model, then leading to the conventional, advanced and nature inspired configurations such as the falcon and dragonfly models, as it has an added advantage of producing high maneuverability and lift. Following this, fluid structure interaction analysis has been performed for the best performing configurations, resulting in the determination of variations in the structural behavior with the imposition of advanced composite materials, namely, boron, Kevlar, glass and carbon fiber-reinforced polymers. In addition to this, a hybrid material is designed by combining two composites that resulted in superior material performance when imposed. Control dynamic study is performed for the maneuvers planned as per mission profile, to ensure stability during flight. All the resulting parameters obtained are compared with one another to choose the best frame of the flying wing body, along with the optimum material to be utilized for future analysis and development. Full article

The wide availability of sensor data stored in multiple formats makes it difficult to reuse in other applications. We consider the problem of extracting sensor data from unstructured and semi-structured texts using Large Language Models. With careful prompt crafting, we have been able to establish a strict JSON structure which can be further processed with automated ease. We establish a workflow that enables the extraction of data using GPT-4, Llama 3, Mistral and Falcon models, and we show that while the closed-source GPT-4 model is generally leading in conversion efficiency, other open-source models can follow this if given appropriate data structures. We define new measures to simplify the comparison, and we present a multi-purpose workflow for sensor data extraction. We observe that some of the smaller models are incapable of correctly extracting data from freeform text but are skilled in processing tabular data. On the other hand, larger models are more robust and avoid conversion mistakes more easily. Full article

For the first time, the numerous scattered data on birds (wild and domestic) have been collected based on their medieval bone remains discovered on the modern territory of the Republic of Bulgaria. The collected information is about a total of 37 medieval settlements from the time of the First and Second Bulgarian Empires. Among the settlements studied are both the two medieval Bulgarian capitals (Pliska and Veliki Preslav), as well as other cities, smaller settlements, military fortresses, monasteries, and inhabited caves. The data refer to a total of 48 species of wild birds and 6 forms of domestic birds of 11 avian orders: Accipitriformes, Anseriformes, Ciconiiformes, Columbiformes, Falconiformes, Galliformes, Gruiformes, Otidiformes, Passeriformes, Pelecaniformes, and Strigiformes. The established composition of wild birds amounts to over one tenth (to 11.5%) of the modern avifauna in the country. Five of the established species (10.4%) have disappeared from the modern nesting avifauna of the country—the bearded vulture, the great bustard, the little bustard, the gray crane, and the saker falcon (the latter two species have reappeared as nesters in the past few years). First Bulgarian Empire (681–1018): Investigated settlements—22. Period covered—five centuries (7th to 11th c.). Found in total: at least 44 species/forms of birds, of which 39 species of wild birds and 5 forms of poultry. Second Bulgarian Empire (1185–1396): Investigated settlements—15. Period covered—3 centuries (12th to 14th c.). Found in total: at least 39 species/forms of birds, of which 33 species of wild birds and 6 forms of poultry. The groups of raptors, water, woodland, openland, synanthropic and domestic birds were analyzed separately. The conclusion was made that during the two periods of the Middle Ages, birds had an important role in the material and spiritual life of the population of the Bulgarian lands. Birds were mainly used for food (domestic birds), although some were objects of hunting. No traces of processing were found on the bones. Birds were subjects of works of applied and monumental art. Their images decorated jewelry, tableware, walls of buildings and other structures. Full article

Heartworm disease, caused by Dirofilaria immitis, often leads to pulmonary hypertension (PH), a serious cardiovascular complication in infected dogs. PH may impair renal function through hemodynamic and inflammatory mechanisms, even when traditional biomarkers such as serum creatinine and blood urea nitrogen (BUN) remain within normal ranges. This study aimed to assess urinary neutrophil gelatinase-associated lipocalin (uNGAL) levels in dogs naturally infected with D. immitis, with and without PH, to evaluate its potential as an early biomarker of renal dysfunction. Forty-two infected dogs were included and divided into two groups based on the presence (n = 14) or absence (n = 28) of PH, diagnosed via echocardiography. uNGAL concentrations were significantly higher in dogs with PH (mean 66.49 ± 6.67 ng/mL) compared to those without PH (mean 49.01 ± 14.48 ng/mL; p < 0.0001), despite normal creatinine and BUN values. No significant associations were found between uNGAL and sex, age, breed, or clinical signs. These findings suggest that uNGAL may serve as a sensitive biomarker of early renal impairment in dogs with heartworm disease and PH, even in the absence of overt azotemia, supporting its use in clinical evaluation and the monitoring of disease progression. Full article

One of the medicinal plants used in Ecuador that has the best prospects for industrialization is guayusa (Ilex guayusa Loes.). This review shows the potential of the species, analyzing the ethnobotanical aspects, ancestral uses, secondary metabolites, and research. The plant has been consumed for thousands of years by the high Amazonian peoples of Ecuador and currently forms part of the gardens of ancestral peoples and mestizo settlers. The most relevant secondary metabolites that have been investigated are xanthine alkaloids, terpenes, and phenolic compounds, while from the pharmacological point of view, the following uses stand out: physical and mental stimulants, analgesic, antioxidant, antimicrobial, anti-inflammatory, anti-diabetic, and phytohormonal. The goal of this review is to make known the benefits of guayusa, with the purpose of representing a resource that will provide benefits to the Amazonian inhabitants in the future. Full article

Conventional public-key cryptographic systems are increasingly threatened by advances in quantum computing, accelerating the need for robust post-quantum cryptographic solutions. Among these, Falcon, a compact lattice-based digital signature scheme, has emerged as a leading candidate in the NIST post-quantum standardization process due to its efficiency and theoretical security grounded in hard lattice problems. This work introduces Falcon-M, a modified version of the Falcon algorithm that significantly reduces implementation complexity. It does so by replacing Falcon’s intricate trapdoor-based key-generation mechanism with a simplified approach that utilizes randomized polynomial Gaussian sampling and fast Fourier transform (FFT) operations. Falcon-M incorporates SHA-512 hashing and discrete Gaussian sampling to preserve cryptographic soundness and statistical randomness while maintaining the core structure of Falcon’s signing and verification processes. We formally specify the Falcon-M algorithm, provide an updated pseudocode, and offer a comparative analysis with the original Falcon in terms of algorithmic complexity, security assumptions, and implementation overhead. Additionally, we present formal lemmas and theorems to ensure correctness and define theoretical bounds on forgery resistance. Although Falcon-M does not rely on a formal cryptographic trapdoor, we demonstrate that it achieves strong practical security based on assumptions related to the Short Integer Solution (SIS) problem. Falcon-M is thus well-suited for lightweight post-quantum applications, particularly in resource-constrained environments, such as embedded systems and Internet-of-Things (IoT) platforms. Full article

Background/Objectives: Deep learning (DL) has shown strong potential in analyzing food images, but few studies have directly predicted mass, energy, and macronutrient content from images. In addition to the importance of high-quality data, differences in country-specific food composition databases (FCDBs) can hinder model generalization. Methods: We assessed the performance of several standard DL models using four ground truth datasets derived from Nutrition5k—the largest image–nutrition dataset with ~5000 complex US cafeteria dishes. In light of developing an Italian dietary assessment tool, these datasets varied by FCDB alignment (Italian vs. US) and data curation (ingredient–mass correction and frame filtering on the test set). We evaluated combinations of four feature extractors [ResNet-50 (R50), ResNet-101 (R101), InceptionV3 (IncV3), and Vision Transformer-B-16 (ViT-B-16)] with two regression networks (2+1 and 2+2), using IncV3_2+2 as the benchmark. Descriptive statistics (percentages of agreement, unweighted Cohen’s kappa, and Bland–Altman plots) and standard regression metrics were used to compare predicted and ground truth nutritional composition. Dishes mispredicted by ≥7 algorithms were analyzed separately. Results: R50, R101, and ViT-B-16 consistently outperformed the benchmark across all datasets. Specifically, when replacing it with these top algorithms, reductions in median Mean Absolute Percentage Errors were 6.2% for mass, 6.4% for energy, 12.3% for fat, and 33.1% and 40.2% for protein and carbohydrates. Ingredient–mass correction substantially improved prediction metrics (6–42% when considering the top algorithms), while frame filtering had a more limited effect (<3%). Performance was consistently poor across most models for complex salads, chicken-based or eggs-based dishes, and Western-inspired breakfasts. Conclusions: The R101 and ViT-B-16 architectures will be prioritized in future analyses, where ingredient–mass correction and automated frame filtering methods will be considered. Full article

This publication focuses on the use of fuzzy neural networks for data prediction. The author reviews papers in which fuzzy neural networks were used. The papers were selected mainly from 2020 to 2025 and were selected if fuzzy neural network were used for practical applications. Also, some chosen networks are described: FALCON, ANFIS, and a fuzzy network with Ordered Fuzzy Numbers. The networks with the implementation code presented in other publications were tested and compared to K Neighbors Classifier, Decision Tree Classifier, and Random Forest Classifier. The methodology and configuration of the networks are provided. Finally, the conclusions discuss limitations, future research prospects, and guidelines for future work. Full article

Despite the transformative potential of artificial intelligence (AI), small and medium-sized enterprises (SMEs) continue to face significant challenges in its effective adoption. While prior studies have emphasized strategic benefits and readiness models, there remains a lack of operational guidance tailored to SME realities—particularly regarding implementation barriers, resource constraints, and emerging demands for responsible AI use. This study presents an analysis of AI adoption in SMEs by integrating the technology–organization–environment (TOE) framework with selected attributes from the diffusion of innovations (DOI) theory to examine adoption dynamics through a dual structural and perceptual lens. Empirical insights from sectoral and regional contexts are also incorporated. Ten critical challenges are identified and analyzed across the TOE dimensions, ranging from data access and skill shortages to cultural resistance, infrastructure limitations, and weak governance practices. Notably, the framework is expanded to incorporate responsible AI governance and democratized access to generative AI—particularly open-weight large language models (LLMs) such as LLaMA, DeepSeek-R1, Mistral, and FALCON—as emerging technological and ethical imperatives. Each challenge is paired with actionable, context-sensitive solutions. The paper is a structured, literature-based conceptual analysis enriched by empirical case study insights. As a key contribution, it introduces a structured, six-phase roadmap methodology to guide SMEs through AI adoption—offering step-by-step recommendations aligned with technological, organizational, and strategic readiness. While this roadmap is conceptual and has yet to be validated through field data, it sets a foundation for future diagnostic tools and practical assessments. The resulting study bridges theoretical insight and implementation strategy—empowering inclusive, responsible, and scalable AI transformation in SMEs. By offering both analytical clarity and practical relevance, this study contributes to a more grounded understanding of AI integration and calls for policies, ecosystems, and leadership models that support SMEs in adopting AI not merely as a tool, but as a strategic enabler of sustainable and inclusive innovation. Full article

Adrenal cortex carcinoma (ACC) in children is a rare tumor that is probably of multifactorial origin and is mainly associated with genetic and environmental alterations. In the south and part of the southeast of Brazil, as well as in the Paraguayan region bordering the Brazilian State of Paraná, ACC prevalence is higher than in any other country, which is associated with the high prevalence of the TP53 p.R337H variant in Paraná (0.30%), Santa Catarina (0.249%), cities around Campinas-SP (0.21%), and the Paraguayan cities on the border with Paraná (0.05%). Recent research suggests that the co-segregation of XAF1-E134* and TP53-R337H mutations leads to a more aggressive cancer phenotype than TP53-R337H alone. Breast cancer may be mildly influenced by co-segregation with XAF1 p.E134*, and this variant can also confer risk for sarcoma. Objectives: The objectives of this study were to (1) estimate the prevalence of the germline TP53 p.R337H and XAF1 p.E134* variants in Paraguay (excluding cities on the border with Paraná State, Brazil) and (2) estimate whether the ethnic origin of TP53 p.R337H carriers in Paraguay is similar to that of ethnic groups in Paraná (possible Portuguese/Spanish origin). Materials and methods: DNA tests for the identification of TP53 p.R337H were carried out from 2016 to 2019 at the Bio-Materials Laboratory of Facultad Politecnica, UNA, and at the Research Center in Biotechnology and Informatics (CEBIOTEC), Asunción, Paraguay. Polymerase chain reaction followed by restriction enzyme digestion (PCR-RFLP) was used to identify TP53 p.R337H, and real-time PCR (RT-PCR) was employed for XAF1 p.E134*. Peripheral blood samples from 40,000 Paraguayan newborns (NBs) were used for the TP53 p.R337H tests. The XAF1 p.E134* tests (RT-PCR) were performed on samples from 2000 Paraguayan newborns at the Pelé Pequeno Principe Research Institute, Curitiba, PR, Brazil. Results: The TP53 p.R337H variant was not found in any of the 14 Paraguayan departments investigated. A total of 12 of the 2000 Paraguayan NBs were positive for one XAF1 p.E134* allele. Conclusions: The hypothesis of Spanish immigrants carrying p.R337H to Paraguay was disproved. TP53 p.R337H neonatal testing in Paraguay is not recommended, except when there are families with Brazilian ancestry presenting cancer cases. Additional epidemiological studies are required to determine the likelihood of the identified prevalence of the XAF1 p.E134* allele (1/153) in NBs from Paraguay without TP53 p.R337H to present cancer risk. This study complements the first national initiative for the DNA screening of newborns aimed at mapping the TP53 p.R337H and XAF1 p.E134* variants in Paraguay (based on the regions of residence of the newborns). Full article

Quantum computing challenges the mathematical problems anchoring the security of the classical public key algorithms. For quantum-resistant public key algorithms, the National Institute of Standards and Technology (NIST) has undergone a multi-year standardization process and selected the post-quantum cryptography (PQC) public key digital signatures of Dilithium, Falcon, and SPHINCS⁺. Finding common ground to compare these algorithms can be difficult because of their design differences, including the fundamental math problems (lattice-based vs. hash-based). We use a visualization model to show the key/signature size vs. security trade-offs for all PQC algorithms. Our performance analyses compare the algorithms’ computational loads in the execution time. Building on the individual algorithms’ analyses, we analyze the communication costs and implementation overheads when integrated with Public Key Infrastructure (PKI) and with Transport Layer Security (TLS) and Transmission Control Protocol (TCP)/Internet Protocol (IP). Our results show that the lattice-based algorithms of Dilithium and Falcon induce lower computational overheads than the hash-based algorithms of SPHINCS⁺. In addition, the lattice-based PQC can outperform the classical algorithm with comparable security strength; for example, Dilithium 2 and Falcon 512 outperform RSA 4096 in the TLS handshake time duration. Full article

The Luanchuan Neoproterozoic gabbroic intrusions are located at the southern margin of the North China Craton (NCC), intruding into the marble and schist from the Nannihu and Meiyaogou Formations of the Neoproterozoic Luanchuan Group. The gabbroic rocks consist of plagioclase (30%–50%) and amphibole (40%–60%), with minor ilmenite (2%–5%), biotite (1%–3%), and titanite (~1%). Based on the occurrence and mineral chemistry, two types of biotites were identified. The first type of biotite (Bt I) is brown, with a fine- to micro-grained anhedral texture, occurring around the magmatic ilmenite and coexisting with titanite. Bt I is characterized by high TiO₂ and FeO contents, with TiO₂ > 2 wt% (2.03 wt%–3.15 wt%) and FeO ranging from 19.94 wt% to 22.08 wt%. The other type of biotite (Bt II) is light grayish-brown to dark reddish-brown, with a medium- to coarse-grained euhedral texture, coexisting with grayish-green amphibole. Bt II exhibits lower TiO₂ (1.40 wt%–1.90 wt%) and FeO contents (18.03 wt%–21.42 wt%). The K₂O (7.56 wt%–9.32 wt%) and SiO₂ (34.49 wt%–37.04 wt%) contents of Bt I are slightly lower than those of Bt II (8.28 wt%–9.73 wt% and 35.18 wt%–37.52 wt%, respectively). Despite the low Ti content in biotites, the mineral occurrence indicates that both types of biotite yield a magmatic origin, resulting from the reactions between early crystallized minerals and residual magma. Bt I originated from the reaction between ilmenite and residual magma, while Bt II resulted from the production of the reaction between clinopyroxne and residual magma. Ilmenite exhibits low MgO and Fe₂O₃ contents but high FeO and MnO contents, suggesting genetic similarities to the Skaergaard and Panzhihua intrusions. Both types of biotites record consistent temperatures (T = 766 to 818 °C), pressures (P = 5.30–8.80 kbar), and oxygen fugacities (log fO₂ = −12.35 to −14.06), aligning with those of the Fanshan complex and the Falcon Island intrusion. The mineralogy of ilmenite and biotite indicates that the Luanchuan gabbroic intrusions formed in a continental rift setting, which is considered to be associated with the breakup of the Rodinia supercontinent. Full article