Search Results (931)

The Molise region in Central-Southern Italy is a major contributor to national truffle production, particularly of the highly prized Tuber magnatum Picco, accounting for approximately 40% of the country’s total output and hosting the highest density of truffle harvesters. Despite this, research on the Italian white truffle populations from this area remains limited. Therefore, the primary objective of the present study was to address this knowledge gap by characterizing four T. magnatum Picco populations collected from the municipalities of Agnone, Carovilli, Castel del Giudice, and Pietrabbondante, located in “Alto Molise”, through morphological, genetic, and microbiological investigations. The statistical analyses revealed significant differences in peridium thickness and ascocarp-associated microbiota even though pairwise comparisons did not identify statistically significant differences between specific population pairs. No significant variation was observed in ascocarp weight and maturation degree. Furthermore, the presence of a unique haplotype at the single-locus marker SCAR A21-inf was confirmed in a subset of the analyzed fruiting bodies. Collectively, these findings expand current biological knowledge of the Molise white truffle and provide a foundation for future research aimed at identifying specific provenance markers to discriminate truffle populations at both regional and local scales. Full article

In Russia, Western Siberia, Anopheles from maculipennis subgroup comprises three vector species: An. messeae, An. daciae, An. beklemishevi, and the hybrid between An. messeae and An. daciae (Anopheles m-d), which exhibit complex cryptic morphological traits. Traditional morphological methods, such as egg morphology and exochorion coloration, have proven insufficient for reliably distinguishing these closely related species due to overlapping characteristics and high intra-species variability. To overcome these limitations, geometric morphometrics (GM) has emerged as a powerful tool for analyzing cryptic morphology. This article focuses on wing venation patterns, where GM provides precise, quantitative data based on defined anatomical landmarks, enabling detailed assessment of size and shape variation among species. Procrustes ANOVA, principal component analysis (PCA), and canonical variate analysis (CVA) were employed to assess shape variation and species differentiation. Centroid size and its relationship to shape variation were examined using multivariate regression. Despite significant morphological differences, the overlap observed in hybrids (An. m-d) reflects their intermediate position between the parental species. Our analyses revealed significant differences in wing shape and size among An. messeae, An. daciae, An. beklemishevi, and their hybrids, with hybrids showing intermediate morphologies. Landmarks on radial and medial veins were the most consistent contributors to species separation. No evidence of static allometry was detected, and wing shape differences were not explained by size. These findings demonstrate that wing morphometrics, combined with molecular identification, provides a reliable framework for species delimitation and surveillance of malaria vectors in temperate regions. Full article

Background: Cervical cancer remains a significant global public health concern, with human papillomavirus (HPV) vaccination serving as an effective preventive measure. Despite its proven efficacy, HPV vaccine uptake in Jordan remains low. This study aimed to assess the knowledge, attitudes, and practices (KAP) influencing HPV vaccine recommendation among healthcare professionals. Methods: A cross-sectional survey was conducted between August 2023 and February 2024 among 304 healthcare professionals and trainees in Amman, Jordan, using a pre-validated questionnaire. Descriptive statistics, correlational analyses, and Firth’s penalized logistic regression were employed to examine predictors of vaccine recommendation behavior. Results: Positive attitudes (OR = 3.89; p < 0.001) and active clinical practice (OR = 5.02; p < 0.001) were strong predictors of HPV vaccine recommendation. Unexpectedly, higher knowledge scores were associated with reduced likelihood of recommending the vaccine (OR = 0.44; p = 0.032). Significant variation in KAP scores was observed across professional groups, with physicians and academic staff demonstrating higher levels of engagement. Conclusions: Attitudes and practical engagement were more influential than knowledge alone in shaping HPV vaccine recommendation behavior among healthcare professionals. These findings underscore the need for interventions that not only enhance knowledge but also foster supportive attitudes and strengthen clinical advocacy skills. The results provide actionable evidence to inform targeted strategies for increasing HPV vaccine uptake and reducing cervical cancer incidence in Jordan. Full article

The degree of informational redundancy is often examined in genetic studies but not yet detailed for taxa conceived as minimally monophyletic groups (microgenus). Evolutionary processes in microgenera were reviewed, detailing critical sets of traits, the novon, the immediate ancestron, and the ancestron. Calculations were made from known intra-genus character state changes for maximum entropy, Shannon entropy, and entropic redundancy. Additional evaluations of contrived data sets were intended to evaluate the range of informational variation in small, medium, and large numbers of species and traits. Results indicate that measures of Shannon information and redundancy are rather similar in all but microgenera with the smallest number of species and traits per species. Hypothetically, this similarity is due to the fairly constant balance between numbers of newly evolved traits and traits monothetically redundant because all are shared with all species in the genus. This balance may be explained by a selective construct or emergent property that balances innovation leading to the colonization of new niches and conservation of proven ancestral traits for survival sympatricially and peripatrically in the particular challenges of the ancestor’s niche. The entropic redundancy calculations indicate that 0.20 to 0.30 of the information in a microgenus serves as flexibility in survival adaptation at the genus level. Full article

Non-invasive glucose monitoring remains a persistent challenge in the scientific literature due to the complexity of biological samples and the limitations of traditional optical methods. Although advances have been made in the use of near-infrared (NIR) spectrophotometry, the direct application of the Lambert–Beer Law (LBL) to such systems has proven problematic, particularly due to the non-linear behavior observed in complex organic solutions. In this context, the objective of this work is to propose and validate a methodology for the determination of the extinction coefficient of glucose in blood, taking into account the limitations of the LBL and the specificities of molecular interactions. The method was optimized through an iterative process to provide consistent results over multiple replicates. Whole blood and plasma samples from two individuals were analyzed using spectrophotometry in the 700 nm to 1400 nm. The results showed that glucose has a high spectral sensitivity close to 975 nm.The extinction coefficients obtained for glucose (${\alpha }_g$) ranged from −0.0045 to −0.0053, and for insulin (${\alpha }_i$) from 0.000075 to 0.000078, with small inter-individual variations, indicating strong stability of these parameters. The non-linear behaviour observed in the relationship between absorbance, glucose and insulin concentrations might be explained by the changes imposed by both s and p orbitals of organic molecules. In order to make the LBL valid in this context, the extinction coefficients must be functions of the analyte concentrations, and the insulin concentration must also be a function of glucose. A regression model was found which allows to differentiate glucose from insulin concentration, by considering the cuvette thickness and sample absorbance at 965, 975, and 985 nm. It can also be concluded from experiments that wavelength of approximately 975 nm is more suitable for blood glucose calculation by using photometry. The final spectra are consistent with those reported in mid-infrared validation studies, suggesting that the proposed model encompasses the key aspects of glucose behavior in biological media. Full article

Metaheuristics have proven to be effective in solving large-scale combinatorial problems by combining global exploration with local exploitation, all within a reasonably short time. The balance between these phases is crucial to avoid slow or premature convergence. We propose binary variants of the Arithmetic Optimization Algorithm for the set cover problem, integrating a two-step binarization scheme based on transfer functions with binarization rules and a greedy repair operator to ensure feasibility. We evaluate the proposed solution using forty-five instances from OR-Beasley and compare it with representative approaches, including genetic algorithms, path-relinking strategies, and Lagrangian-based heuristics. The quality of the solution is evaluated using relative percentage deviation and stability with the coefficient of variation. The results show competitive deviations and consistently low variation, confirming that our approach is a robust alternative with a solid balance between exploration and exploitation. Full article

The study of qualitative morphological variation is essential for taxonomists and professionals involved in the identification and diagnosis of species of agricultural importance. This becomes particularly critical when quarantine decisions depend on the accurate identification of species belonging to highly diverse genera, poorly reviewed taxonomic groups, or sets of morphologically similar species that lack comprehensive identification keys. Geometric morphometrics has proven to be a powerful tool for resolving taxonomic uncertainties and distinguishing economically significant pest insects, even in the absence of formal taxonomic keys. In this study, we applied geometric morphometrics to analyze pronotum shape variation across 11 species of the genus Acanthocephala, representing nearly half of the currently recognized diversity in the genus, including several species of quarantine relevance to the United States. Our results indicate that principal component analysis accounted for 67% of the total shape variation and identified shape patterns that are useful for distinguishing between several species. Discriminate analysis further supported the differentiation among species, with significant differences confirmed through Mahalanobis distances. Although some species exhibited morphological overlaps, particularly among closely related taxa, most comparisons yielded statistically significant results. These findings demonstrate that the shape of the pronotum is a reliable and informative characteristic for species delimitation within the Acanthocephala group. We propose the use of geometric morphometrics as a reproducible, cost-effective, and robust method for species-level identification in taxonomically complex groups, which has valuable applications in quarantine inspection, pest monitoring, and agricultural biosecurity. Full article

The provenance of the Middle-Upper Permian in the Lintan and Jiangligou areas, remnants of rift basin sedimentation within the West Qinling, remains controversial, hindering understanding of the basin-range coupling evolution of the Qinling Orogenic Belt and its periphery. Heavy minerals, major and trace elements, rare earth elements, detrital zircon U-Pb dating, and in situ Lu-Hf isotopes were analyzed to determine the provenance of the Middle-Upper Permian sandstones. Results were integrated with previous studies to investigate basin-range coupling processes. The results reveal the following: (1) The Upper Member of the Shilidun Formation in the Lintan area was deposited during the Late Permian. Heavy minerals are dominated by moderately to highly stable species. Source rocks were derived from intermediate-acidic magmatic rocks and low- to medium-grade metamorphic terrains. The provenance was primarily situated in a continental island arc tectonic setting. Diverse source rock types were identified, including materials from felsic igneous, quartzose recycled, and mafic igneous provenances. Detrital zircon U–Pb age spectra display two major peak ages at 285 Ma and 442 Ma, along with five subordinate peaks at 818 Ma, 970 Ma, 1734 Ma, 1956 Ma, and 2500 Ma. The ε_Hf(t) values range from –44.95 to 42.67, and T_DM2 ages vary from 367 Ma to 4106 Ma. It is concluded that the sedimentary materials were mainly derived from the North Qinling Orogenic Belt, with minor contributions from the basement of the North China Craton. (2) In the Jiangligou area, the Shiguan Formation is characterized by highly and stable heavy minerals. The provenance is dominated by intermediate-acidic magmatic rocks, within an oceanic island arc tectonic setting. Detrital zircon U–Pb age spectrum displays a prominent peak at 442 Ma. The ε_Hf(t) values range from –0.5 to 10.55, with T_DM2 ages ranging from 744 Ma to 897 Ma. These results indicate that the sedimentary materials were derived from the North Qilian Orogenic Belt. (3) The Permian in the Western Qinling exhibit multi-provenance supply, dominated by the North Qinling Orogenic Belt and the North China Craton basement, with local contributions from the North Qilian Orogenic Belt. Significant regional variations in provenance contributions were identified. This study further constrains the closure of the Shangdan Ocean to pre-Late Permian. It reveals that the Western Qinling was situated in a back-arc rift basin setting during the Late Paleozoic. Key sedimentary evidence is provided for understanding the tectonic evolution of the Paleo-Tethys Ocean and the collision between the North China and Yangtze cratons. Full article

Open-plan offices have established themselves as economically efficient working environments and promote communication. Zoned lighting concepts have proven to be particularly energy-efficient and are determined by the respective occupancy profile. Due to their size, open-plan offices usually have very different levels of daylight availability depending on their position in the room, which affects the light doses per workstation. It is unclear what influence the distribution of users in the room has on the respective target values. This study therefore examines the effects of a variation in the spatial distribution of users in a real open-plan office regarding the three target values of communication distances, daily light doses, and artificial light energy requirements. Statistical methods are used to examine how a user distribution optimized for one target variable affects the other target variables. Since optimizing user distribution is an NP-hard combinatorial problem, heuristic methods are used. The results show that optimized user distribution improves only one target variable. There are no consistently strong correlations between the optimization of communication distances, energy savings, and achievable daily light doses. The work thus contributes to the holistic design of sustainable, user-centered working environments. This research is an example of a living lab case study with optimization-based modeling, emphasizing its exploratory nature rather than controlled experimental inference. Full article

Autonomous robotic manipulators in industrial environments face significant challenges, including time-varying payloads, multi-source disturbances, and real-time computational constraints. Traditional model predictive control frameworks degrade by over 40% under model uncertainties, while conventional adaptive techniques exhibit convergence times incompatible with industrial cycles. This work presents a hybrid adaptive model predictive control framework integrating edge artificial intelligence with dual-stage parameter estimation for 6-DoF industrial manipulators. The approach combines recursive least squares with a resource-optimized neural network (three layers, 32 neurons, <500 KB memory) designed for industrial edge deployment. The system employs innovation-based adaptive forgetting factors, providing exponential convergence with mathematically proven Lyapunov-based stability guarantees. Simulation validation using the Fanuc CR-7iA/L manipulator demonstrates superior performance across demanding scenarios, including precision laser cutting and obstacle avoidance. Results show 52% trajectory tracking RMSE reduction (0.022 m to 0.012 m) under 20% payload variations compared to standard MPC, while achieving sub-5 ms edge inference latency with 99.2% reliability. The hybrid estimator achieves 65% faster parameter convergence than classical RLS, with 18% energy efficiency improvement. Statistical significance is confirmed through ANOVA (F = 24.7, p < 0.001) with large effect sizes (Cohen’s d > 1.2). This performance surpasses recent adaptive control methods while maintaining proven stability guarantees. Hardware validation under realistic industrial conditions remains necessary to confirm practical applicability. Full article

The multi-factorial hypothesis of quantitative trait inheritance originated from Nilson’s wheat hybridization experiments. It takes unit traits as the object and is based on the binomial distribution mathematically. Due to the requirement of the same distribution, it cannot include genes of other distributions. This is its limitation. Moreover, it does not incorporate the environmental effects that constitute the phenotype, so it is not comprehensive enough. This article started from the overallness of quantitative traits, was based on the central limit theorem, and was analyzed from both the genotype and the environment and proposed the assumption on the inheritance of dual multi-factors and tri-normal distributions of quantitative traits. This genetic model was tested with practical examples, and three inferences were made. Method and Results: Firstly, the overallness of quantitative traits was discussed, thus the above assumption was proposed. Next, using many examples of normal distribution of quantitative characters in the homogeneous populations, the research on the identification of the environments without GEI was carried out. Then, the examples of normal distribution of the same quantitative characters in the homogeneous populations and in the segregated populations of the same family were used. By means of normal distribution of quantitative characters in the homogeneous populations, it was indicated that the test locations were the environments without GEI. By utilizing the properties of normal distribution and variance, it was proven that normal distribution of phenotypic value for quantitative traits in a segregated population was formed by adding normal distribution of genotypic value and environmental effect, which enables the genetic model to be tested in practice. Three types of normal distribution of quantitative traits were inferred, indicating that the quantitative characters of a considerable number of organisms in nature obey a normal distribution, expressing continuous variation. Full article

This paper presents a novel approach to thermal process control in the food industry, specifically targeting the pasteurization and cooking of soft-boiled eggs. The unique challenge of this process lies in the precise temperature control required, as pasteurization and cooking must occur within a narrow temperature range. Traditional control methods, such as fuzzy logic controllers, have proven insufficient due to their limitations in handling varying loads and environmental conditions. To address these challenges, we propose the integration of robust reinforcement learning (RL) techniques, particularly the utilization of the Deep Q-Network (DQN) algorithm. Our approach involves training an RL agent in a simulated environment to manage the thermal process with high accuracy. The RL-based system adapts to different heat capacities, initial conditions, and environmental variations, demonstrating superior performance over traditional methods. Experimental results indicate that the RL-based controller significantly improves temperature regulation accuracy, ensuring consistent pasteurization and cooking quality. This study opens new avenues for the application of artificial intelligence in industrial food processing, highlighting the potential for RL algorithms to enhance process control and efficiency. Full article

Juglans neotropica Diels, classified as endangered on the IUCN Red List, plays a crucial role in the resilience of Andean montane forests in southern Ecuador—a megadiverse region encompassing coastal, Andean, and Amazonian ecosystems. This study examines how climatic, edaphic, and topographic gradients influence the species’ phenotypic traits across six source localities—Tibio, Merced, Tundo, Victoria, Zañe, and Argelia—all of which are localities situated in the provinces of Loja and Zamora Chinchipe. By integrating long-term climate records, slope mapping, and soil characterization, we assessed the effects of temperature, precipitation, humidity, soil moisture, and terrain steepness on leaf presence, fruit maturation, and tree architecture. Over the past 20 years, temperature increased by 1.5 °C (p < 0.01), while precipitation decreased by 22%, disrupting local edaphoclimatic balances. More than 2000 individuals were measured in forest stands, with estimated ages ranging from 11 to 355 years. ANOVA results revealed that Tundo and Victoria exhibited significantly greater DBH, height, and volume (p ≤ 0.05), with Victoria showing a 30% larger DBH than Argelia, the lowest-performing provenance. Soils ranged from loam to sandy loam, with slopes exceeding 45% and pH levels from slightly acidic to neutral. These findings confirm the species’ pronounced phenotypic plasticity and ecological adaptability, directly informing site-specific conservation strategies and long-term forest management under shifting climatic conditions. Full article

In the context of retrofitting existing buildings into nearly zero-energy buildings (NZEBs), in situ assessment methods have proven reliable for evaluating the performance of building components, including glazing systems. However, these methods are often time-consuming, intrusive to occupants, and disruptive to building operations. This study investigates the potential of a machine learning approach—multiple linear regression (MLR)—to predict the dynamic performance of an office building’s glazing system by analyzing surface temperature variations and their impact on nearby thermal comfort. The models were trained using in situ data collected over just two weeks—one in September and one in December—but were applied to predict the glazing performance on multiple other dates with diverse weather conditions. Results show that MLR predictions closely matched nighttime measurements, while some discrepancies occurred during the daytime. Nevertheless, the machine learning model achieved a daytime prediction accuracy of approximately 1.5 °C in terms of root mean square error (RMSE), which is lower than the values reported in previous studies. For thermal comfort evaluation, the MLR model identified the periods with thermal discomfort with an overall accuracy of approximately 92%. However, during periods when the difference between predicted and measured operative temperatures exceeded 1 °C, the thermal comfort predictions showed greater deviation from actual measurements. The study concludes by acknowledging its limitations and recommending a future approach that integrates machine learning with laboratory-based techniques (e.g., hot-box setups and solar simulators) and in situ measurements, together with a broader variety of glazing samples, to more effectively evaluate and enhance prediction accuracy, robustness, and generalizability. Full article

This study provides new constraints on the paleogeographic evolution of the Arctic during the Mesozoic. U–Pb geochronology of detrital zircon and rutile grains, together with (U–Th)/He zircon thermochronological data from the uppermost Middle Jurassic to Cretaceous strata of the Sverdrup well in the Kara Sea, reveals a major shift in sediment provenance. Two distinct age populations of detrital zircon define this transition: Group 1 (Middle Jurassic–Hauterivian) shows dominant Neoproterozoic–Cambrian (ca. 700–500 Ma) and Paleozoic (ca. 350–290 Ma) peaks, whereas Group 2 (Aptian–Albian) is characterized by prominent Paleoproterozoic (ca. 1980–1720 Ma), Paleozoic (ca. 350–255 Ma), and Early Mesozoic (ca. 240–115 Ma) ages. Corresponding variations in (U–Th)/He zircon ages—from a Triassic peak (~225 Ma) in Group 1 to a dominant Early Cretaceous peak (~140 Ma) in Group 2—support a switch from a proximal to more distal sediment source. We propose that the emergence of large continent-scale river systems transported clastic material from the southern margin of the Siberian Craton to the Arctic Ocean starting in the late Early Cretaceous. The development of a significant freshwater supply potentially initiated a thick low-salinity layer within the surface waters of the central Arctic Ocean, possibly leading to the onset of a strong salinity stratification of near-surface water masses as in the modern Arctic Ocean. Full article