Nitrate sources and dynamics in a salinized river and estuary : a δ15N-NO₃⁻ and δ18O-NO₃⁻ isotope approach

To trace NO3- sources and assess NO3- dynamics in salinized rivers and estuaries, three rivers (Haihe River: HH River, Chaobaixin River: CB River and Jiyun River: JY River) and two estuaries (HH Estuary and CJ Estuary) along the Bohai Bay (China) have been selected to determine dissolved inorganic nitrogen (DIN: NH4+, NO2- and NO3-. Upstream of the HH River, NO3- was removed 30.9 +/- 22.1% by denitrification, resulting from effects of the floodgate: limiting water exchange with downstream and prolonging water residence time to remove NO3-. Downstream of the HH River NO3- was removed 2.5 +/- 13.3% by NO3- turnover processes. Conversely, NO3- was increased 36.6 +/- 25.2% by external N source addition in the CB River and 34.6 +/- 35.1% by instream nitrification in the JY River. The HH and CY Estuaries behaved mostly conservatively excluding the sewage input in the CJ Estuary. Hydrodynamics in estuaries has been changed by the ongoing reclamation projects, aggravating the loss of the attenuation function of NO3- in the estuary

Some Contributions in Statistical Discrimination of Different Pathogens Using Observations through FTIR

Fourier Transform Infrared (FTIR) has been use to discriminate different pathogens by signals from cells infected with these versus normal cells as references. To do the statistical analysis, Partial Least Square Regression (PLSR) was utilized to distinguish any two kinds of virus‐infected cells and normal cells. Validation using Bootstrap method and Cross‐validations were employed to calculate the shrinkages of Area Under the ROC Curve (AUC) and specificities corresponding to 80%, 90%, and 95% sensitivities. The result shows that our procedure can significantly discriminate these pathogens when we compare infected cells with the normal cells. On the height of this success, PLSR was applied again to simultaneously compare two kinds of virus‐infected cells and the normal cells. The shrinkage of Volume Under the Surface (VUS) was calculated to do the evaluation of model diagnostic performance. The high value of VUS demonstrates that our method can effectively differentiate virus‐infected cells and normal cells

Basicities, nucleophilicities, and bond dissociation enthalpies of organometallic complexes

It is widely recognized that the properties and reactivities of metal complexes are influenced by the basicity of the metal center. However, few quantitative data are available concerning the relationships between basicities and reactivities of metal complexes. In this research, correlations between basicities and nucleophilicities of a series of complexes CpIr(CO)(PR[subscript]3) have been studied. The basicities have been measured by the heat evolved ([delta]H[subscript] HM) when a metal complex is protonated by CF[subscript]3SO[subscript]3H in 1,2-dichloroethane (DCE) to form [CpIr(CO)(PR[subscript]3)(H)] CF[subscript]3SO[subscript]3 at 25.0°C (eq 1). The nucleophilicities have(DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)been studied by measuring rate constants (k) for their reactions with CH[subscript]3I to form [CpIr(CO)(PR[subscript]3)(CH[subscript]3)] I in CD[subscript]2Cl[subscript]2 at 25.0°C (eq 2). Excellent linear(DIAGRAM, TABLE OR GRAPHIC OMITTED...PLEASE SEE DAI)correlations are found between the basicities of the complexes ([delta]H[subscript] HM) and the basicities ([delta]H[subscript] HP) of the PR[subscript]3 ligands, and between [delta]H[subscript] HM and log k. A steric effect is observed when a bulky phosphine is used. A comparison of the effects of C[subscript]5Me[subscript]5 and C[subscript]5H[subscript]5 on both the basicities and nucleophilicities of Ir in these complexes is also presented;Homolytic bond dissociation enthalpies (BDEs) of the mononuclear cationic metal hydride complexes HML[subscript] n[superscript]+, where ML[subscript] n = Cr(CO)[subscript]2(dppm)[subscript]2, Mo(CO)[subscript]2(L-L)[subscript]2, W(CO)[subscript]3(PR[subscript]3)[subscript]3, W(CO)[subscript]2(dppm)[subscript]2, W(CO)[subscript]3(tripod), W(CO)[subscript]3(triphos), Cp*Re(CO)[subscript]2(PR[subscript]3), Fe(CO)[subscript]3(PR[subscript]3)[subscript]2, Fe(CO)[subscript]3(L-L), Cp*[subscript]2Ru, CpRu(PMe[subscript]3)[subscript]2I, CpRu(L-L)H, CpRu(PPh[subscript]3)[subscript]2H, Cp*[subscript]2Os, CpOs(PR[subscript]3)[subscript]2Br, CpOs(PPh[subscript]3)[subscript]2Cl, CpOs(PPh[subscript]3)[subscript]2H, CpIr(CO)(PR[subscript]3), CpIr(CS)(PPh[subscript]3), (C[subscript]5Me[subscript] nH[subscript] 5-n) Ir(COD), Cp*Ir(CO)(PR[subscript]3), and Cp*Ir(CO)[subscript]2 have been estimated by use of a thermochemical cycle that requires a knowledge of the heats of protonation ([delta]H[subscript] HM) and oxidation potentials (E[subscript]1/2) of the neutral metal complexes (ML[subscript] n). Excellent correlations were found between -[delta]H[subscript] HM and E[subscript]1/2 within related series of complexes. The BDE values obtained by this method fall in the range 56-75 kcal/mol. For related complexes of a given metal, the energy required for homolytic M-H bond cleavage (BDE) increases linearly as -[delta]H[subscript] HM for heterolytic M-H bond cleavage increases. The M-H BDE values are greater for third-row than second-row and first-row metals, the difference being 1-12 kcal/mol. Other trends in BDE values are also discussed

2-[(E)-2-(Nitro­methyl­idene)imidazolidin-1-yl]ethanol

In the title compound, C6H11N3O3, the imidazolidine NH group is involved in a three-center N—H⋯O hydrogen bond, with intra­molecular and inter­molecular branches, to the nitro group O atoms. The centrosymmetric dimers that are formed are further connected by O—H⋯O hydrogen bonds between the hy­droxy and nitro groups into a two-dimensional polymeric structure extending parallel to (101)

Adaptive fault-tolerant control of uncertain nonlinear systems under Actuator failure of unmanned aerial vehicles

With the increasingly extensive application of UAV technology, UAV accidents are increasing, and the safety problem is becoming more and more serious. Therefore, it is urgent to ensure the safety and reliability of UAV. This paper fi rstly introduces the application requirements and research signifi cance of the fault-tolerant control system of UAV; Secondly, the classifi cation of fault-tolerant control system of UAV is introduced. Finally, taking the nonlinear system of UAV as an example, the controller and its parameters are derived, and Simulink simulation model is established with MATLAB software to verify that the designed adaptive fault-tolerant controller can eff ectively maintain the stability and reliability of the system