SL: Stable Learning in Source-Free Domain Adaption for Medical Image Segmentation

Deep learning techniques for medical image analysis usually suffer from the domain shift between source and target data. Most existing works focus on unsupervised domain adaptation (UDA). However, in practical applications, privacy issues are much more severe. For example, the data of different hospitals have domain shifts due to equipment problems, and data of the two domains cannot be available simultaneously because of privacy. In this challenge defined as Source-Free UDA, the previous UDA medical methods are limited. Although a variety of medical source-free unsupervised domain adaption (MSFUDA) methods have been proposed, we found they fall into an over-fitting dilemma called "longer training, worse performance." Therefore, we propose the Stable Learning (SL) strategy to address the dilemma. SL is a scalable method and can be integrated with other research, which consists of Weight Consolidation and Entropy Increase. First, we apply Weight Consolidation to retain domain-invariant knowledge and then we design Entropy Increase to avoid over-learning. Comparative experiments prove the effectiveness of SL. We also have done extensive ablation experiments. Besides, We will release codes including a variety of MSFUDA methods

Generalized Second Price Auction with Probabilistic Broad Match

Generalized Second Price (GSP) auctions are widely used by search engines today to sell their ad slots. Most search engines have supported broad match between queries and bid keywords when executing GSP auctions, however, it has been revealed that GSP auction with the standard broad-match mechanism they are currently using (denoted as SBM-GSP) has several theoretical drawbacks (e.g., its theoretical properties are known only for the single-slot case and full-information setting, and even in this simple setting, the corresponding worst-case social welfare can be rather bad). To address this issue, we propose a novel broad-match mechanism, which we call the Probabilistic Broad-Match (PBM) mechanism. Different from SBM that puts together the ads bidding on all the keywords matched to a given query for the GSP auction, the GSP with PBM (denoted as PBM-GSP) randomly samples a keyword according to a predefined probability distribution and only runs the GSP auction for the ads bidding on this sampled keyword. We perform a comprehensive study on the theoretical properties of the PBM-GSP. Specifically, we study its social welfare in the worst equilibrium, in both full-information and Bayesian settings. The results show that PBM-GSP can generate larger welfare than SBM-GSP under mild conditions. Furthermore, we also study the revenue guarantee for PBM-GSP in Bayesian setting. To the best of our knowledge, this is the first work on broad-match mechanisms for GSP that goes beyond the single-slot case and the full-information setting

Technology Features, Empowering Perceptions, and Voicing Behavior on Microblog

Recently, we have observed rapid growth of individual daily technologies such as microblogs, and the technology’s influence on people’s social life. To investigate such self-determined technology usage, we choose an empowerment perspective as our theoretical lens, because the empowerment concept highlights human beings’ proactive nature. We investigate a specific microblog usage, i.e. publicly voicing personal views on social affairs, which is an initial yet fundamental step in citizen participation. The study reveals that microblog features have transformed the way social news disseminate, and hence influence information quality and users’ social network building. These changes further influence users’ empowerment perceptions through raising users’ perceptions of internal political self-efficacy, autonomy, meaning, and impact. The more empowered users are, the more likely users will voice on microblog. We integrate context into our theorizing, and the empowerment framework allow us to uncover the psychological mechanism through which microblog technology features enable voicing, a specific technology usage

Online Community Citizenship Behaviors (OCCB) and Community Sustainability: An Examination of Benefit Creating Behaviors in Online Communities

Online communities now reach various aspects of people’s work and life; and both practitioners and researchers have recognized their importance. However, among the tens of thousands of online communities, a considerable portion of them gradually become lifeless, with little ongoing conversation and few active members. Since online communities largely rely on members’ participations to generate benefits, it is important to identify the behaviors that contribute to community sustainability. Specifically, the research questions are: 1) Besides knowledge contribution, what are the behaviors contributing to online community sustainability? 2) What is the nature of these behaviors? How do they benefit communities? Comparing online communities with organizations and referring to Organization Citizenship Behaviors (OCB), we conceptualize the benefiting creation behaviors as Online Community Citizenship Behaviors (OCCB), which have the following characteristics: 3) Discretionary 4) Beyond personal needs gratification 5) Promote the effective functioning of the online community We then identify the dimensions of OCCB, viewing online communities as complicated social entities which people go to with various needs to be fulfilled. Previous IS research mainly focuses on people’s information needs and examine knowledge sharing. Referring to social psychology studies on human needs and small group interaction analysis, we highlight that people also have social emotional needs, and argue for the importance of social emotional support on community sustainability. Behaviors offering social emotional support contribute to community relationship building, help to attract new members, and attract posts asking for social emotional support. We also examine behaviors related with community norm development and maintenance, such as recognizing other’s contribution, discouraging inappropriate behaviors. These behaviors cultivate community reciprocity norm and a friendly social atmosphere. They create strong bonding among members, retain members, and encourage members to contribute. We also note community participants may leverage other Internet platforms, such as personal blogs, to promote the community. Specifically, members’ recommendations on other platforms may generate publicity for the community and help the community to attract new users, hence we include cross platform community promotion in OCCB. Overall speaking, how to make online community sustainable is a question of both practical and theoretical interest. We address this question through investigating the benefit creating behaviors, i.e. OCCB. The study goes beyond knowledge contribution, and highlights behaviors related with social emotional needs gratifying, group norms forming, and group publicity. We propose that OCCB have positive influence on membership size, attracting posts seeking knowledge and social support, and hence make the community more influential and sustainable in the topical area; and we suggest ways to help community develop sustainably

Learning To Teach Large Language Models Logical Reasoning

Large language models (LLMs) have gained enormous attention from both academia and industry, due to their exceptional ability in language generation and extremely powerful generalization. However, current LLMs still output unreliable content in practical reasoning tasks due to their inherent issues (e.g., hallucination). To better disentangle this problem, in this paper, we conduct an in-depth investigation to systematically explore the capability of LLMs in logical reasoning. More in detail, we first investigate the deficiency of LLMs in logical reasoning on different tasks, including event relation extraction and deductive reasoning. Our study demonstrates that LLMs are not good reasoners in solving tasks with rigorous reasoning and will produce counterfactual answers, which require us to iteratively refine. Therefore, we comprehensively explore different strategies to endow LLMs with logical reasoning ability, and thus enable them to generate more logically consistent answers across different scenarios. Based on our approach, we also contribute a synthesized dataset (LLM-LR) involving multi-hop reasoning for evaluation and pre-training. Extensive quantitative and qualitative analyses on different tasks also validate the effectiveness and necessity of teaching LLMs with logic and provide insights for solving practical tasks with LLMs in future work

Automatic Service Composition Using AND/OR Graph

As SOC and Web service technology become more widely used, large amounts of services need to be efficiently and effectively composed to meet complex businesses. In this paper, we proposed an approach to resolve the composition problem over large-scale services. We used an inverted table as index for a quick service discovery, and applied a Service Dependency Graph (SDG) and an AND/OR graph as the algorithm basis for parallel compostion. Considering the semantic information described in Web service, our approach also recognizes and transmits the semantic relationships described i

Design of Spread-Spectrum Communication System Based on FPGA

Spread spectrum communication technology, compared with the conventional communication technology, has many characteristics, such as a low interception rate, strong anti-noise performance, noise immunity, information hiding and multiple access communication. Widely used in military communication and civil communication at present, it is the core technology in the third generation mobile communication standards and has become one of the three high-tech communication transmission modes to enter the information age. The communication system of direct sequence spread spectrum (DSSS) is most common in the spread spectrum communication technology, and this type of system was studied in this research. FPGA is one of hot research topics on hardware design. It has been widely used in the algorithm implementation and product prototype verification due to its rich logical unit, high integration, flexible configuration and many other advantages. Design and implementation on digital communication system with a more complex function have become reality on the hardware platform of FPGA with the considerable development of modern microelectronics especially in recent years. The research studied the various parts of key technologies, introduced the various algorithms of the most critical synchronization technologies (including pseudo-code acquisition, pseudo-code tracking, and carrier synchronization) in system in detail and gave their simulation results by establishing a complete simulation system for Direct Sequence Spread Spectrum

Polystyrene nanoplastics mediated the toxicity of silver nanoparticles in zebrafish embryos

The widespread distribution of nanoplastics and nanomaterials in aquatic environments is of great concern. Nanoplastics have been found to modulate the toxicity of other environmental pollutants in organisms, while few studies have focused on their influences on nanomaterials. Thus, this study evaluated the influences of polystyrene (PS) nanoplastics on the toxicity of silver nanoparticles (AgNPs) to zebrafish (Danio rerio) embryos, including acute toxicity, oxidative stress, apoptosis, immunotoxicity, and metabolic capability. The results showed that the presence of PS nanoplastics could act as a carrier of the co-existing AgNPs in waters. The release ratio of Ag+ from AgNPs was up to 4.23%. The lethal effects of AgNPs on zebrafish embryos were not significantly changed by the co-added PS nanoplastics. Whereas, the alterations in gene expression related to antioxidant and metabolic capability in zebrafish (sod1, cat, mt2, mtf-1, and cox1) caused by AgNPs were significantly enhanced by the presence of PS nanoplastics, which simultaneously lowered the apoptosis and immunotoxicity (caspase9, nfkβ, cebp, and il-1β) induced by AgNPs. It suggests the presence of PS nanoplastics suppressed the AgNPs-induced genotoxicity in zebrafish. The released Ag+ from AgNPs may be responsible for the toxicity of AgNPs in zebrafish, while the subsequent absorption and agglomeration of AgNPs and the released Ag+ on PS nanoplastics may alleviate the toxicity

In situ growth of ultrathin Co-MOF nanosheets on Α-Fe2O3 hematite nanorods for efficient photoelectrochemical water oxidation

Efficient charge transport is an important factor in photoelectrochemical (PEC) water splitting. The charge transfer at the semiconductor/electrolyte interface is of great importance, especially for the complex water oxidation reaction. In this study, we explored the feasibility of improving charge transfer efficiency at the interface of semiconductor/electrolyte by in situ growth of Co based Metal-Organic Frame work (Co-MOF) through a facile ion-exchanging method. Under optimized conditions, the Co-MOF nanosheet-modified hematite gave a photocurrent density of 2.0 mA cm−2 (200% improvement) at 1.23 VRHE with a cathodic shift of 180 mV in the photocurrent onset potential, in comparison to bare α-Fe2O3 (0.71 mA cm−[email protected] VRHE). To elucidate the role of Co-MOF, X-ray photoelectron spectroscopy, electrochemical impedance spectroscopy and Mott-Schottky measurements were carried out. It was found that the atomically distributed Co2+ in Co-MOF possessed excellent hole storage capability and charge transfer efficiency, as evidenced by the high surface capacitance and extremely low surface charge transfer resistance