VBF vs. GGF Higgs with Full-Event Deep Learning: Towards a Decay-Agnostic Tagger

We study the benefits of jet- and event-level deep learning methods in distinguishing vector boson fusion (VBF) from gluon-gluon fusion (GGF) Higgs production at the LHC. We show that a variety of classifiers (CNNs, attention-based networks) trained on the complete low-level inputs of the full event achieve significant performance gains over shallow machine learning methods (BDTs) trained on jet kinematics and jet shapes, and we elucidate the reasons for these performance gains. Finally, we take initial steps towards the possibility of a VBF vs. GGF tagger that is agnostic to the Higgs decay mode, by demonstrating that the performance of our event-level CNN does not change when the Higgs decay products are removed. These results highlight the potentially powerful benefits of event-level deep learning at the LHC.Comment: 21 pages+appendices, 16 figures; added references, updated Pythia shower scheme for VBF, and added Appendix C for version

Understanding Software-as-a-Service Performance - A Dynamic Capability Perspective

How to increase a client’s capability through outsourcing remains a problem. This papers draws on strategic management literature and the relational view to develop a theoretical model that explains the relationships between collaboration, agility, and outsourcing performance in software-as-a-service (SaaS) context. Collaboration are characterized as knowledge sharing and process alignment between a supplier and its client, agility as a supplier’s sensing agility and responding agility. This study also investigates the moderating effect of environmental turbulence on the relationships between agility and performance. The proposed hypotheses are largely supported by the empirical data from 215 firms. The results show that SaaS performance is affected by both sensing agility and responding ability, which, in turn, are impacted by collaboration between a supplier and its client. Finally, we discuss the implications of our results

BLIP-Adapter: Parameter-Efficient Transfer Learning for Mobile Screenshot Captioning

This study aims to explore efficient tuning methods for the screenshot captioning task. Recently, image captioning has seen significant advancements, but research in captioning tasks for mobile screens remains relatively scarce. Current datasets and use cases describing user behaviors within product screenshots are notably limited. Consequently, we sought to fine-tune pre-existing models for the screenshot captioning task. However, fine-tuning large pre-trained models can be resource-intensive, requiring considerable time, computational power, and storage due to the vast number of parameters in image captioning models. To tackle this challenge, this study proposes a combination of adapter methods, which necessitates tuning only the additional modules on the model. These methods are originally designed for vision or language tasks, and our intention is to apply them to address similar challenges in screenshot captioning. By freezing the parameters of the image caption models and training only the weights associated with the methods, performance comparable to fine-tuning the entire model can be achieved, while significantly reducing the number of parameters. This study represents the first comprehensive investigation into the effectiveness of combining adapters within the context of the screenshot captioning task. Through our experiments and analyses, this study aims to provide valuable insights into the application of adapters in vision-language models and contribute to the development of efficient tuning techniques for the screenshot captioning task. Our study is available at https://github.com/RainYuGG/BLIP-Adapte

Understanding Outsourcing Commitment—An Integrated Model Combining The Resoruce-Based View And Knowledge Management

The understanding on how a service provider’s (SP) process capabilities, in terms of aligning and adapting resources to deliver value to its service recipient (SR) in business process outsourcing (BPO), affect its commitment is limited. To address this, building on a strategic perspective and related theories such as the resource-based view and knowledge management, we develop a theoretical model and test it empirically. Specifically, we posit that a SP’s process capabilities, in terms of process alignment, offering flexibility, and partnering flexibility, positively affect its SR’s commitment and the above relationships is negatively moderated by the SR’s behavior control. Besides, we also examine the influence of interaction effect between antecedents of process capabilities on commitment, such as how does process alignment interact with its partnering flexibility and offering flexibility to affect commitment. Finally, we assess whether process capabilities are influenced by the SR’s absorptive capacity and the SP’s task-knowledge coordination. We test our model using survey data collected from 183 firms, supporting most proposed hypotheses. We discuss the theoretical and practical implications of how to increase the value offered to a SR by levering resources, in terms of process capabilities and knowledge management

Modeling the Combined Effects of River Stage and Groundwater Flow on Riverbank Stability Before and After Dam Removal

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive

Celecoxib extends C. elegans lifespan via inhibition of insulin‐like signaling but not cyclooxygenase‐2 activity

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/86911/1/ACEL_688_sm_FigS1-S2-TableS1-S2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/86911/2/j.1474-9726.2011.00688.x.pd

UNDERSTANDING COMPETITIVE PERFORMANCE OF SOFTWARE-AS-A-SERVICE (SAAS)—THE COMPETITIVE DYNAMICS PERSPECTIVE

Understanding the antecedents and consequences of a firm’s agility in cloud software applications is important. This papers draws on the competitive dynamics perspective to develop a model that explains the relationships between collaboration with vendors, agility, and competitive performance in software-as-a-service (SaaS) context. Collaboration reflects a firm’s ability to leverage interfirm resources, characterized as knowledge sharing and process alignment. Agility is measured by a firm’s strategy-oriented agility and service-oriented agility. This study also investigates the moderating effect of environmental turbulence. The proposed hypotheses are supported by the empirical data. The results show that competitive performance is affected by ability, which, in turn, is impacted by collaboration. Environmental turbulence positively moderates the relationship between agility and performance. Finally, we discuss the implications of our results

Inhibitory Effects of Terminalia catappa on UVB-Induced Photodamage in Fibroblast Cell Line

This study investigated whether Terminalia catappa L. hydrophilic extract (TCLW) prevents photoaging in human dermal fibroblasts after exposure to UVB radiation. TCLW exhibited DPPH free radical scavenging activity and protected erythrocytes against AAPH-induced hemolysis. In the gelatin digestion assay, the rates of collagenase inhibition by TCL methanol extract, TCLW, and its hydrolysates were greater than 100% at the concentration of 1 mg/mL. We found that serial dilutions of TCLW (10–500 μg/mL) inhibited collagenase activity in a dose-dependent manner (82.3% to 101.0%). However, TCLW did not significantly inhibit elastase activity. In addition, TCLW inhibited MMP-1 and MMP-9 protein expression at a concentration of 25 μg/mL and inhibited MMP-3 protein expression at a concentration of 50 μg/mL. TCLW also promoted the protein expression of type I procollagen. We also found that TCLW attenuated the expression of MMP-1, -3, and -9 by inhibiting the phosphorylation of ERK, JNK, and p38. These findings suggest that TCLW increases the production of type I procollagen by inhibiting the activity of MMP-1, -3 and -9, and, therefore, has potential use in anti-aging cosmetics