The Financial Deepening-Productivity Nexus in China: 1987-2001

The financial intermediation-growth nexus is a widely studied topic in the literature of development economics. Deepening financial intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Relying on provincial panel data from China, this paper attempts to examine if regional productivity growth is accounted for by the deepening process of financial development. Towards this end, an appropriate measurement of financial depth is constructed and then included as a determinant of productivity growth. It finds that a significant and positive nexus exists between financial deepening and productivity growth. Given the divergent pattern of financial deepening between coastal and inland provinces, this finding also helps explain the rising regional disparity in China.growth, financial development, productivity, China

The financial deepening-productivity nexus in China: 1987 - 2001

The financial intermediation-growth nexus is a widely studied topic in the literature of development economics. Deepening financial intermediation may promote economic growth by mobilizing more investments, and lifting returns to financial resources, which raises productivity. Relying on provincial panel data from China, this paper attempts to examine if regional productivity growth is accounted for by the deepening process of financial development. Towards this end, an appropriate measurement of financial depth is constructed and then included as a determinant of productivity growth. It finds that a significant and positive nexus exists between financial deepening and productivity growth. Given the divergent pattern of financial deepening between coastal and inland provinces, this finding also helps explain the rising regional disparity in China

Coordination chemistry and catalysis at iron: from non-innocent ligands to CO2 transformation

L'utilisation du fer en chimie de coordination et en catalyse suscite un intérêt croissant de par son abondance et sa faible toxicité. Dans le premier chapitre, une étude bibliographique présente deux domaines d'applications du fer : i) l'utilisation de complexes de fer comportant des ligands " non innocent " pour différentes applications en catalyse, et ii) l'utilisation de complexes de fer pour des transformations stœchiométriques et catalytiques du CO2. Dans le chapitre 2, la synthèse et la caractérisation de complexes de fer portant un ligand coopératif non-innocent sont présentées. Le composé hautement réactif [Fe(N(TMS)2)2] a été choisi comme précurseur pour l'étude de la coordination du ligand bis(picolyl)phosphine dans des conditions douces. Une famille de complexes mono- et di-nucléaires de fer a été isolée et le comportement " non-innocent " du ligand a été mis en évidence. La combinaison de plusieurs techniques : diffraction des rayons X, RMN (en solution et à l'état solide), RPE, Mössbauer et spectroscopie infrarouge a permis de complètement caractériser à la fois les complexes diamagnétiques mais aussi paramagnétiques. Le chapitre 3 se concentre sur la transformation de CO2 par un système catalytique efficace au fer. Les complexes dihydrure de fer [Fe(H)2(diphosphine)2] catalysent la fonctionnalisation réductrice du CO2 dans des conditions douces. Dans ce système, la première étape concerne la réduction catalytique du CO2 par des hydroboranes donnant un composé bis(boryl)acetal. Via une stratégie " un pot, deux étapes " l'intermédiaire acétal est ensuite utilisé comme source de méthylène et est fonctionnalisé pour donner une série de composés organiques contenant non seulement des liaisons C-N mais aussi des liaisons C-O, C-S et C-C avec de bons à très bons rendements.There is an increasing interest in the use of iron in coordination chemistry and catalysis because it is an earth abundant metal which exhibits a low toxicity. The first chapter is a bibliographic study concerning two areas of applications for iron: the combination of iron with non-innocent ligands leading to highly active catalysts, and the use of iron complexes for CO2 transformations at the stoichiometric and catalytic levels. In chapter 2, the synthesis and characterization of iron complexes bearing a cooperative non-innocent ligand are presented. The highly reactive compound [Fe(N(TMS)2)2] has been chosen as a precursor for the study of the coordination of the bis(picolyl)phosphine ligand under mild conditions. As a result, a family of mono- and di-meric iron complexes has been isolated and the non-innocent behavior of the ligand has been observed. The combination of several techniques: X-ray diffraction, NMR (in solution and in the solid state), EPR, Mössbauer and infrared spectroscopy allows to clearly characterize both diamagnetic and paramagnetic complexes. Chapter 3 focuses on the transformation of CO2 catalyzed by an efficient iron-based system. In this system, iron hydride complexes [Fe(H)2(diphosphine)2] have been chosen to catalyze the reductive functionalization of CO2 through a one-pot two steps strategy under mild conditions. The first step concerns the iron-catalyzed reduction of CO2 by hydroboranes affording a bis(boryl)acetal compound. This intermediate is then used as a source of methylene in functionalization reactions, leading to a series of organic compounds containing not only C-N but also C-O, C-S, and C-C bonds in good yields

Diaqua­bis­{1-[(1H-benzimidazol-2-yl)meth­yl]-1H-1,2,4-triazole-κN 4}bis­(2,4,5-tricarb­oxy­benzoato-κO 1)cadmium dihydrate

In the title complex, [Cd(C10H5O8)2(C10H9N5)2(H2O)2]·2H2O, the CdII ion lies on an inversion center and is coordinated by two N atoms from two symmetry-related 1-[(1H-benzimidazol-2-yl)meth­yl]-1H-1,2,4-triazole ligands and two O atoms from two monodeprotonated 2,4,5-tricarb­oxy­benzoate anions in equatorial positions and by two water O atoms in axial positions, leading to a distorted octa­hedral environment. In the crystal, complex mol­ecules and solvent water mol­ecules are linked through inter­molecular O—H⋯O, O—H⋯N and N—H⋯O hydrogen bonds into a three-dimensional network. Intra­molecular O—H⋯O hydrogen bonds are also present

Diaqua­[5,5′-dicarb­oxy-2,2′-(propane-1,3-di­yl)bis­(1H-imidazole-4-carboxyl­ato)]manganese(II)

The complex mol­ecule of the title compound, [Mn(C13H10N4O8)(H2O)2] or [Mn(H4pbidc)(H2O)2] (H6pbidc = 2,2′-(propane-1,3-di­yl)bis­(1H-imidazole-4,5-dicarb­oxy­lic acid), has 2 symmetry with the twofold rotation axis running through the Mn2+ cation and the central C atom of the propanediyl unit. The cation is six-coordinated by two N atoms and two O atoms from one H4pbidc2− anion and two water O atoms in a considerably distorted octa­hedral coordination. In the crystal, adjacent mol­ecules are linked through O—H⋯O and N—H⋯O hydrogen bonds into a three-dimensional network

Rhizobacterial community structure in response to nitrogen addition varied between two Mollisols differing in soil organic carbon

Excessive nitrogen (N) fertilizer input to agroecosystem fundamentally alters soil microbial properties and subsequent their ecofunctions such as carbon (C) sequestration and nutrient cycling in soil. However, between soils, the rhizobacterial community diversity and structure in response to N addition is not well understood, which is important to make proper N fertilization strategies to alleviate the negative impact of N addition on soil organic C and soil quality and maintain plant health in soils. Thus, a rhizo-box experiment was conducted with soybean grown in two soils, i.e. soil organic C (SOC)-poor and SOC-rich soil, supplied with three N rates in a range from 0 to 100 mg N kg−1. The rhizospheric soil was collected 50 days after sowing and MiSeq sequencing was deployed to analyze the rhizobacterial community structure. The results showed that increasing N addition significantly decreased the number of phylotype of rhizobacteria by 12.3%, and decreased Shannon index from 5.98 to 5.36 irrespective of soils. Compared to the SOC-rich soil, the increases in abundances of Aquincola affiliated to Proteobacteria, and Streptomyces affiliated to Actinobacteria were greater in the SOC-poor soil in response to N addition. An opposite trend was observed for Ramlibacter belong to Proteobacteria. These results suggest that N addition reduced the rhizobacterial diversity and its influence on rhizobacterial community structure was soil-specific

A Deep Learning Onion Peeling Approach to Measure Oral Epithelium Layer Number

Head and neck squamous cell carcinoma (HNSCC), specifically in the oral cavity (oral squamous cell carcinoma, OSCC), is a common, complex cancer that significantly affects patients\u27 quality of life. Early diagnosis typically improves prognoses yet relies on pathologist examination of histology images that exhibit high inter- and intra-observer variation. The advent of deep learning has automated this analysis, notably with object segmentation. However, techniques for automated oral dysplasia diagnosis have been limited to shape or cell stain information, without addressing the diagnostic potential in counting the number of cell layers in the oral epithelium. Our study attempts to address this gap by combining the existing U-Net and HD-Staining architectures for segmenting the oral epithelium and introducing a novel algorithm that we call Onion Peeling for counting the epithelium layer number. Experimental results show a close correlation between our algorithmic and expert manual layer counts, demonstrating the feasibility of automated layer counting. We also show the clinical relevance of oral epithelial layer number to grading oral dysplasia severity through survival analysis. Overall, our study shows that automated counting of oral epithelium layers can represent a potential addition to the digital pathology toolbox. Model generalizability and accuracy could be improved further with a larger training dataset

Autophagy promotes tumor cell survival and restricts necrosis, inflammation, and tumorigenesis

SummaryDefective apoptosis renders immortalized epithelial cells highly tumorigenic, but how this is impacted by other common tumor mutations is not known. In apoptosis-defective cells, inhibition of autophagy by AKT activation or by allelic disruption of beclin1 confers sensitivity to metabolic stress by inhibiting an autophagy-dependent survival pathway. While autophagy acts to buffer metabolic stress, the combined impairment of apoptosis and autophagy promotes necrotic cell death in vitro and in vivo. Thus, inhibiting autophagy under conditions of nutrient limitation can restore cell death to apoptosis-refractory tumors, but this necrosis is associated with inflammation and accelerated tumor growth. Thus, autophagy may function in tumor suppression by mitigating metabolic stress and, in concert with apoptosis, by preventing death by necrosis

A Deep Learning Onion Peeling Approach to Measure Oral Epithelium Layer Number.

Head and neck squamous cell carcinoma (HNSCC), specifically in the oral cavity (oral squamous cell carcinoma, OSCC), is a common, complex cancer that significantly affects patients\u27 quality of life. Early diagnosis typically improves prognoses yet relies on pathologist examination of histology images that exhibit high inter- and intra-observer variation. The advent of deep learning has automated this analysis, notably with object segmentation. However, techniques for automated oral dysplasia diagnosis have been limited to shape or cell stain information, without addressing the diagnostic potential in counting the number of cell layers in the oral epithelium. Our study attempts to address this gap by combining the existing U-Net and HD-Staining architectures for segmenting the oral epithelium and introducing a novel algorithm that we call Onion Peeling for counting the epithelium layer number. Experimental results show a close correlation between our algorithmic and expert manual layer counts, demonstrating the feasibility of automated layer counting. We also show the clinical relevance of oral epithelial layer number to grading oral dysplasia severity through survival analysis. Overall, our study shows that automated counting of oral epithelium layers can represent a potential addition to the digital pathology toolbox. Model generalizability and accuracy could be improved further with a larger training dataset