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C26H36N4O14Co, triclinic, P1̄ (no. 2), a = 7.1895(7) Å, b = 8.7773(9) Å, c = 10.9067(11) Å, α = 98.180(2)°, β = 104.0480(10)°, γ = 90.180(2)°, V = 660.37(11) Å3, Z = 1, Rgt(F) = 0.0287, wRref(F2) = 0.0751, T = 296.15 K. [ABSTRACT FROM AUTHOR]

This study focuses on the energy variation rules of gas hydrate-bearing coal during deformation and failure, combined with the deviatoric stress-strain curves under conventional triaxial compression and the first law of thermodynamics. The results show that the elastic strain energy is dominant in the process of pre-peak deformation and failure of gas hydrate-bearing coal; while the gas hydrate-bearing coal may experience energy dissipation after the peak stress. Then, the total energy, elastic strain energy and dissipation energy all increase with increasing of the confining pressure and the saturation. Furthermore, the multiple linear regression equation depicting the viriation of saturation and confining pressure was established with the total energy of the critical failure point, with the better fitting effect. Moreover, the elastic energy accumulation at the failure point increases, thus producing the larger dissipation energy.

To establish a method for the determination of phthalic acid esters in Peanut oil, Peanut oil samples were extracted with n-hexane saturated acetonitrile, purified by 25 mg PSA and 25 mg C18 and detected by GC-MS selected ion monitoring (SIM) mode detection, external standard method quantitative.The standard solution of 17 phthalates showed a good linearity in the concentration range of 0.02～3.0 mg/L,and the correlation coefficient (r) is above 0.999, the detection limit (LOD) was 0.01 mg/kg to 0.02 mg/kg,and the quantitative limit (LQD) was 0.03 mg/kg to 0.05 mg/kg. the recovery of standard addition was 92.47% to 108.72%, and the relative standard deviation was 1.10% to 5.94%.The method is simple, rapid,sensitive and accurate. and can be used for the determination of 17 phthalates in Peanut oils.

This paper aims at quantitatively and qualitatively analyzing the use and distribution of informality features in a comparable corpus of research articles (rAs) written by L1 Chinese scholars (Css) and L1 English scholars (Ess) across four disciplines. The normalized frequencies of eleven informal features were calculated and compared first between Ess’ and Css’ rAs in the same discipline and then across the four disciplines. Four features, namely first person pronouns, pronominal anaphoric reference, sentence-initial conjunctions/conjunctive adverbs, and imperatives, were identified to be the contributing factors and analyzed qualitatively. The results demonstrate that: (i) there is significant difference in the use of informality features between Ess and Css with Css employing informality features less frequently than Ess; (ii) disciplinary variations are present with Physics rAs sounding more informal and Linguistics rAs more formal; (iii) the distribution of specific informality features presents a diversified picture: Css’ use of first person pronouns and pronominal anaphoric references is less frequent, and their use of imperatives and sentence-initial conjunctions/conjunctive adverbs is more frequent than Ess’. These findings shed light on teaching academic writing and provide writers with some guidance about stylistic choice.

Introduction: The aim of the study was to investigate differences in the intra- and inter-network functional connectivity (FC) of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) in patients with tinnitus, with (T + H) or without hearing loss (T). Methods: We performed rs-fMRI on 82 participants (21 T, 32 T + H, and 29 healthy controls). An independent component analysis (ICA) was performed to obtain the resting-state networks (RSNs) and calculate the differences in FC. Moreover, we investigated the relationships between networks using functional network connectivity analysis. Results: We identified nine major RSNs, including the auditory network; default mode network; executive control network (ECN), including the right frontoparietal network and left frontoparietal network (LFPN); somatomotor network (SMN); dorsal attention network; ventral attention network; salience network (SN); and visual network (VN). These RSNs were extracted in all groups using ICA. Compared with that in the control group, we observed reduced FC between the LFPN and VN in the T group and between the LFPN and SN in the T + H group. The inter-network connectivity analysis revealed decreased network interactions in the SMN (IC 22)-ECN (IC 2), SMN (IC 22)-VN (IC 8), and VN (IC 14)-SN (IC 3) connections in the T + H group, compared with the healthy control group. Furthermore, we observed significantly decreased network interactions in the SMN (IC 22)-VN (IC 8) in the T group. Conclusions: Our results indicated abnormalities within the brain networks of the T and T + H groups, including the SMN, ECN, and VN, compared with the control group. Furthermore, both T and T + H groups demonstrated reduced FC between the LFPN, VN, and SMN. There were no significant differences between the T and the T + H groups. Furthermore, we observed reduced FC between the right olfactory cortex and the orbital part of the right middle frontal gyrus, right precentral gyrus, left dorsolateral superior frontal gyrus, and right triangular part of the inferior frontal gyrus within the T and T + H groups. Thus, disruptions in brain regions responsible for attention, stimulus monitoring, and auditory orientation contribute to tinnitus generation. [ABSTRACT FROM AUTHOR]

This study investigates the synergistic effect and mechanism of gelling materials with blast furnace slag (BFS), steel slag (SS) and desulphurization gypsum (DG) as the main components on the hardening of heavy metal ions by lead and zinc tailings. It is found that lead and zinc tailing (LZT) is mainly composed of dolomite and quartz and contain small amounts of calcium, aluminum, iron, magnesium and other elements as well as heavy metals such as lead and zinc. By the mechanical activation method, it is found that the lead and zinc tailings powder has the largest specific surface area and the highest activity index when the ball milling time is 2 h. At a hardening timepoint of 28 d, the calcite crystals in the samples are intertwined with the amorphous C-S-H gel (C-S-H gels are mainly composed of 3CaO∙SiO2 and 2CaO∙SiO2), which enhances the structural strength of the samples. The chemical reaction analysis confirmed that the formation of calcite is a major driver for the hydration reaction of the steel slag–desulphurization gypsum (SSSDG) system. Overall, the slag, steel slag and desulphurization gypsum solid waste-based gelling materials have synergistic effects in hardening heavy metals by limiting the leaching of metal ions, adsorbing metal ions and hardening heavy metals, and facilitating the hydration process through the formation of compound salt precipitates. [ABSTRACT FROM AUTHOR]