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A bstract We investigate the causality and the stability of the relativistic viscous non-resistive magneto-hydrodynamics in the framework of the Israel-Stewart (IS) second-order theory, and also within a modified IS theory which incorporates the effect of magnetic fields in the relaxation equations of the viscous stress. We compute the dispersion relation by perturbing the fluid variables around their equilibrium values. In the ideal magnetohydrodynamics limit, the linear dispersion relation yields the well-known propagating modes: the Alfvén and the magneto-sonic modes. In the presence of bulk viscous pressure, the causality bound is found to be independent of the magnitude of the magnetic field. The same bound also remains true, when we take the full non-linear form of the equation using the method of characteristics. In the presence of shear viscous pressure, the causality bound is independent of the magnitude of the magnetic field for the two magneto-sonic modes. The causality bound for the shear-Alfvén modes, however, depends both on the magnitude and the direction of the propagation. For modified IS theory in the presence of shear viscosity, new non-hydrodynamic modes emerge but the asymptotic causality condition is the same as that of IS. In summary, although the magnetic field does influence the wave propagation in the fluid, the study of the stability and asymptotic causality conditions in the fluid rest frame shows that the fluid remains stable and causal given that they obey certain asymptotic causality condition.

Academic collaborations improve research efficiency and spur scientific innovation. However, scholarly big data has hindered scholars from finding suitable collaborators. Although some studies have involved the prediction problem of academic collaborations, they neglect the rich dynamic information of the heterogeneous academic network. In this paper, we propose a prediction model for academic collaborations, which considers both the dynamic structure and content information. We first formally define the dynamic academic network and the collaboration prediction problem. Then, a scholar representation model is designed by capturing both the dynamic structure and content features, together with the macro-impact of overall academic trends. Finally, we build the prediction model based on the representation result of scholars. Extensive experiments for predicting new collaborations are conducted on the DBLP dataset. The experimental results on the accuracy, F1, and AUC metrics demonstrate that our method outperforms the baseline methods and can predict academic collaborations efficiently.

To meet the increasing need of high-data-rate and broadband wireless communication systems, the devices and its circuits R&D under Millimeter, Sub-Millimeter, or even Terahertz (THz) frequency bands are attracting more and more attention from not only academic, but also industrial areas. Most of the former research on the THz waveband (0.1–10 THz) antenna design is mainly focused on realizing high directional gain, such as horn antennas, even though the coverage area is very limited when comparing with the current Wi-Fi system. One solution for the horizontally omnidirectional communication antenna is using the structure of multiple split-ring resonators (MSRRs). Aiming at this point, a novel 300 GHz microstrip antenna array based on the dual-surfaced multiple split-ring resonators (DSMSRRs) is proposed in this paper. By employing the two parallel microstrip transmission lines, different MSRRs are fed and connected on two surfaces of the PCB with a centrally symmetric way about them. The feeding port of the whole antenna is in between the centers of the two microstrip lines. Thus, this kind of structure is a so-called DSMSRR. Based on the different size of the MSRRs, different or multiple working wavebands can be achieved on the whole antenna. Firstly, in this paper, the quasi-static model is used to analyze the factors affecting the resonance frequency of MSRRs. Simulation and measured results demonstrate that the resonant frequency of the proposed array antenna is 300 GHz, which meets the design requirements of the expected frequency point and exhibits good radiation characteristics. Then, a dual-band antenna is designed on the above methods, and it is proved by simulation that the working frequency bands of the proposed dual-band antenna with reflection coefficient below −10 dB are 274.1–295.6 GHz and 306.3–313.4 GHz.

Background Arbuscular mycorrhizal fungi (AMF) enhance plant drought tolerance partly by promoting soluble sugar accumulation, the mechanisms by which AMF colonization influences host sugar metabolism and associated gene expression under drought remain poorly understood. This study therefore examined the effects of inoculation with Funneliformis mosseae (T.H. Nicolson & Gerd.) C. Walker & A. Schüßler on the growth, water status, sugar profiles, and the expression/activity of sucrose-associated genes in the leaves of trifoliate orange ( Citrus trifoliata L.) under water stress conditions. Results Over a 10-week water stress period, the root colonization by F. mosseae decreased by 14.36%, compared with ample water controls. Under water stress, F. mosseae inoculation significantly promoted plant growth performance (height, leaf number, and stem thickness), leaf water potential, nitrogen balance index, and chlorophyll index compared to those without inoculation. Ten sugar components (eight monosaccharides and two disaccharides) were detected. Inoculation with F. mosseae significantly elevated leaf contents of D-fructose, D-galactose, glucose, and inositol under both ample water and water stress conditions. It also increased leaf contents of D-arabinose under water stress, while decreasing the sucrose content under ample water conditions. The presence of the fungus boosted the acid invertase (AI) activity under water stress and up-regulated the relative expression of CtAI , CtNI , and CtSPS genes in leaves under both conditions. These gene expressions displayed a significantly positive correlation with root mycorrhizal colonization rate and glucose content, but a negative correlation with sucrose content. Conclusion F. mosseae modulated leaf sugar profiles in trifoliate orange under water stress, particularly by regulating sucrose synthesis and cleavage through modulating the expression of sucrose-associated genes. Since this study focused on a single AMF species and leaf response, further work should investigate diverse AMF species and sugar profiles in other plant tissues under water stress.

In this study, dormitory room and social group assignment data from a college are used to investigate peer effects on college students' decisions to switch majors. Results reveal strong evidence of such peer effects at both the room and the social group level. Most notably, at the room level, the dense concentration of same-major roommates deters students from switching majors; having one or two same-major roommates has no significant effect on major switching, indicating strong nonlinearity of peer effects at the room level. Such nonlinearity is not observed among social group members. Results also reveal evidence that students' choices of new majors are affected by peers' majors. Peers are more likely to choose the same destination majors than nonpeers. In choosing their new majors, students do not necessarily follow their peers indiscriminately. Their decisions seem to be influenced more by short-term academic requirements than by long-term job prospects. Finally, peer effects on major switching and major choices are stronger at the dormitory room level than at the social group level in most cases.

Since the onset of agriculture, soils have lost their organic carbon to such an extent that the soil functions of many croplands are threatened. Hence, there is a strong demand for mapping and monitoring critical soil properties and in particular soil organic carbon (SOC). Pilot studies have demonstrated the potential for remote sensing techniques for SOC mapping in croplands. It has, however, been shown that the assessment of SOC may be hampered by the condition of the soil surface. While growing vegetation can be readily detected by means of the well-known Normalized Difference Vegetation Index (NDVI), the distinction between bare soil and crop residues is expressed in the shortwave infrared region (SWIR), which is only covered by two broad bands in Landsat or Sentinel-2 imagery. Here we tested the effect of thresholds for the Cellulose Absorption Index (CAI), on the performance of SOC prediction models for cropland soils. Airborne Prism Experiment (APEX) hyperspectral images covering an area of 240 km2 in the Belgian Loam Belt were used together with a local soil dataset. We used the partial least square regression (PLSR) model to estimate the SOC content based on 104 georeferenced calibration samples (NDVI < 0.26), firstly without setting a CAI threshold, and obtained a satisfactory result (coefficient of determination (R2) = 0.49, Ratio of Performance to Deviation (RPD) = 1.4 and Root Mean Square Error (RMSE) = 2.13 g kgC−1 for cross-validation). However, a cross comparison of the estimated SOC values to grid-based measurements of SOC content within three fields revealed a systematic overestimation for fields with high residue cover. We then tested different CAI thresholds in order to mask pixels with high residue cover. The best model was obtained for a CAI threshold of 0.75 (R2 = 0.59, RPD = 1.5 and RMSE = 1.75 g kgC−1 for cross-validation). These results reveal that the purity of the pixels needs to be assessed aforehand in order to produce reliable SOC maps. The Normalized Burn Ratio (NBR2) index based on the SWIR bands of the MSI Sentinel 2 sensor extracted from images collected nine days before the APEX flight campaign correlates well with the CAI index of the APEX imagery. However, the NBR2 index calculated from Sentinel 2 images under moist conditions is poorly correlated with residue cover. This can be explained by the sensitivity of the NBR2 index to both soil moisture and residues.

Equitable human resource allocation can maximize the efficiency of resources and optimize business performance. Despite numerous methods that have been suggested for solving the allocation problem, most of the existing methods focus on a single resource or task, and neglect the effects of team composition in business performance. In this paper, we introduce team faultlines to the human resource allocation problem. We first analyze resource characteristics from a demographic perspective and business process, then utilize the information value to select key characteristics and determine the corresponding weight. Second, we qualitatively identify team faultlines based on the clustering results of human resources and quantitatively measure the strength and distance of team faultlines. Multi-layer perceptron is utilized to build the base and ensemble performance prediction model. The allocation model and flow are designed subsequently. The reasonableness and effectiveness are evaluated with a real-world scenario, and the results show that our human resource allocation method using team faultlines can allocate human resources with high performance and optimize the business process.

Γ-aminobutyric acid (GABA), a major inhibitory neurotransmitter in the central nervous system, has been shown to alleviate various physiological disorders including insomnia, hypertension, depression, and memory loss. Lactic acid bacteria (LAB), recognized as safe GABA producers, have attracted increasing attention. This study aimed to screen GABA-producing LAB from naturally fermented dairy products and evaluate their probiotic potential, antioxidant and neuromodulatory activities, while optimizing GABA production. GABA-producing LAB were screened using the Berthelot method and thin-layer chromatography. The safety of  Lactiplantibacillus plantarum  SY1 was assessed through hemolysin production and drug sensitivity tests.  L. plantarum  SY1 demonstrated high tolerance to acidic conditions and low bile salt concentrations, along with significant antioxidant capacity (49 ± 0.2% DPPH radical scavenging rate, 86.1 ± 0.14% hydroxyl radical scavenging rate, and 32.7 ± 1.6% superoxide radical anion scavenging rate). In vivo experiments revealed that  L. plantarum  SY1 extended the lifespan of  C. elegans  N2, enhanced oxidative stress resistance, and delayed paralysis in transgenic  C. elegans  (CL4176) by 23.53%. Through OFAT strategy and RSM optimization, GABA production reached 1.49 g/L under optimal conditions (37℃, pH 4.44, 96 h fermentation, and 4.16% inoculum). These findings demonstrate that  L. plantarum  SY1 is a promising GABA-producing strain with antioxidant and neuromodulatory effects, suggesting its potential as an anti-aging and neuroprotective probiotic.

This historical study investigates the concept of learner autonomy in the national English language curricula for Chinese universities. It seeks to understand the meaning of learner autonomy in China and the intentionality of promoting this concept through the curricula from 1978 to 2007. By adopting Quentin Skinner’s intentionalist approach to analyzing the history of ideas, this study conducted a systematic document analysis of three national curricula in relation to their linguistic and practical contexts constituted of 169 Chinese academic articles in total. The study revealed that learner autonomy mainly referred to students’ motivation and ability to work hard on their own outside the classroom in the Chinese context. Importing this concept, however, caused ideological confusion and exacerbated the disempowerment of teachers within the dynamics of China’s English language education at the tertiary level. The study raises awareness for borrowing concepts across different cultural contexts and has implications for research, policymaking, teacher development, and pedagogical practice in second language education in China.