Credit risk assessment is an important process in bank financial risk management. Traditional machine-learning methods cannot solve the problem of data islands and the high error rate of two-way decisions, which is not conducive to banks’ accurate credit risk assessment of users. To this end, this paper establishes a federated three-way decision incremental naive Bayes bank user credit risk assessment model (FTwNB) that supports asymmetric encryption, uses federated learning to break down data barriers between banks, and uses asymmetric encryption to protect data security for federated processes. At the same time, the model combines the three-way decision methods to realize the three-way classification of user credit (good, bad and delayed judgment), so as to avoid the loss of bank interests caused by the forced division of uncertain users. In addition, the model also incorporates incremental learning steps to eliminate training samples with poor data quality to further improve the model performance. This paper takes German Credit data and Default of Credit Card Clients data as examples to conduct simulation experiments. The result shows that the performance of the FTwNB model has been greatly improved, which verifies that it has good credit risk assessment capabilities. Full article

An acceptance sampling plan is a method used to make a decision about acceptance or rejection of a product based on adherence to a standard. Meanwhile, prior information, such as the process capability index (PCI), has been applied in different manufacturing industries to improve the quality of manufacturing processes and the quality inspection of products. In this paper, an attribute sampling plan is developed for submitted lots based on prior information and Bayesian approach. The new attribute sampling plans adjust sample sizes to prior information based on the status of the inspection target. To be specific, the sampling plans in this paper are indexed by the parameter trust with levels of low, medium, and high, where increasing trust level reduces sample size or risk. PCIs are an important basis for the choice of the trust level. In addition, multiple comparisons have been performed, including producer’s risk and consumer’s risk under different prior information parameters and different sample sizes. Full article

Hyperfine structure constants have many applications, but are often hard to calculate accurately due to large and canceling contributions from different terms of the hyperfine interaction operator, and also from different closed and spherically symmetric core subshells that break up due to electron correlation effects. In multiconfiguration calculations, the wave functions are expanded in terms of configuration state functions (CSFs) built from sets of one-electron orbitals. The orbital sets are typically enlarged within the layer-by-layer approach. The calculations are energy-driven, and orbitals in each new layer of correlation orbitals are spatially localized in regions where the weighted total energy decreases the most, overlapping and breaking up different closed core subshells in an irregular pattern. As a result, hyperfine structure constants, computed as expectation values of the hyperfine operators, often show irregular or oscillating convergence patterns. Large orbital sets, and associated large CSF expansions, are needed to obtain converged values of the hyperfine structure constants. We analyze the situation for the states of the $\{2s^{2}2p^3,2s^{2}2p^{2}3p,2s^{2}2p^{2}4p\}$ odd and $\{2s^{2}2p^{2}3s,2s2p^4,2s^{2}2p^{2}4s,2s^{2}2p^{2}3d\}$ even configurations in N I, and show that the convergence with respect to the increasing sets of orbitals is radically improved by introducing separately optimized orbital sets targeted for describing the spin- and orbital-polarization effects of the $1s$ and $2s$ core subshells that are merged with, and orthogonalized against, the ordinary energy-optimized orbitals. In the layer-by-layer approach, the spectroscopic orbitals are kept frozen from the initial calculation and are not allowed to relax in response to the introduced layers of correlation orbitals. To compensate for this lack of variational freedom, the orbitals are transformed to natural orbitals prior to the final calculation based on single and double substitutions from an increased multireference set. The use of natural orbitals has an important impact on the states of the $2s^{2}2p^{2}3s$ configuration, bringing the corresponding hyperfine interaction constants in closer agreement with experiment. Relying on recent progress in methodology, the multiconfiguration calculations are based on configuration state function generators, cutting down the time for spin-angular integration by factors of up to 50, compared to ordinary calculations. Full article

The main motivation for this research was to improve the properties of geopolymers by reinforcement using synthetic and natural fibers, and to gain new knowledge regarding how the nature and/or the quantity of reinforcement fibers influences the properties of the final geopolymers. The main objective was to investigate the effects of different types of reinforcement fibers on the properties of the geopolymers. These reinforcement fibers were mainly environmentally friendly materials that can be used as alternatives to ordinary Portland cement. The authors used fly ash and river sand as the raw materials for the matrix, and added carbon fibers (CF), flax fibers (FF), or a hybrid of both (CFM) as reinforcements. The samples were prepared by mixing, casting, and curing, and then subjected to various tests. The main research methods used were compressive strength (CS), flexural strength (FS), water absorption (WA), abrasion resistance (Böhme’s disk method), microstructure analysis (SEM), chemical composition (XRF), and crystal structure analysis (XRD). The results showed that the addition of fibers partially improved the mechanical properties of the geopolymers, as well as reducing microcracks. The CF-reinforced geopolymers exhibited the highest compressive strength, while the FF-reinforced geopolymers showed the lowest water absorption. The authors, based on previous research, also discussed the factors that influence fiber-matrix adhesion, and the optimal fiber content for geopolymers. Full article

Background & Aims: Reports of a rise in childhood cancer incidence in Australia and globally prompted the investigation of cancer incidence and survival in South Australia (SA) and the Northern Territory (NT) over a 28-year period, with emphasis on Indigenous peoples. Methods: This cross-sectional analysis of two prospective longitudinal databases, the SA and NT Cancer Registries (1990–2017), included all reported cases of childhood cancers. Poisson regression provided estimates of incidence rate ratios and survival was modelled using Cox proportional hazard models for children aged <5 and ≥5 years. Results: A total of 895 patients across SA (N = 753) and the NT (N = 142) were ascertained. Overall and in the NT, childhood cancer incidence was higher in males compared with females (IRR 1.19 [1.04–1.35] and 1.43 [1.02–2.01], respectively). Lymphocytic leukemia was the most reported cancer type across all locations. With reference to the 1990–1999 era (181.67/100,000), cancer incidence remained unchanged across subsequent eras in the combined cohort (SA and NT) (2000–2009: 190.55/100,000; 1.06 [0.91–1.25]; 2010–2017: 210.00/100,000; 1.15 [0.98–1.35]); similar outcomes were reflected in SA and NT cohorts. Cancer incidence amongst non-Indigenous children significantly decreased from the 1990–1999 era (278.32/100,000) to the 2000–2009 era (162.92/100,000; 0.58 [0.35–0.97]). Amongst 39 Indigenous children in the NT, incidence rates remained unchanged across eras (p > 0.05). With reference to the 1990–1999 era, overall survival improved in subsequent eras in SA (2000–2009: HR 0.53 [0.38–0.73]; 2010–2017: 0.44 [0.28–0.68]); however, remained unchanged in the NT (2000–2009: 0.78 [0.40–1.51]; 2010–2017: 0.50 [0.24–1.05]). In the NT, overall survival of Indigenous patients was significantly lower compared with the non-Indigenous cohort (3.42 [1.92–6.10]). While the survival of Indigenous children with cancer significantly improved in the last two eras (p < 0.05), compared to the 1990–1999 era, no change was noted amongst non-Indigenous children in the NT (p > 0.05). Conclusions: The incidence of childhood cancers has remained unchanged over 28-years in SA and the NT. Encouragingly, improved survival rates over time were observed in SA and amongst Indigenous children of the NT. Nevertheless, survival rates in Indigenous children remain lower than non-Indigenous children. Full article

Long-term conservation of more than 7 million plant germplasm accessions in 1750 genebanks worldwide is a challenging mission. The extent of deleterious mutations present in conserved germplasm and the genetic risk associated with accumulative mutations are largely unknown. This study took advantage of published barley genomic data to predict sample-wise mutation burdens for 19,778 domesticated barley (Hordeum vulgare L.) accessions conserved ex situ. It was found that the conserved germplasm harbored 407 deleterious mutations and 337 (or 82%) identified deleterious alleles were present in 20 (or 0.1%) or fewer barley accessions. Analysis of the predicted mutation burdens revealed significant differences in mutation burden for several groups of barley germplasm (landrace > cultivar (or higher burden estimate in landrace than in cultivar); winter barley > spring barley; six-rowed barley > two-rowed barley; and 1000-accession core collection > non-core germplasm). Significant differences in burden estimate were also found among seven major geographical regions. The sample-wise predicted mutation burdens were positively correlated with the estimates of sample average pairwise genetic difference. These findings are significant for barley germplasm management and utilization and for a better understanding of the genetic risk in conserved plant germplasm. Full article

DNA methylation plays an essential role in regulating gene activity, modulating disease risk, and determining treatment response. We can obtain insight into methylation patterns at a single-nucleotide level via next-generation sequencing technologies. However, complex features inherent in the data obtained via these technologies pose challenges beyond the typical big data problems. Identifying differentially methylated cytosines (dmc) or regions is one such challenge. We have developed DMCFB, an efficient dmc identification method based on Bayesian functional regression, to tackle these challenges. Using simulations, we establish that DMCFB outperforms current methods and results in better smoothing and efficient imputation. We analyzed a dataset of patients with acute promyelocytic leukemia and control samples. With DMCFB, we discovered many new dmcs and, more importantly, exhibited enhanced consistency of differential methylation within islands and their adjacent shores. Additionally, we detected differential methylation at more of the binding sites of the fused gene involved in this cancer. Full article

Floods are a common natural disaster whose severity in terms of duration, water resource volume, peak, and accumulated rainfall-based damage is likely to differ significantly for different geographical regions. In this paper, we first propose a novel hourly flood index ($SWR{I}_{24-hr-S}$) derived from normalising the existing 24-hourly water resources index ($WR{I}_{24-hr-S}$) in the literature to monitor flood risk on an hourly scale. The proposed $SWR{I}_{24-hr-S}$ is adopted to identify a flood situation and derive its characteristics, such as the duration (D), volume (V), and peak (Q). The comprehensive result analysis establishes the practical utility of $SWR{I}_{24-hr-S}$ in identifying flood situations at seven study sites in Fiji between 2014 and 2018 and deriving their characteristics (i.e., D, V, and Q). Secondly, this study develops a vine copula-probabilistic risk analysis system that models the joint distribution of flood characteristics (i.e., D, V, and Q) to extract their joint exceedance probability for the seven study sites in Fiji, enabling probabilistic flood risk assessment. The vine copula approach, particularly suited to Fiji’s study sites, introduces a novel probabilistic framework for flood risk assessment. The results show moderate differences in the spatial patterns of joint exceedance probability of flood characteristics in different combination scenarios generated by the proposed vine copula approach. In the worst-case scenario, the probability of any flood event occurring where the flood volume, peak, and duration are likely to exceed the 95th-quantile value (representing an extreme flood event) is found to be less than 5% for all study sites. The proposed hourly flood index and the vine copula approach can be feasible and cost-effective tools for flood risk monitoring and assessment. The methodologies proposed in this study can be applied to other data-scarce regions where only rainfall data are available, offering crucial information for flood risk monitoring and assessment and for the development of effective mitigation strategies. Full article

The present study aims to resolve the existing research gaps on olive pomace (OP) hydrochars application as a fuel by evaluating its molecular structures (FTIR and solid NMR analysis), identifying influential characteristics (Pearson correlation analysis), process optimization (response surface methodology), slagging–fouling risks (empirical indices), and combustion performance (TG-DSC analysis). The response surfaces plot for hydrothermal carbonization (HTC) of OP slurry performed in a pressure reactor under varied temperatures (180–250 °C) and residence times (2–30 min) revealed 250 °C for 30 min to be optimal conditions for producing hydrochar fuel with a higher heating value (32.20 MJ·Kg⁻¹) and energy densification ratio (1.40). However, in terms of process efficiency and cost-effectiveness, the optimal HTC conditions for producing the hydrochar with the highest energy yield of 87.9% were 202.7 °C and 2.0 min. The molecular structure of hydrochar was mainly comprised of aromatic rings with methyl groups, alpha-C atoms of esters, and ether bond linkages of lignin fractions. The slagging and fouling risks of hydrochars were comparatively lower than those of raw OP, as indicated by low slagging and fouling indices. The Pearson correlation analysis emphasized that the enrichment of acid-insoluble lignin and extractive contents, carbon densification, and reduced ash content were the main pivotal factors for hydrochar to exhibit better biofuel characteristics for energy applications. Full article

Upper urinary tract urolithiasis is an emerging disease in cats, with 98% of kidney stones composed of calcium oxalate. In humans, disturbances in the intestinal and urinary microbiota are suspected to contribute to the formation of calcium oxalate stones. We hypothesized that similar mechanisms may be at play in cats. This study examines the intestinal and urinary microbiota of nine cats with kidney stones compared to nine healthy cats before, during, and after treatment with the antibiotic cefovecin, a cephalosporin. Initially, cats with kidney stones displayed a less diverse intestinal microbiota. Antibiotic treatment reduced microbiota diversity in both groups. The absence of specific intestinal bacteria could lead to a loss of the functions these bacteria perform, such as oxalate degradation, which may contribute to the formation of calcium oxalate stones. This study confirms the presence of a distinct urobiome in cats with kidney stones, characterized by greater richness and diversity compared to healthy cats. These findings highlight the potential of microbiota modulation as a strategy to prevent renal lithiasis in cats. Full article

Milk bioactivity refers to the specific health effects of milk components beyond nutrition. The science of milk bioactivity involves the systematic study of these components and their health effects, as verified by empirical data, controlled experiments, and logical arguments. Conversely, ’faith in milk bioactivity’ can be defined as personal opinion, meaning, value, trust, and hope for health effects that are beyond investigation by natural, social, or human sciences. Faith can be strictly secular, but also influenced by spirituality or religion. The aim of this paper is to show that scientific knowledge is frequently supplemented with faith convictions to establish personal and public understanding of milk bioactivity. Mammalian milk is an immensely complex fluid containing myriad proteins, carbohydrates, lipids, and micronutrients with multiple functions across species, genetics, ages, environments, and cultures. Human health includes not only physical health, but also social, mental, and spiritual health, requiring widely different fields of science to prove the relevance, safety, and efficacy of milk interventions. These complex relationships between milk feeding and health outcomes prevent firm conclusions based on science and logic alone. Current beliefs in and understanding of the value of breast milk, colostrum, infant formula, or isolated milk proteins (e.g., immunoglobulins, α-lactalbumin, lactoferrin, and growth factors) show that both science and faith contribute to understand, stimulate, or restrict the use of milk bioactivity. The benefits of breastfeeding for infants are beyond doubt, but the strong beliefs in its health effects rely not only on science, and mechanisms are unclear. Likewise, fear of, or trust in, infant formula may rely on both science and faith. Knowledge from science safeguards individuals and society against ‘milk bioactivity superstition’. Conversely, wisdom from faith-based convictions may protect science from unrealistic ‘milk bioactivity scientism’. Honesty and transparency about the potentials and limitations of both scientific knowledge and faith convictions are important when informing individuals and society about the nutritious and bioactive qualities of milk. Full article

In recent years, the efficient removal of organic pollutants from wastewater has emerged as a critical area of global research interest. Against this backdrop, an array of innovative technologies for wastewater treatment has been developed. Among numerous advanced oxidation processes (AOPs), periodate (PI), an emerging oxidizing agent in AOPs, has garnered significant attention from researchers. Particularly, the integration of ultrasound (US)-activated PI systems has been recognized as an exceptionally promising approach for the synergistic degradation of organic pollutants in wastewater. In this paper, we conducted a thorough analysis of the mechanisms underlying the degradation of organic pollutants using the US/PI system. Furthermore, we comprehensively delineated the effects of ultrasonic power, periodate concentration, temperature, pH, coexisting inorganic ions, and dissolved organic matter on the removal efficiency of organic pollutants and summarized application cases of the US/PI system for the degradation of different pollutants. Finally, we also offered prospective discussions on the future trajectories of US/PI technology development. Full article

International conservation approaches recognise architectural heritage as crucial in promoting sustainable development and enhancing human well-being. This has been highlighted by the recent New European Bauhaus (NEB) movement. As for the reuse of architectural heritage, this debate has led to the formulation of new guidelines that aim to maximise the tangible and intangible values of the assets from a long-term and circular economy perspective. In turning theory into operational practice, it is essential to reuse heritage structures while keeping these principles in mind and remaining within the boundaries of conservation objectives. To achieve this, evaluation tools that can aid in the decision-making process need to be identified. This research presents a novel model of indicators that can monitor and evaluate the quality of architectural heritage reuse projects, proposing a perspective that considers both the concept of well-being and the NEB principles. The proposed model is tested on Turin’s IPIM (Provincial Institute for Childhood and Maternity). This structure has been transformed from an uncomfortable heritage into a cultural centre for contemporary art called Flashback Habitat. The case study tests the model’s practical applicability and demonstrates its effectiveness in identifying the most challenging principles to apply in practice. Full article

In West Africa, the construction of small earth dams is common against water scarcity. Burkina Faso, an inland country in West Africa, is home to 1001 dams that serve agricultural and pastoral needs. These embankments are predominantly made of compacted laterite, a cost-effective material abundant in over 2/3 of the country. However, these dams degrade over time, hindering their functionality. This study aims to establish a catalog of typical degradation occurring on small dams in Burkina Faso, which is virtually non-existent in the region while identifying and analyzing the potential causes. The study uses a diagnostic analysis followed up with technical visits on a representative sample of 24 dams in the Centre and Centre-South regions as a basis for future studies. The results reveal that these dams were constructed between 1965 and 2018, with capacities ranging from 150,000 to 4,740,000 m³. 33% of these dams have undergone total failure, likely attributed to factors such as internal erosion, pore overpressures, settlement, and deformation. Although 67% of the dams remain functional, their structural integrity could be improved. Erosion observed in riprap indicates vulnerability during high flood periods. Additionally, the absence of proper maintenance, as shown by the vegetation development weakening embankments, contributes to deterioration. The analysis also suggests that variability in construction techniques and lateritic material properties across time and regions may further exacerbate degradation. These findings inform infrastructure improvements and policy development for sustainable water resource management in Burkina Faso and similar regions. Full article

Hybrid lateral closed-wedge high tibial osteotomy (HBHTO) carries certain advantages over medial open-wedge high tibial osteotomy (OWHTO). We investigated the potential difference in the required correction angle between HBHTO and OWHTO to achieve an equal amount of whole lower-extremity alignment correction, retrospectively analyzing the preoperative plain radiographic images of 100 patients. The medial proximal tibial angle (MPTA), joint line convergence angle (JLCA), mechanical lateral distal femoral angle (mLDFA), hip–knee–ankle axis (HKA), length of the tibia, width of the tibial plateau, length of the lower limb (leg length), and location of the center of deformity (CD) were measured. Differences in the required correction angle at the hinge point between the two techniques (CAD) were compared, and correlation analysis was performed to reveal the influential factors. The mean difference in CAD between HBHTO and OWHTO was 0.78 ± 0.22 (0.4~1.5)°, and mean WBL position change per correction angle was 3.9 ± 0.3 (3.0~4.6)% in HBHTO and 4.1 ± 0.3 (3.1~4.7)% in OWHTO. Correlation analysis revealed a strong positive correlation between CAD and HKA. mLDFA, JLCA, MPTA, leg length, OWCD, HBCD, and HCD were also significantly correlated with CAD. HBHTO required a 5.6% larger correction angle at the hinge point to achieve the same amount of alignment correction as OWHTO. Full article

Progress in composite materials has led to their use in applications where improved mechanical and resistance characteristics are required. Most composites are obtained in such a way that they present specific mechanical properties and/or have the role of both a thermal conductor and insulator; these properties are important, specific, specialized, and useful. The advantages of these materials compared to the classic ones are as follows: low weight, high resistance to wear and corrosion, and mechanical characteristics consistent with the subsequent use of the product. The slightly high costs of these materials are justified by their precision, the quality of the products obtained, and the fact that their use leads to increased reliability, maintenance, and, in the cases of the automotive and aeronautical industries, reduced energy consumption. This paper aims to bring to readers’ attention the latest research related to glass fibre-reinforced composite materials in transport-related applications, such as automotive and aeronautic applications, including the manufacturing of unmanned aerial vehicles (UAVs). Considering the long period of use, the recycling and reuse of composite materials used in aeronautical transport is a must considering the environmental aspects and the need of achieving a circular economy. In recent years, considerable efforts have been made to find new alternatives to improve the performance and durability of materials in the aeronautical transport sector. Full article

Transformer has emerged as one of the modern neural networks that has been applied in numerous applications. However, transformers’ large and deep architecture makes them computationally and memory-intensive. In this paper, we propose the block g-circulant matrices to replace the dense weight matrices in the feedforward layers of the transformer and leverage the DCT-DST algorithm to multiply these matrices with the input vector. Our test using Portuguese-English datasets shows that the suggested method improves model memory efficiency compared to the dense transformer but at the cost of a slight drop in accuracy. We found that the model Dense-block 1-circulant DCT-DST of 128 dimensions achieved the highest model memory efficiency at 22.14%. We further show that the same model achieved a BLEU score of 26.47%. Full article

The permafrost in Northeast China is experiencing rapid degradation due to the influence of climate change and human activities, profoundly impacting the local ecological environment and engineering construction. Understanding the spatiotemporal dynamics of long-term permafrost in this region is crucial; however, systematic research on this topic remains scarce. This study combines meteorological station data, MODIS land surface temperature (LST) datasets, and borehole locations to apply the surface frost number (SFn) model. This approach enables the simulation and estimation of the spatial distribution and changes in the area of the surface frost number without vegetation effects (SFnv) and permafrost temperature (PT) in Northeast China from 1971 to 2020. The area of the SFnv > 0.49 within the permafrost region decreased substantially from approximately 44.353 × 10⁴ km² to 19.909 × 10⁴ km² between 1971 and 2020, with a notable change in 1988. The area of permafrost calculated using PT < 0 was slightly smaller, declining from 39.388 × 10⁴ km² to 29.852 × 10⁴ km². There was also a significant increase in the area with PT ranging from −1 °C to 0 °C, indicating a decline in permafrost stability. Approximately 10.926 × 10⁴ km² of stable permafrost has been transformed into semi-stable and unstable permafrost. Moreover, from 1982 to 2020, the NDVI was negatively correlated with the area of stable permafrost and positively correlated with the area of transitional or unstable permafrost. Vegetation cover decreased as transitional or unstable permafrost degraded. These findings provide valuable information for permafrost research and engineering development in cold regions, as well as for future planning and adaptation strategies. Full article

Allometry reflects the quantitative relationship between the allocation of resources among different organs. Understanding patterns of forest biomass allocation is critical to comprehending global climate change and the response of terrestrial vegetation to climate change. By collecting and reorganizing the existing allometric models of tree species in China, we established a database containing over 3000 empirical allometric models. Based on this database, we analyzed the model parameters and the effect of climate on forest biomass allocation under the context of ‘optimal allocation theory’. We showed that (1) the average and median exponent of power functions for above-ground biomass were 2.344 and 2.385, respectively, which significantly deviated from the theoretical prediction of 2.667 by metabolic theory (p < 0.01). (2) The parameters of the allometric model were not constant, and not significantly correlated with temperature, precipitation, latitude, and elevation (p > 0.05), but were more closely related to individual size (p < 0.01). (3) Among different types of forests, the proportion of above-ground biomass in tropical rainforests and subtropical evergreen rainforests was significantly higher than that in temperate forests and boreal forests (p < 0.05). The proportion of trunk and branch biomass allocated to tropical rainforest was significantly higher than that of boreal forest (p < 0.05), while the proportion of root and leaf biomass allocated to tropical rainforest was significantly lower than that of boreal forest (p < 0.05). (4) The abiotic environment plays a crucial role in determining the allocation of plant biomass. The ratio of below-ground/above-ground biomass is significantly and negatively correlated with both temperature and rainfall (p < 0.01), and significantly and positively correlated with altitude and latitude (p < 0.01). This means that as temperature and rainfall increase, there is a decrease in the amount of biomass allocated to below-ground structures such as roots. On the other hand, as altitude and latitude increase, there is an increase in below-ground biomass allocation. These findings highlight the importance of considering the influence of abiotic factors on plant growth and development. Full article

Infectious bursal disease virus (IBDV) is a significant burden for poultry production and market due to both direct disease and induced immunosuppression. In the present study, the expression of different cytokines in the bursa of Fabricius and thymus was evaluated during a 28-day-long experimental infection with two strains classified in the G1a (Classical) and G6 (ITA) genogroups. Although both strains significantly affected and modulated the expression of different molecules, the G6 strain seemed to induce a delayed immune response or suppress it more promptly. A recovery in the expression of several mediators was observed in the G1a-infected group at the end of the study, but not in the G6 one, further supporting a more persistent immunosuppression. This evidence fits with the higher replication level previously reported for the G6 and with the clinical outcome, as this genotype, although subclinical, has often been considered more immunosuppressive. However, unlike other studies focused on shorter time periods after infection, the patterns observed in this paper were highly variable and complex, depending on the strain, tissue, and time point, and characterized by a non-negligible within-group variability. Besides confirming the strain/genogroup effect on immune system modulation, the present study suggests the usefulness of longer monitoring activities after experimental infection to better understand the complex patterns and interactions with the host response. Full article

This comprehensive review delineates the extensive roles of Akkermansia muciniphila in various health domains, spanning from metabolic and inflammatory diseases to neurodegenerative disorders. A. muciniphila, known for its ability to reside in the mucous layer of the intestine, plays a pivotal role in maintaining gut integrity and interacting with host metabolic processes. Its influence extends to modulating immune responses and potentially easing symptoms across several non-communicable diseases, including obesity, diabetes, inflammatory bowel disease, and cancer. Recent studies highlight its capacity to interact with the gut–brain axis, suggesting a possible impact on neuropsychiatric conditions. Despite the promising therapeutic potential of A. muciniphila highlighted in animal and preliminary human studies, challenges remain in its practical application due to stability and cultivation issues. However, the development of pasteurized forms and synthetic mediums offers new avenues for its use in clinical settings, as recognized by regulatory bodies like the European Food Safety Authority. This narrative review serves as a crucial resource for understanding the broad implications of A. muciniphila across different health conditions and its potential integration into therapeutic strategies. Full article

Ginkgo biloba L. is a rare dioecious species that is valued for its diverse applications and is cultivated globally. This study aimed to develop a rapid and effective method for determining the sex of a Ginkgo biloba. Green and yellow leaves representing annual growth stages were scanned with a hyperspectral imager, and classification models for RGB images, spectral features, and a fusion of spectral and image features were established. Initially, a ResNet101 model classified the RGB dataset using the proportional scaling–background expansion preprocessing method, achieving an accuracy of 90.27%. Further, machine learning algorithms like support vector machine (SVM), linear discriminant analysis (LDA), and subspace discriminant analysis (SDA) were applied. Optimal results were achieved with SVM and SDA in the green leaf stage and LDA in the yellow leaf stage, with prediction accuracies of 87.35% and 98.85%, respectively. To fully utilize the optimal model, a two-stage Period-Predetermined (PP) method was proposed, and a fusion dataset was built using the spectral and image features. The overall accuracy for the prediction set was as high as 96.30%. This is the first study to establish a standard technique framework for Ginkgo sex classification using hyperspectral imaging, offering an efficient tool for industrial and ecological applications and the potential for classifying other dioecious plants. Full article