Earnings quality and stress levels of Chinese listed companies

This paper investigates the relation between earnings quality and stress levels of Chinese companies listed in Shanghai and Shenzhen stock exchanges from 2003 to 2007 by classifying them as financially stressed and bankrupt (SB), financially stressed and not bankrupt (SNB), and not financially stressed and not bankrupt (NSNB) firms. We measure the earnings quality by four separate attributes: accruals quality, earnings persistence, earnings predictability, and earnings smoothness. We find that earnings quality levels are parallel to firm\u27s stress levels: the SB firms have the lowest earnings quality measured by each of the four earnings attributes, the SNB firms have a lower earnings quality compared with the SB firms, the NSNB firms have the highest earnings quality. We also find that the earnings quality deteriorated over the study period, the number of SB firms with the lowest earnings quality increased, and the number of NSNB firms with the highest earnings quality decreased for the fiscal years 2003 to 2007

High-Performance Catalytic Four-Channel Hollow Fibers with Highly Dispersed Nickel Nanoparticles Prepared by Atomic Layer Deposition for Dry Reforming of Methane

Highly dispersed nickel (Ni) nanoparticles (NPs) with an average particle size of 4.3 nm were uniformly deposited on the outer surface, the inner channel surface, and inside the pores of 20 cm long four-channel α-Al2O3hollow fibers (HFs) by atomic layer deposition (ALD) for dry reforming of methane (DRM). Cerium oxide (CeO2) was added to promote the catalytic performance of Ni/Al2O3-HF catalysts. Rationally designed filling methods, by tuning the reactor size and inert fillings, can reduce the catalyst bed voidage in a fixed bed reactor for better reactant gas distribution, effectively utilize the Ni reactive sites, and achieve excellent catalytic performance. It was found that the CeO2-promoted Ni/Al2O3-HF catalyst was highly active and highly stable without deactivation during an overall 400-h DRM test at 850 °C. CeO2with reversible valence states could participate in surface reactions; especially, the formation of CeAlO3provided sufficient surface Ce3+for CO2activation and enhanced the stability and reusability of the HF catalysts

Universal approach to deterministic spatial search via alternating quantum walks

Spatial search is an important problem in quantum computation, which aims to find a marked vertex on a graph. We propose a novel and universal approach for designing deterministic quantum search algorithms on a variety of graphs via alternating quantum walks. The approach divides the search space into a series of subspaces and performs deterministic quantum searching on these subspaces. We highlight the flexibility of our approach by proving that for Johnson graphs, rook graphs, complete-square graphs and complete bipartite graphs, our quantum algorithms can find the marked vertex with $100\%$ success probability and achieve quadratic speedups over classical algorithms. This not only gives an alternative succinct way to prove the existing results, but also leads to new findings on more general graphs.Comment: The introduction has been revise

Engineering Metal-Oxide Interface by Depositing ZrO2 overcoating on Ni/Al2O3 for Dry Reforming of Methane

Zirconium oxide (ZrO2) was deposited onto Ni/Al2O3 catalyst as overcoating by atomic layer deposition (ALD) for dry reforming of methane (DRM). High-temperature heating during H2-reduction could transform the ALD-prepared ZrO2 thin film to tetragonal phase and crack the encapsulating layer on Ni sites, which constructed a beneficial Ni-ZrOx interface. Interfacial surface oxygen vacancies on ZrO2 overcoating were induced by the partial reduction of ZrO2 surface during high-temperature H2 reduction, with the assistance of Ni. During DRM, the interfacial oxygen vacancies enhanced CO2 activation by dissociating CO2 and releasing active O, thereby limiting carbon formation. For DRM at 700 °C and 800 °C, Ni/Al2O3 with 5 cycles of ZrO2 ALD overcoating enhanced both activity and stability significantly. For a 100-h DRM test at 600 °C, no deactivation was observed for the Ni/Al2O3 catalyst with 10 cycles of ZrO2 ALD overcoating, as compared to 59% relative activity loss of Ni/Al2O3

The role of acupoint stimulation as an adjunct therapy for lung cancer: A systematic review and meta-analysis

Background: Lung cancer is the leading cause of death in cancer patients. Clinical studies showed that a variety of acupoint stimulations have been extensively used for lung cancer patients, including needle insertion, injection with herbal extraction, plaster application, and moxibustion. However, the role of acupoint stimulation in lung cancer treatment was not fully reviewed. Methods: In the present study, we conducted a systematic review and meta-analysis on the role of acupoint stimulation in lung cancer treatment by electronic and manual searching in seven databases, including Ovid (Ovid MEDLINE, AMED, CAB Abstracts, EMBASE), EBSCOhost research databases (Academic Search premier, MEDLINE, CIHAHL Plus), PreQuest (British Nursing Index, ProQuest Medical Library, ProQuest Dissertations & Theses A&I, PsycINFO), and ISI web of knowledge (Web of Science, BIOSIS Citation Index, Biological Abstracts, Chinese Science Citation Database), CNKI, Wanfang Data, and CQVIP. Results: Our study showed that acupoint stimulation has strong immunomodulatory effect for lung cancer patients as demonstrated by the significant increase of IL-2, T cell subtypes (CD3+ and CD4+, but not CD8+ cells), and natural killer cells. Further analysis revealed that acupoint stimulation remarkably alleviates the conventional therapy-induced bone marrow suppression (hemoglobin, platelet, and WBC reduction) in lung cancer patients, as well as decreases nausea and vomiting. The pooled studies also showed that acupoint stimulation can improve Karnofsky performance status, immediate tumor response, quality of life (EORCT-QLQ-C30), and pain control of cancer patients. Conclusions: Acupoint stimulation is found to be effective in lung cancer treatment, further confirmatory evaluation via large scale randomized trials is warranted. © 2013 Chen et al.; licensee BioMed Central Ltd.published_or_final_versio

Patch Is Not All You Need

Vision Transformers have achieved great success in computer visions, delivering exceptional performance across various tasks. However, their inherent reliance on sequential input enforces the manual partitioning of images into patch sequences, which disrupts the image's inherent structural and semantic continuity. To handle this, we propose a novel Pattern Transformer (Patternformer) to adaptively convert images to pattern sequences for Transformer input. Specifically, we employ the Convolutional Neural Network to extract various patterns from the input image, with each channel representing a unique pattern that is fed into the succeeding Transformer as a visual token. By enabling the network to optimize these patterns, each pattern concentrates on its local region of interest, thereby preserving its intrinsic structural and semantic information. Only employing the vanilla ResNet and Transformer, we have accomplished state-of-the-art performance on CIFAR-10 and CIFAR-100, and have achieved competitive results on ImageNet