Governmental-Owner Power Imbalance and Privatization

Privatization is defined as the sale of state-owned assets by governmental agencies to private investors (e.g., Megginson, Nash, Netter, and Poulsen, 2004; Villalonga, 2000). Research on privatization has focused on privatization techniques (e.g., share issue privatization or voucher privatization), social welfare, governmental commitments to economic development, and varieties of outcomes of privatizations. Most prior studies from the financial economics perspective take privatization as a natural research context to examine the function of capital markets, the impact of national institutional settings, and the differences between partial privatization and initial public offerings. Very little research, however, has examined the determinants of privatization from an organizational perspective. This dissertation proposes that privatization decisions of state-owned enterprises (SOEs) are influenced by different interests in governmental agencies. Using the resource dependence theory, I studied the power relationships of SOEs and their governmental owners. Four panel databases of 206 pharmaceutical firms across eight years in China were combined to answer the research question of this dissertation: What is the role of power imbalance between different governmental owners in the privatization of an SOE? The results suggest that organizational effectiveness and efficiency of an SOE increase the likelihood of its privatization. Results also show that provincial governmental owners are more likely to privatize SOEs if they can successfully attract foreign direct investment projects. Furthermore, the likelihood of privatization increases with the power asymmetry between the provincial government and the central government but decreases with the degree of the defense mechanism used by SOEs

Rapid determination of trace Cu 2+ by an in-syringe membrane SPE and membrane solid-phase spectral technique

A new in-syringe membrane SPE and solid-phase visible spectral method was proposed for the rapid extraction and visible spectral determination of trace Cu2+. The chelation and membrane SPE can be accomplished in a syringe. The yellow Cu(DDTC)2 complex was separated using a polyethersulfone membrane from the sample solution. Then, the complex can be detected directly on the polyethersulfone membrane utilizing solid-phase visible absorbance spectra without elution. The proposed method simplified the experimental procedure and improved the sensitivity to the μg L-1 level. Furthermore, this method is environmentally friendly since it avoids the use of organic solvents. After the investigation of the influence of different variables on the membrane SPE procedure, water and blood plasma were analyzed to validate the proposed method. A LOD of 0.04 μg L-1 and recoveries of 96.0-103.7% confirmed that the present work can be applied for the determination of trace Cu2+ in water and blood plasma samples

Target-Grounded Graph-Aware Transformer for Aerial Vision-and-Dialog Navigation

This report details the method of the winning entry of the AVDN Challenge in ICCV 2023. The competition addresses the Aerial Navigation from Dialog History (ANDH) task, which requires a drone agent to associate dialog history with aerial observations to reach the destination. For better cross-modal grounding abilities of the drone agent, we propose a Target-Grounded Graph-Aware Transformer (TG-GAT) framework. Concretely, TG-GAT first leverages a graph-aware transformer to capture spatiotemporal dependency, which is beneficial for navigation state tracking and robust action planning. TG-GAT first leverages a graph-aware transformer to capture spatiotemporal dependencies for more robust action planning. In addition, an auxiliary visual grounding task is devised to boost the agent's awareness of referred landmarks. Moreover, a hybrid augmentation strategy based on large language models is utilized to mitigate data scarcity limitations. Our TG-GAT framework won the AVDN Challenge 2023, with 2.2% and 3.0% absolute improvements over the baseline on SPL and SR metrics, respectively. The code is available at https://github.com/yifeisu/avdn-challenge

Experimental Study on Landslides of Loose Sediment Slope Induced by Stream Bed Incision

Uplift of the Qinghai-Tibetan Plateau has resulted in rapid incision of rivers along the margin of the plateau. Landslides occur frequently as a consequence of increasing bank slope and potential landslide energy due to stream bed incision or lateral bank erosion on the concave banks at bends. The Fencha Gully is on the eastern margin of the Qinghai-Tibetan Plateau and is developing on a huge landslide body. Flume experiments were conducted on the base of the field investigation to study the mechanism of landslides induced by stream bed incision. The experiments were designed with a length scale ratio of 1:20. Landslides and stream bed incision with loose sediment were observed and analyzed. The results show that landslides are induced as a result of stream bed incision. The potential landslide energy is defined, which increases quickly with an effective incision depth coupling vertical incision and lateral bank erosion. The occurrence of landslides can be attributed to increasing incision depth and potential landslide energy. Results indicate that the critical effective incision depth is 4.0–6.0 m. A critical value of the potential landslide energy is found from the experiments. Landslides occur if the potential energy exceeds the critical energy, which is 2.24×104 t·m/s2 for the Fencha Gully. The incision depth and potential energy of landslides from the Fencha Gully agree well with the results

State control can result in good performance for firms

State firms are now hybrid organisations, say Ciprian Stan, David Ahlstrom, Mike W. Peng, Kehan Xu and Garry D. Bruto

L2L_2BN: Enhancing Batch Normalization by Equalizing the L2L_2 Norms of Features

In this paper, we show that the difference in $l_2$ norms of sample features can hinder batch normalization from obtaining more distinguished inter-class features and more compact intra-class features. To address this issue, we propose an intuitive but effective method to equalize the $l_2$ norms of sample features. Concretely, we $l_2$-normalize each sample feature before feeding them into batch normalization, and therefore the features are of the same magnitude. Since the proposed method combines the $l_2$ normalization and batch normalization, we name our method $L_2$BN. The $L_2$BN can strengthen the compactness of intra-class features and enlarge the discrepancy of inter-class features. The $L_2$BN is easy to implement and can exert its effect without any additional parameters or hyper-parameters. Therefore, it can be used as a basic normalization method for neural networks. We evaluate the effectiveness of $L_2$BN through extensive experiments with various models on image classification and acoustic scene classification tasks. The results demonstrate that the $L_2$BN can boost the generalization ability of various neural network models and achieve considerable performance improvements

Impacts of fertilization methods on Salvia miltiorrhiza quality and characteristics of the epiphytic microbial community

Plant epiphytic microorganisms have established a unique symbiotic relationship with plants, which has a significant impact on their growth, immune defense, and environmental adaptation. However, the impact of fertilization methods on the epiphytic microbial community and their correlation with the yield and quality of medicinal plant was still unclear. In current study, we conducted a field fertilization experiment and analyzed the composition of epiphytic bacterial and fungal communities employing high throughput sequencing data in different organs (roots, stems, and leaves) of Salvia miltiorrhiza, as well as their correlation with plant growth. The results showed that fertilization significantly affected the active ingredients and hormone content, soil physicochemical properties, and the composition of epiphytic microbial communities. After fertilization, the plant surface was enriched with a core microbial community mainly composed of bacteria from Firmicutes, Proteobacteria, and Actinobacteria, as well as fungi from Zygomycota and Ascomycota. Additionally, plant growth hormones were the principal factors leading to alterations in the epiphytic microbial community of S. miltiorrhiza. Thus, the most effective method of fertilization involved the application of base fertilizer in combination with foliar fertilizer. This study provides a new perspective for studying the correlation between microbial community function and the quality of S. miltiorrhiza, and also provides a theoretical basis for the cultivation and sustainable development of high-quality medicinal plants

Toxin inhibition in <i>C. crescentus</i> VapBC1 is mediated by a flexible pseudo-palindromic protein motif and modulated by DNA binding

Expression of bacterial type II toxin-antitoxin (TA) systems is regulated at the transcriptional level through direct binding of the antitoxin to pseudo-palindromic sequences on operator DNA. In this context, the toxin functions as a co-repressor by stimulating DNA binding through direct interaction with the antitoxin. Here, we determine crystal structures of the complete 90 kDa heterooctameric VapBC1 complex from Caulobacter crescentus CB15 both in isolation and bound to its cognate DNA operator sequence at 1.6 and 2.7 Å resolution, respectively. DNA binding is associated with a dramatic architectural rearrangement of conserved TA interactions in which C-terminal extended structures of the antitoxin VapB1 swap positions to interlock the complex in the DNA-bound state. We further show that a pseudo-palindromic protein sequence in the antitoxin is responsible for this interaction and required for binding and inactivation of the VapC1 toxin dimer. Sequence analysis of 4127 orthologous VapB sequences reveals that such palindromic protein sequences are widespread and unique to bacterial and archaeal VapB antitoxins suggesting a general principle governing regulation of VapBC TA systems. Finally, a structure of C-terminally truncated VapB1 bound to VapC1 reveals discrete states of the TA interaction that suggest a structural basis for toxin activation in vivo

Modulated model predictive current control of an indirect matrix converter with active damping

A modulated model predictive control (M²PC) scheme for an indirect matrix converter is proposed in this paper, including an active damping method to mitigate the input filter resonance. The control strategy allows the instantaneous power control and the output current control at the same time, operating at a fixed frequency. An optimal switching pattern is used to emulate the desired waveform quality features of space vector modulation and achieve zero-current switching operations. The active damping technique emulates a virtual resistor which damps the filter resonance. Simulation results present a good tracking to the output-current references, unity input displacement power factor, the low input-current distortions and a reduced common-mode voltage (CMV)