Search Results (18)

Accurate prediction of food delivery time is crucial for enhancing operational efficiency and customer satisfaction in real-world logistics and intelligent dispatch systems. To address this challenge, this study proposes a novel symmetric optimization prediction framework, termed SymOpt-CNSVR. The framework is designed to leverage the strengths of both deep learning and statistical learning models in a complementary architecture. It employs a Convolutional Neural Network (CNN) to extract and assess the importance of multi-feature data. An Enhanced Superb Fairy-Wren Optimization Algorithm (ESFOA) is utilized to optimize the diverse hyperparameters of the CNN, forming an optimal adaptive feature extraction structure. The significant features identified by the CNN are then fed into a Support Vector Regression (SVR) model, whose hyperparameters are optimized using Bayesian optimization, for final prediction. This combination reduces the overall parameter search time and incorporates probabilistic reasoning. Extensive experimental evaluations demonstrate the superior performance of the proposed SymOpt-CNSVR model. It achieves outstanding results with an R² of 0.9269, MAE of 3.0582, RMSE of 4.1947, and MSLE of 0.1114, outperforming a range of benchmark and state-of-the-art models. Specifically, the MAE was reduced from 4.713 (KNN) and 5.2676 (BiLSTM) to 3.0582, and the RMSE decreased from 6.9073 (KNN) and 6.9194 (BiLSTM) to 4.1947. The results confirm the framework’s powerful capability and robustness in handling high-dimensional delivery time prediction tasks. Full article

This study proposes a deep learning-based vertical decomposition model for ionospheric Total Electron Content (TEC), which establishes a nonlinear mapping from macroscale TEC data to vertically layered electron density (Ne) spanning 60–800 km by integrating geomagnetic indices (AE, SYM-H) and solar activity parameters (F10.7). Utilizing global TEC grid data (spatiotemporal resolution: 1 h/5.625° × 2.8125°) provided by the International GNSS Service (IGS), a Multilayer Perceptron (MLP) model was developed, taking spatiotemporal coordinates, altitude, and space environment parameters as inputs to predict logarithmic electron density ln(Ne). Experimental validation against COSMIC-2 radio occultation observations in 2019 demonstrates the model’s capability to capture ionospheric vertical structures, with a prediction performance significantly outperforming the International Reference Ionosphere model IRI-2020: root mean square error (RMSE) decreased by 34.16%, and the coefficient of determination (R²) increased by 28.45%. This method overcomes the reliance of traditional electron density inversion on costly radar or satellite observations, enabling high-spatiotemporal-resolution global ionospheric profile reconstruction using widely available GNSS-TEC data. It provides a novel tool for space weather warning and shortwave communication optimization. Current limitations include insufficient physical interpretability and prediction uncertainty in GNSS-sparse regions, which could be mitigated in future work through the integration of physical constraints and multi-source data assimilation. Full article

Background: For the past 25 years, the ITS rDNA (ITS1-5.8S-ITS2) of Gyrodactylidae has been crucial for species identification, description, and phylogeny. This family includes 25 genera parasitizing marine and freshwater fish, initially distinguished by morphological differences in attachment and/or male copulatory organs. Gyrodactylus Nordmann, 1832, the most species-rich genus, has approximately 500 described species and an additional 25,000 species suspected. The genus is not monophyletic, and the functionally adaptive nature of morphological diagnostic characters complicates the delimitation of new genera. Methods: A phylogeny based on ITS rDNA was proposed to address these challenges, using only complete sequences of primitive taxa. Fifty-four sequences were aligned with the MUSCLE v5.1 algorithm, creating a 1590 ps long matrix. Maximum Likelihood (ML) and Bayesian Inference (BI) methods with the models TVM+F+G4 and SYM+G4 for ITS1–ITS2 and 5.8S, respectively, were inferred using IQ-TREE v2.3.5 and BEAST v2.7.6.0. Results: The findings revealed eleven main lineages. Four of them are proposed for classification into new genera: Cichlidarus gen. nov., Iraqemembranatus gen. nov., Macracanthus gen. nov., and Rysavyius gen. nov. Elevating the subgenus G. (Gyrodactylus) to genus rank was supported. Conclusions: The presented phylogeny provides a foundation for developing a classification system within Gyrodactylidae that is both reasonable and comprehensive. Full article

Probiotic-fermented milk is commonly used to maintain intestinal health. However, the effects of heat-treated fermented milk, which does not contain live microorganisms, on intestinal function are not yet fully understood. This study aimed to investigate whether heat-treated Lactobacillus helveticus CP790-fermented milk affects fecal microbiota and gut health as a “postbiotic”. A randomized, double-blind, placebo-controlled trial was conducted in healthy Japanese individuals aged 20–59 years with a tendency toward constipation. Participants consumed 100 mL of either the test beverage (n = 60) or placebo beverage (n = 60) for four weeks. The test beverages were prepared with heat-treated CP790-fermented milk, while the placebo beverages were prepared with nonfermented milk flavored with lactic acid. Fecal samples were analyzed using 16S rRNA gene sequencing. Constipation symptoms were assessed using defecation logs and the Patient Assessment of Constipation Symptoms (PAC-SYM) questionnaire. Mood state was also assessed using the Profile of Mood States 2 (POMS2) questionnaire to explore its potential as a “psychobiotic”. Desulfobacterota were significantly decreased by CP790-fermented milk intake. PICRUSt2 analysis predicted a decrease in the proportion of genes involved in the sulfate reduction pathway following the consumption of CP790-fermented milk. The CP790-fermented milk intervention significantly improved stool consistency and straining during defecation. These improvements were correlated with a decrease in Desulfobacterota. After the intervention, overall mood, expressed as total mood disturbance, and depression–dejection were significantly better in the CP790 group than in the placebo group. These results suggest that the intake of CP790-fermented milk could be effective in modulating gut microbiota and improving constipation symptoms and mood states. Full article

A review is made of constraints on the nuclear symmetry energy parameters arising from nuclear binding energy measurements, theoretical chiral effective field predictions of neutron matter properties, the unitary gas conjecture, and measurements of neutron skin thicknesses and dipole polarizabilities. While most studies have been confined to the parameters $S_V$ and L, the important roles played by, and constraints on $K_{\mathrm{sym}}$, or, equivalently, the neutron matter incompressibility $K_N$, are discussed. Strong correlations among $S_V,L$, and $K_N$ are found from both nuclear binding energies and neutron matter theory. However, these correlations somewhat differ in the two cases, and those from neutron matter theory have smaller uncertainties. To 68% confidence, it is found from neutron matter theory that $S_V=32.0\pm 1.1$ MeV, $L=51.9\pm 7.9$ MeV and $K_N=152.2\pm 38.1$ MeV. Theoretical predictions for neutron skin thickness and dipole polarizability measurements of the neutron-rich nuclei ${}^{48}$Ca, ${}^{120}$Sn, and ${}^{208}$Pb are compared to recent experimental measurements, most notably the CREX and PREX neutron skin experiments from Jefferson Laboratory. By themselves, PREX I+II measurements of ${}^{208}$Pb and CREX measurement of ${}^{48}$Ca suggest $L=121\pm 47$ MeV and $L=-5\pm 40$ MeV, respectively, to 68% confidence. However, we show that nuclear interactions optimally satisfying both measurements imply $L=53\pm 13$ MeV, nearly the range suggested by either nuclear mass measurements or neutron matter theory, and is also consistent with nuclear dipole polarizability measurements. This small parameter range implies $R_{1.4}=11.6\pm 1.0$ km and ${\Lambda }_{1.4}={228}_{-90}^{+148}$, which are consistent with NICER X-ray and LIGO/Virgo gravitational wave observations of neutron stars. Full article

Detection rapidity and model accuracy are the keys to hyperspectral nondestructive testing technology, especially for Pennisetum sinese Roxb (PsR) due to its extremely high adsorptive heavy metal content. The study of the resolution of PsR is conducive to the analysis of the accumulated heavy metal content in its different parts. In this paper, the contents of Cd, Cu and Zn accumulated in the old leaves, young leaves, upper stem, middle stem and lower stem, as well as the hyperspectral data of the corresponding parts, were measured simultaneously in both fresh and dry states. To begin, the spectral data of PsR were preprocessed by using Ensemble Empirical Mode Decomposition-Daubechies3 (EEMD-db3), Savitzky–Golay (SG), Symlet3 (sym3), Symlet5 (sym5), and multiplicative scatter correction (MSC). The 40 samples were divided into 32 training sets and 8 validation sets. The preprocessed spectral data were transformed by the first derivative (FD) and reciprocal logarithm (log(1/R)) to highlight the singularities using binary wavelet decomposition. After screening the significant bands from the correlation curve, the competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were applied to extract the spectral characteristic variables, which were used to establish the partial least-squares (PLS) regression and multiple stepwise linear regression (MSLR) inversion models of Cd, Cu, and Zn contents. Based on EEMD-db3 pretreatment, the inversion model of Zn in the dry (fresh) state had R² values of 0.884 (0.880), NRMSE values of 0.179 (0.253) and RPD values of 3.191 (3.221), indicating excellent stability and predictive performance. The findings of this study can not only aid in the rapid nondestructive detection of heavy metal adsorption in various parts of PsR, but can also be applied to guide the development and use of animal feed. Full article

This study aimed to investigate the relationship between anxiety, depression, and gut microbiota in elderly patients with FC. Methods: in this cross-sectional study, a total of 198 elderly participants (85 male and 113 female) aged over 60 years were recruited. The study was conducted in Changsha city, China. The participants completed an online questionnaire, including The Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7), The Patient Assessment of Symptoms (PAC-SYM), and The Patient Assessment of Quality of Life (PAC-QoL). We selected the 16S rDNA V3 + V4 region as the amplification region and sequenced the gut microbiota using the Illumina Novaseq PE250 high-throughput sequencing platform. Results: in total, 30.3% of patients with constipation had depression, while 21.3% had anxiety. The relative abundance of intestinal microbiota in the normal group was higher than that in the anxiety and depression group. According to LEfSe analysis, the relative abundance of g_Peptoniphilus and g_Geobacter in the people without depression and anxiety was higher. The relative abundance of g_Pseudoramibacter-Eubacterium and g_Candidatus-Solibacter in the depression group was lower, and the relative abundance of g_Bacteroides and g_Paraprevotella, g_Cc_115 in the anxiety group was higher. In addition, according to the correlation analysis, g_Aquicella and g_Limnohabitans were negatively correlated with constipation symptoms, anxiety, and depression. Conclusions: this study found that gut microbiota composition may be associated with a higher incidence of anxiety and depression in patients with FC, thus providing insight into the mechanisms that ameliorate mood disorders in patients with FC. Full article

Uridine diphosphate glycosyltransferases (UGTs) as fine catalysts of glycosylation are increasingly used in the synthesis of natural products. Sucrose synthase (SuSy) is recognized as a powerful tool for in situ regenerating sugar donors for the UGT-catalyzed reaction. It is crucial to select the appropriate SuSy for cooperation with UGT in a suitable way. In the present study, eukaryotic SuSy from Arabidopsisthaliana (AtSUS1) helped stevia glycosyltransferase UGT76G1 achieve the complete conversion of stevioside (30 g/L) into rebaudioside A (RebA). Position of the individual transcription units containing the genes encoding AtSUS1 and UGT76G1 in the expression plasmid has an effect, but less than that of the fusion order of these genes on RebA yield. Fusion of the C-terminal of AtSUS1 and the N-terminal of UGT76G1 with rigid linkers are conducive to maintaining enzyme activities. When the same fusion strategy was applied to a L637M-T640V double mutant of prokaryotic SuSy from Acidithiobacillus caldus (AcSuSym), 18.8 ± 0.6 g/L RebA (a yield of 78.2%) was accumulated in the reaction mixture catalyzed by the fusion protein Acm-R3-76G1 (the C-terminal of AcSuSym and the N-terminal of UGT76G1 were linked with (EAAAK)3). This work would hopefully reveal the potential of UGT-SuSy fusion in improving the cascade enzymatic glycosylation. Full article

Foeniculum vulgare Mill. (commonly known as fennel) is used in the pharmaceutical, cosmetic, and food industries. Fennel widely used as a digestive, carminative, galactagogue and diuretic and in treating gastrointestinal and respiratory disorders. Improving low heritability traits such as essential oil yield (EOY%) and trans-anethole yield (TAY%) of fennel by direct selection does not result in rapid gains of EOY% and TAY%. Identification of high-heritable traits and using efficient modeling methods can be a beneficial approach to overcome this limitation and help breeders select the most advantageous traits in medicinal plant breeding programs. The present study aims to compare the performance of the artificial neural network (ANN) and multilinear regression (MLR) to predict the EOY% and TAY% of fennel populations. Stepwise regression (SWR) was used to assess the effect of various input variables. Based on SWR, nine traits—number of days to 50% flowering (NDF50%), number of days to maturity (NDM), final plant height (FPH), number of internodes (NI), number of umbels (NU), seed yield per square meter (SY/m²), number of seeds per plant (NS/P), number of seeds per umbel (NS/U) and 1000-seed weight (TSW)—were chosen as input variables. The network with Sigmoid Axon transfer function and two hidden layers was selected as the final ANN model for the prediction of EOY%, and the TanhAxon function with one hidden layer was used for the prediction of TAY%. The results revealed that the ANN method could predict the EOY% and TAY% with more accuracy and efficiency (R² of EOY% = 0.929, R² of TAY% = 0.777, RMSE of EOY% = 0.544, RMSE of TAY% = 0.264, MAE of EOY% = 0.385 and MAE of TAY% = 0.352) compared with the MLR model (R² of EOY% = 0.553, R² of TAY% = 0.467, RMSE of EOY% = 0.819, RMSE of TAY% = 0.448, MAE of EOY% = 0.624 and MAE of TAY% = 0.452). Based on the sensitivity analysis, SY/m², NDF50% and NS/P were the most important traits to predict EOY% as well as SY/m², NS/U and NDM to predict of TAY%. The results demonstrate the potential of ANNs as a promising tool to predict the EOY% and TAY% of fennel, and they can be used in future fennel breeding programs. Full article

Here, we report an improved and complete genome sequence of Sinorhizobium (Ensifer) meliloti strain WSM1022, a microsymbiont of Medicago species, revealing its tripartite structure. This improved genome sequence was generated combining Illumina and Oxford nanopore sequencing technologies to better understand the symbiotic properties of the bacterium. The 6.75 Mb WSM1022 genome consists of three scaffolds, corresponding to a chromosome (3.70 Mb) and the pSymA (1.38 Mb) and pSymB (1.66 Mb) megaplasmids. The assembly has an average GC content of 62.2% and a mean coverage of 77X. Genome annotation of WSM1022 predicted 6058 protein coding sequences (CDSs), 202 pseudogenes, 9 rRNAs (3 each of 5S, 16S, and 23S), 55 tRNAs, and 4 ncRNAs. We compared the genome of WSM1022 to two other rhizobial strains, closely related Sinorhizobium (Ensifer) meliloti Sm1021 and Sinorhizobium (Ensifer) medicae WSM419. Both WSM1022 and WSM419 species are high-efficiency rhizobial strains when in symbiosis with Medicago truncatula, whereas Sm1021 is ineffective. Our findings report significant genomic differences across the three strains with some similarities between the meliloti strains and some others between the high efficiency strains WSM1022 and WSM419. The addition of this high-quality rhizobial genome sequence in conjunction with comparative analyses will help to unravel the features that make a rhizobial symbiont highly efficient for nitrogen fixation. Full article

The density dependence of nuclear symmetry energy is among the most uncertain parts of the Equation of State (EOS) of dense neutron-rich nuclear matter. It is currently poorly known especially at suprasaturation densities partially because of our poor knowledge about isovector nuclear interactions at short distances. Because of its broad impacts on many interesting issues, pinning down the density dependence of nuclear symmetry energy has been a longstanding and shared goal of both astrophysics and nuclear physics. New observational data of neutron stars including their masses, radii, and tidal deformations since GW170817 have helped improve our knowledge about nuclear symmetry energy, especially at high densities. Based on various model analyses of these new data by many people in the nuclear astrophysics community, while our brief review might be incomplete and biased unintentionally, we learned in particular the following: (1) The slope parameter L of nuclear symmetry energy at saturation density ${\rho }_0$ of nuclear matter from 24 new analyses of neutron star observables was about $L\approx 57.7\pm 19$ MeV at a 68% confidence level, consistent with its fiducial value from surveys of over 50 earlier analyses of both terrestrial and astrophysical data within error bars. (2) The curvature $K_{\mathrm{sym}}$ of nuclear symmetry energy at ${\rho }_0$ from 16 new analyses of neutron star observables was about $K_{\mathrm{sym}}\approx -107\pm 88$ MeV at a 68% confidence level, in very good agreement with the systematics of earlier analyses. (3) The magnitude of nuclear symmetry energy at $2{\rho }_0$, i.e., $E_{\mathrm{sym}}\left(2{\rho }_0\right)\approx 51\pm 13$ MeV at a 68% confidence level, was extracted from nine new analyses of neutron star observables, consistent with the results from earlier analyses of heavy-ion reactions and the latest predictions of the state-of-the-art nuclear many-body theories. (4) While the available data from canonical neutron stars did not provide tight constraints on nuclear symmetry energy at densities above about $2{\rho }_0$, the lower radius boundary $R_{2.01}=12.2$ km from NICER’s very recent observation of PSR J0740+6620 of mass $2.08\pm 0.07$$M_{\odot }$ and radius $R=12.2–16.3$ km at a 68% confidence level set a tight lower limit for nuclear symmetry energy at densities above $2{\rho }_0$. (5) Bayesian inferences of nuclear symmetry energy using models encapsulating a first-order hadron–quark phase transition from observables of canonical neutron stars indicated that the phase transition shifted appreciably both L and $K_{\mathrm{sym}}$ to higher values, but with larger uncertainties compared to analyses assuming no such phase transition. (6) The high-density behavior of nuclear symmetry energy significantly affected the minimum frequency necessary to rotationally support GW190814’s secondary component of mass (2.50–2.67) $M_{\odot }$ as the fastest and most massive pulsar discovered so far. Overall, thanks to the hard work of many people in the astrophysics and nuclear physics community, new data of neutron star observations since the discovery of GW170817 have significantly enriched our knowledge about the symmetry energy of dense neutron-rich nuclear matter. Full article

In order to optimize the management of groundwater resources, accurate estimates of groundwater level (GWL) fluctuations are required. In recent years, the use of artificial intelligence methods based on data mining theory has increasingly attracted attention. The goal of this research is to evaluate and compare the performance of adaptive network-based fuzzy inference system (ANFIS) and Wavelet-ANFIS models based on FCM for simulation/prediction of monthly GWL in the Maragheh plain in northwestern Iran. A 22-year dataset (1996–2018) including hydrological parameters such as monthly precipitation (P) and GWL from 25 observation wells was used as models input data. To improve the prediction accuracy of hybrid Wavelet-ANFIS model, different mother wavelets and different numbers of clusters and decomposition levels were investigated. The new hybrid model with Sym4-mother wavelet, two clusters and a decomposition level equal to 3 showed the best performance. The maximum values of R2 in the training and testing phases were 0.997 and 0.994, respectively, and the best RMSE values were 0.05 and 0.08 m, respectively. By comparing the results of the ANFIS and hybrid Wavelet-ANFIS models, it can be deduced that a hybrid model is an acceptable method in modeling of GWL because it employs both the wavelet transform and FCM clustering technique. Full article

The peptidyl transferase center of the modern ribosome has been found to encompass an area of twofold pseudosymmetry (SymR). This observation strongly suggests that the very core of the ribosome arose from a dimerization event between two modest-sized RNAs. It was previously shown that at least four non-standard interactions exist between the two halves of SymR. Herein, we verify that the structure of the SymR is highly conserved with respect to both ribosome transition state and phylogenetic diversity. These comparisons also reveal two additional sites of interaction between the two halves of SymR and refine our understanding of the previously known interactions. In addition, the possible role that magnesium may have in the coordination, stabilization, association, and evolutionary history of the two halves (A-region and P-region) was examined. Together, the results identify a likely site where structural elements and Mg²⁺ ions may have facilitated the ligation of two aboriginal RNAs into a single unit. Full article

This pilot study aimed to explore the effect of solution-focused group counseling intervention on Internet addiction among college students. Eighteen college students participated in this study, out of which nine subjects were assigned into the experimental group and the rest (n = 9) to a control group. The experimental group received group counseling for five weeks, while the control group did not receive any intervention. The revised version of the Chinese Internet Addiction Scale (CIAS-R) was used to capture pre-test and post-test excessive use in the two groups. The experimental group was also subjected to a follow-up test and self-reported Internet addiction scores six months after the end of group counseling. Results showed that after the five-week solution-focused group counseling, the scores of four dimensions of the CIAS-R in the experimental group had CIAS-R decreased, and the reduction trend of the total score of CIAS-R was similar across all subjects in this group. The treatment effect was larger than the placebo reduction in the control group in two dimensions: compulsive and withdrawal (Sym-C & Sym-W) and tolerance (Sym-T) symptoms. Qualitative research confirmed the conclusions from the quantitative data, showing that the experimental group reduced its Internet addiction symptoms. Overall, the findings suggested that solution-focused group counseling had positive intervention effects on Internet addiction. Full article

Quorum sensing (QS) is a bacterial cell-to-cell signaling mechanism that collectively regulates and synchronizes behaviors by means of small diffusible chemical molecules. In rhizobia, QS systems usually relies on the synthesis and detection of N-acyl-homoserine lactones (AHLs). In the model bacterium Sinorhizobium meliloti functions regulated by the QS systems TraI-TraR and SinI-SinR(-ExpR) include plasmid transfer, production of surface polysaccharides, motility, growth rate and nodulation. These systems are also present in other bacteria of the Sinorhizobium genus, with variations at the species and strain level. In Sinorhizobium fredii NGR234 phenotypes regulated by QS are plasmid transfer, growth rate, sedimentation, motility, biofilm formation, EPS production and copy number of the symbiotic plasmid (pSym). The analysis of the S. fredii HH103 genomes reveal also the presence of both QS systems. In this manuscript we characterized the QS systems of S. fredii HH103, determining that both TraI and SinI AHL-synthases proteins are responsible of the production of short- and long-chain AHLs, respectively, at very low and not physiological concentrations. Interestingly, the main HH103 luxR-type genes, expR and traR, are split into two ORFs, suggesting that in S. fredii HH103 the corresponding carboxy-terminal proteins, which contain the DNA-binding motives, may control target genes in an AHL-independent manner. The presence of a split traR gene is common in other S. fredii strains. Full article