Nowadays, pet animals are known to be asymptomatic carriers of Clostridioidesdifficile. This study was conducted to investigate the burden of toxigenic C. difficile among diarrheic dogs and cats using direct PCR on fecal samples to reveal better insights about the epidemiology of such toxigenic strains referring to its public health significance. For this purpose, fecal samples were obtained from 58 dogs and 42 cats experiencing diarrhea. Following DNA extraction, the extracted DNA was examined for the occurrence of C. difficile as well as toxigenic strains through the detection of C. difficile 16S rRNA and toxin encoding genes (tcdA, tcdB, cdtA and cdtB) using PCR. Moreover, partial DNA sequencing of toxigenic strains retrieved from dog and cat was carried out. Of 100 examined diarrheic animals, 90 (90%) were C. difficile positive, including 93.1% and 85.7% of dogs and cats, respectively. In addition, toxigenic strains were detected in 13 animals, giving an overall prevalence 13% with the following prevalence rates among dogs and cats 12.1% and 14.3%, respectively. Furthermore, the phylogenetic analysis of the obtained sequence revealed high genetic relatedness of tcdA sequence obtained from a cat to strains of human diarrheic cases to point out the public health threat of such sequence. In conclusion, the direct detection of toxigenic C. difficile using PCR among dogs and cats highlights the potential role of household pets as a source for such strains to human contacts.Puberty and the onset of menarche influences the motor performance of girls. However, the magnitude of these influences during varying maturity status, is not clear. This longitudinal study over two years aimed to investigate differences in motor fitness between early and late developing girls based on pre- and post-menarche status. A convenience sample (n = 58) of girls aged 13.51 ± 3.51, divided by means of the Status Quo method into pre (n = 13) and post-menarche (n = 45) groups, was used. Motor fitness was tested once annually by standardized protocols. Basic statistics, independent t-testing and a repeated measures ANOVA with a post hoc Bonferonni correction were used (p 0.05). Our data show that the potential to excel in sport based on motor capabilities can only be accurately estimated 1-2 years after reaching menarche.Cactaceae and Asphodelaceae are native desert plants known for their high mucilage content, which is a polysaccharide of growing interest in the food, cosmetic, and pharmaceutical industries. In this study, powdered mucilage was obtained from cladodes of Opuntia ficus-indica (OFI) and aloe vera (AV) leaves, and their molecular, morphological, and thermal properties were investigated and compared. Additionally, their dietary fiber content was determined. Three-dimensional molecular models were calculated for both mucilages using ab initio methods. Vibrational spectra (FTIR and Raman) revealed intramolecular interactions and functional groups that were specified with the help of theoretical ab initio and semi-empirical calculations. SEM micrographs measured at magnifications of 500× and 2000× demonstrated significantly different superficial and internal morphologies between these two mucilages. Thermal analysis using DSC/TGA demonstrated superior thermal stability for the OFI mucilage. The dietary fiber content in OFI mucilage was more than double that of AV mucilage. Our results show that both dehydrated mucilages present adequate thermal and nutritional properties to be used as functional ingredients in industrial formulations; however, OFI mucilage exhibited better physicochemical and functional characteristics than AV mucilage as a raw material.How to form carbon nanoscrolls with non-uniform curvatures is worthy of a detailed investigation. The first-principles method is suitable for studying the combined effects due to the finite-size confinement, the edge-dependent interactions, the interlayer atomic interactions, the mechanical strains, and the magnetic configurations. The complex mechanisms can induce unusual essential properties, e.g., the optimal structures, magnetism, band gaps and energy dispersions. To reach a stable spiral profile, the requirements on the critical nanoribbon width and overlapping length will be thoroughly explored by evaluating the width-dependent scrolling energies. A comparison of formation energy between armchair and zigzag nanoscrolls is useful in understanding the experimental characterizations. The spin-up and spin-down distributions near the zigzag edges are examined for their magnetic environments. This accounts for the conservation or destruction of spin degeneracy. The various curved surfaces on a relaxed nanoscroll will create complicated multi-orbital hybridizations so that the low-lying energy dispersions and energy gaps are expected to be very sensitive to ribbon width, especially for those of armchair systems. Finally, the planar, curved, folded, and scrolled graphene nanoribbons are compared with one another to illustrate the geometry-induced diversity.The early diagnosis of a motor is important. Many researchers have used deep learning to diagnose motor applications. This paper proposes a one-dimensional convolutional neural network for the diagnosis of permanent magnet synchronous motors. The one-dimensional convolutional neural network model is weakly supervised and consists of multiple convolutional feature-extraction modules. Through the analysis of the torque and current signals of the motors, the motors can be diagnosed under a wide range of speeds, variable loads, and eccentricity effects. The advantage of the proposed method is that the feature-extraction modules can extract multiscale features from complex conditions. The number of training parameters was reduced so as to solve the overfitting problem. Furthermore, the class feature map was proposed to automatically determine the frequency component that contributes to the classification using the weak learning method. The experimental results reveal that the proposed model can effectively diagnose three different motor states-healthy state, demagnetization fault state, and bearing fault state. In addition, the model can detect eccentric effects. By combining the current and torque features, the classification accuracy of the proposed model is up to 98.85%, which is higher than that of classical machine-learning methods such as the k-nearest neighbor and support vector machine.Personalized nutrition may be more effective in changing lifestyle behaviors compared to population-based guidelines. This single-arm exploratory study evaluated the impact of a 10-week personalized systems nutrition (PSN) program on lifestyle behavior and health outcomes. Healthy men and women (n = 82) completed the trial. Individuals were grouped into seven diet types, for which phenotypic, genotypic and behavioral data were used to generate personalized recommendations. Behavior change guidance was also provided. The intervention reduced the intake of calories (-256.2 kcal; p less then 0.0001), carbohydrates (-22.1 g; p less then 0.0039), sugar (-13.0 g; p less then 0.0001), total fat (-17.3 g; p less then 0.0001), saturated fat (-5.9 g; p = 0.0003) and PUFA (-2.5 g; p = 0.0065). Additionally, BMI (-0.6 kg/m2; p less then 0.0001), body fat (-1.2%; p = 0.0192) and hip circumference (-5.8 cm; p less then 0.0001) were decreased after the intervention. In the subgroup with the lowest phenotypic flexibility, a measure of the body’s ability to adapt to environmental stressors, LDL (-0.44 mmol/L; p = 0.002) and total cholesterol (-0.49 mmol/L; p less then 0.0001) were reduced after the intervention. This study shows that a PSN program in a workforce improves lifestyle habits and reduces body weight, BMI and other health-related outcomes. Health improvement was most pronounced in the compromised phenotypic flexibility subgroup, which indicates that a PSN program may be effective in targeting behavior change in health-compromised target groups.In a digital terrestrial multimedia broadcasting (DTMB)-based passive bistatic radar (PBR) system, the received reference signal often suffers from serious multipath effect, which decreases the detection ability of low-observable targets in urban environments. In order to improve the target detection performance, a novel reference signal purification method based on the low-rank and sparse feature is proposed in this paper. Specifically, this method firstly performs synchronization operations to the received reference signal and thus obtains the corresponding pseudo-noise (PN) sequences. Then, by innovatively exploiting the inherent low-rank structure of DTMB signals, the noise component in PN sequences is reduced. After that, a temporal correlation (TC)-based adaptive orthogonal matching pursuit (OMP) method, i.e., TC-AOMP, is performed to acquire the reliable channel estimation, whereby the previous noise-reduced PN sequences and a new halting criterion are utilized to improve channel estimation accuracy. Finally, the purification reference signal is obtained via equalization operation. The advantage of the proposed method is that it can obtain superior channel estimation performance and is more efficient compared to existing methods. Numerical and experimental results collected from the DTMB-based PBR system are presented to demonstrate the effectiveness of the proposed method.(1) Recently, metabolic profiling of the tissue in the native state or extracts of its metabolites has become increasingly important in the field of metabolomics. An important factor, in this case, is the presence of blood in a tissue sample, which can potentially lead to a change in the concentration of tissue metabolites and, as a result, distortion of experimental data and their interpretation. (2) In this paper, the metabolomic profiling based on NMR spectroscopy was performed to determine the effect of blood contained in the studied samples of brain tissue on their metabolomic profile. We used 13 male laboratory CD-1® IGS mice for this study. The animals were divided into two groups. The first group of animals (n = 7) was subjected to the perfusion procedure, and the second group of animals (n = 6) was not perfused. The brain tissues of the animals were homogenized, and the metabolite fraction was extracted with a water/methanol/chloroform solution. Samples were studied by high-frequency 1H-NMR spectroscopy with subsequent statistical data analysis. The group comparison was performed with the use of the Student’s test. We identified 36 metabolites in the brain tissue with the use of NMR spectroscopy. (3) For the major set of studied metabolites, no significant differences were found in the brain tissue metabolite concentrations in the native state and after the blood removal procedure. (4) Thus, it was shown that the presence of blood does not have a significant effect on the metabolomic profile of the brain in animals without pathologies.New mesomorphic series, 4-hexadecyloxy phenyl-imino-4′-(3-methoxyphenyl)-4″-alkoxybenzoates (An), were prepared and investigated with different thermal and mesomorphic techniques. The synthesized homologous series constitutes four members that differ from each other in the terminal length of flexible chain (n) attached to phenyl ester moiety, which varies between n = 6, 8, 10, and 12 carbons. A lateral CH3O group is attached to the central benzene ring in the meta position with respect to the ester moiety. Molecular structures of all newly prepared homologues were elucidated via FT-IR, 1H and 13C NMR spectroscopy. Mesomorphic and thermal properties were examined by differential scanning calorimetry (DSC), thermogravimetric analysis (TGA) and the mesophases identified by polarized optical microscopy (POM). DSC and POM examinations revealed that all members of the present series (An) exhibit a purely enantiotropic nematic (N) phase. Comparative evaluations and binary phase diagrams were established between the present homologues and their corresponding shorter one (Bn).