Hierarchical Structuring of a Workflow Model in Petri-Net

In this paper, we introduce the way of deriving hierarchical structure of a workflow model represented in classical Petrinet, even for the cases with cycles, which allows handling a workflow model efficiently. More specifically, our method identifies any block structures as candidates for the subprocesses and represents them as a single block node in the upper layer of the hierarchical model. The proposed method can make workflow analysis and design more accurate and efficient and further lead to a better design on a collaborate environment

Transaction Complexity and the Movement to Fair Value Accounting

Our global economy has pushed the complexity of business transactions to a new level, as companies now employ sophisticated contracts and financial instruments. However, it is unclear whether accounting standards are able to effectively capture transaction complexity, which has been growing at a rapid pace. In this study, we examine three questions related to transaction complexity: (1) Do accounting standards reflect differences in the complexity of the transactions being recorded? (2) Does the use of mark-to-market (i.e., fair value) accounting reduce the complexity of standards by relying on market valuations to capture transaction complexity? (3) Does the reliance on fair value measurements reduce audit costs for transactions with significant complexity? Our findings suggest that complex transactions result in complex accounting guidance, making the standards difficult to read and understand. However, the use of fair value accounting might be a solution to the challenges arising from transaction complexity. Our study informs regulatory bodies, investors, creditors, and public companies that are increasingly concerned about the state of financial reporting standards, which arguably have become very costly to implement yet less effective in communicating the economic substance of complex transactions

Does judicial foreclosure procedure help delinquent subprime mortgage borrowers?

We conduct comprehensive analyses on whether and how the judicial foreclosure procedure helps subprime mortgage borrowers to reinstate their delinquent loans outside foreclosure liquidation. Even though the transition rates of various exit types are all higher in non-judicial states, we argue such higher rates can be mechanically driven by the faster shrinking pool of delinquent mortgages in non-judicial states over time. Based on the cumulative proportions of various exit types during a period of up to 5 years post the mortgage first become 90 days past due, we find that judicial states offer more opportunities for delinquent borrowers to reinstate their loans outside foreclosure liquidation, especially during a housing market downturn. Cures, modifications, and paid-offs were all important alternative ways to resolve serious delinquencies during 2007–2008. After modifications became widely available in 2009, loan modifications became the most important alternative for subprime borrowers to reinstate their delinquent mortgages outside foreclosure liquidation. The lion\u27s share of the judicial foreclosure benefit shows up after the start of the foreclosure process

Strategic Default Induced by Loan Modification Programs

We use the October 2008 Countrywide legal settlement as a natural experiment to investigate how borrowers may change their payment behavior to be eligible for loan modifications. We find that the Countrywide modification program induces strategic default among both borrowers current in their loan payments and those already in payment delinquency before the settlement. By January 2009, modification-induced strategic default is about nine percentage points, on a base default rate of 30 percent, and such strategic behavior is more severe among riskier loans. These findings have implications on designs of loan modification programs that are different from the existing literature

Strategic Default Induced by Loan Modification Programs

We use the October 2008 Countrywide legal settlement as a natural experiment to investigate how borrowers may change their payment behavior to be eligible for loan modifications. We find that the Countrywide modification program induces strategic default among both borrowers current in their loan payments and those already in payment delinquency before the settlement. By January 2009, modification-induced strategic default is about nine percentage points, on a base default rate of 30 percent, and such strategic behavior is more severe among riskier loans. These findings have implications on designs of loan modification programs that are different from the existing literature

Strategies on Poisonous Plants Problem in China

Poisonous plants are widely distributed on large areas of native grasslands of China, causing livestock poisoning and grassland degradation, which severely impacts the development of animal husbandry. Of the almost 300 poisonous species that are responsible for livestock losses in China, locoweed, drunken horse grass and Langdu cause the greatest impact. Many strategies have been developed to minimise the impact of poisonous plants including the treatment of livestock that have been poisoned, controlling poisonous plants and managing livestock grazing. Both physical and chemical traditional methods are still used to eliminate poisonous plants while biological control using specific insects may eventually be used to control certain species. According to a grassland law, grazing systems (rotational, rest and forbidden grazing) may be applied on dense stands of poisonous plants

Generative Watermarking Against Unauthorized Subject-Driven Image Synthesis

Large text-to-image models have shown remarkable performance in synthesizing high-quality images. In particular, the subject-driven model makes it possible to personalize the image synthesis for a specific subject, e.g., a human face or an artistic style, by fine-tuning the generic text-to-image model with a few images from that subject. Nevertheless, misuse of subject-driven image synthesis may violate the authority of subject owners. For example, malicious users may use subject-driven synthesis to mimic specific artistic styles or to create fake facial images without authorization. To protect subject owners against such misuse, recent attempts have commonly relied on adversarial examples to indiscriminately disrupt subject-driven image synthesis. However, this essentially prevents any benign use of subject-driven synthesis based on protected images. In this paper, we take a different angle and aim at protection without sacrificing the utility of protected images for general synthesis purposes. Specifically, we propose GenWatermark, a novel watermark system based on jointly learning a watermark generator and a detector. In particular, to help the watermark survive the subject-driven synthesis, we incorporate the synthesis process in learning GenWatermark by fine-tuning the detector with synthesized images for a specific subject. This operation is shown to largely improve the watermark detection accuracy and also ensure the uniqueness of the watermark for each individual subject. Extensive experiments validate the effectiveness of GenWatermark, especially in practical scenarios with unknown models and text prompts (74% Acc.), as well as partial data watermarking (80% Acc. for 1/4 watermarking). We also demonstrate the robustness of GenWatermark to two potential countermeasures that substantially degrade the synthesis quality

Identifying potential therapeutic targets of a natural product Jujuboside B for insomnia through network pharmacology.

Knowledge of the interactome improves the understanding of disease metabolism. Biological information about interactions among genes and their protein products, computationally extracted in the context of SysBiomics, can hint at molecular causes of diseases, be essential for understanding biological systems, and provide clues for new therapeutic approaches. Quick and efficient access to this data have become critical issues for biologists. We have implemented a computational platform that integrates pathway, protein–protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for insomnia and intervention effects of Jujuboside B (JuB). The interaction data were imported into Cytoscape software, a popular bioinformatics package for biological network visualization and data integration, for screening the central nodes of the network, exploiting functional study of the central node genes, exploring the mechanism of insomnia. Results showed that seven differentially expressed genes confirmed by Cytoscape as the central nodes of the network in insomnia had interactions, forming a complicated interaction network (77 nodes, 96 edges). Among gene nodes, HBA1, LEP, MAOA, PRNP, GHRL, CLOCK and SLC6A4 were verified as the genes with maximal differential expressions. Of note, we further observed that the HBA1, LEP, SLC6A4 and MAOA were JuB target genes. The interaction network of the differentially expressed genes, especially the central nodes of this network, can provide clues to the insomnia, early diagnosis and molecular targeted therapy. Our findings demonstrate that the integration of interaction network in genomic space can not only speed the genome-wide identification of drug targets but also find new applications for the existing drugs