Quantification of De-anonymization Risks in Social Networks

The risks of publishing privacy-sensitive data have received considerable attention recently. Several de-anonymization attacks have been proposed to re-identify individuals even if data anonymization techniques were applied. However, there is no theoretical quantification for relating the data utility that is preserved by the anonymization techniques and the data vulnerability against de-anonymization attacks. In this paper, we theoretically analyze the de-anonymization attacks and provide conditions on the utility of the anonymized data (denoted by anonymized utility) to achieve successful de-anonymization. To the best of our knowledge, this is the first work on quantifying the relationships between anonymized utility and de-anonymization capability. Unlike previous work, our quantification analysis requires no assumptions about the graph model, thus providing a general theoretical guide for developing practical de-anonymization/anonymization techniques. Furthermore, we evaluate state-of-the-art de-anonymization attacks on a real-world Facebook dataset to show the limitations of previous work. By comparing these experimental results and the theoretically achievable de-anonymization capability derived in our analysis, we further demonstrate the ineffectiveness of previous de-anonymization attacks and the potential of more powerful de-anonymization attacks in the future.Comment: Published in International Conference on Information Systems Security and Privacy, 201

An urbanism theory for Chengdu: criteria towards advancing an alternative urban development model for central Chinese cities

This project advances an alternative urban development model for central Chinese cities. Urbanization of Chinese cities occurred within a relatively short time compared to western cities. The related urban theories, as a consequence, are less developed. Most Chinese cities apply western urban theories directly to an eastern setting, which causes underused and unsuccessful urban space. Currently, both Chinese citizens and theorists are looking for an urban development model that can perfectly fit in the specific context. In this thesis, the Kuanzhai district is the main study model. Kuanzhai, a historical commercial district in Chengdu, holds great popularity and contributes to the conservation of the local culture. Chengdu is the largest and oldest city in central China. Other central Chinese cities look to Chengdu as a model of a good balance between modernization and cultural heritage in its built environment. In order to establish a unique urban theory for central Chinese cities, this thesis presents a study of western urban theories since 1960, conducts an intensive analysis of Chengdu's Kuanzhai district, and makes a comparison of these theories to the Kuanzhai district. The analysis of Kuanzhai focuses on five components of urban space; these are identified as people, time, programs, space/scale and materiality. The outcome reveals the discrepancies between western urban design theories and the situation of Chengdu, and establishes unique criteria for the development of central Chinese cities. To test the generality, rationality and applicability of the criteria, two other places in the city of Chengdu--Wenshu and Kejia, are also examined. The goal of this thesis is to use those criteria to advance a development model specific to central Chinese cities that underscores a unique cultural and physical composition within the built environment

Evaluating the Information Usefulness of Online Health Information for Third-party Patients

Online health interactions (OHIs) can benefit patients, physicians, and society. However, little research has been conducted that studies the social value of OHIs for third-party patients who view previous OHIs concerning similar health issues to theirs. Drawing on the literature on social support and information uncertainty, this study established a theoretical model to explore the roles of treatment information, prevention information, and emotional support in determining information usefulness perceived by third-party patients, and whether such relationships are contingent on information uncertainty. The model was tested using “health questions and answers” textual data from 1,848 OHIs. The results indicate that prevention information and emotional support significantly improve information usefulness perceived by third-party patients. When the level of information uncertainty regarding physicians’ replies is high, the effect of treatment information is strengthened and the effect of emotional support is weakened, indicating both positive and negative contingent roles of information uncertainty. This study has implications for practitioners and also contributes to the literature on online health information, social support, information science, and information uncertainty

Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms

This paper studies a new task of federated learning (FL) for semantic parsing, where multiple clients collaboratively train one global model without sharing their semantic parsing data. By leveraging data from multiple clients, the FL paradigm can be especially beneficial for clients that have little training data to develop a data-hungry neural semantic parser on their own. We propose an evaluation setup to study this task, where we re-purpose widely-used single-domain text-to-SQL datasets as clients to form a realistic heterogeneous FL setting and collaboratively train a global model. As standard FL algorithms suffer from the high client heterogeneity in our realistic setup, we further propose a novel LOss Reduction Adjusted Re-weighting (Lorar) mechanism to mitigate the performance degradation, which adjusts each client's contribution to the global model update based on its training loss reduction during each round. Our intuition is that the larger the loss reduction, the further away the current global model is from the client's local optimum, and the larger weight the client should get. By applying Lorar to three widely adopted FL algorithms (FedAvg, FedOPT and FedProx), we observe that their performance can be improved substantially on average (4%-20% absolute gain under MacroAvg) and that clients with smaller datasets enjoy larger performance gains. In addition, the global model converges faster for almost all the clients.Comment: ACL 2023 long pape

Kwas zoledronowy stosowany przez dwa lata u Chinek z osteoporozą pomenopauzalną zwiększa gęstość mineralną tkanki kostnej i poprawia jakość życia związaną ze stanem zdrowia

Introduction: Osteoporosis is characterised by decreased bone mass and weakened bones, with an increased risk of fractures. Osteoporotic fracture, the most serious complication of osteoporosis, is related not only to lower bone mineral density (BMD), but also falls. Osteoporosis and fractures are associated with a decreased health-related quality of life (HRQL). Zoledronic acid (ZOL) is an intravenous once-yearly bisphosphonate that has been shown to be effective and safe in improving BMD and reducing fracture risk in controlled clinical trials.Material and methods: In this self-controlled, prospective trial, 220 postmenopausal women with osteoporosis (mean age 67 years) received a single infusion of ZOL 5 mg at baseline and month 12. BMD, HRQL and Fall Index (FI) were measured at baseline, and months 12 and 24 (before each use of ZOL). The main outcome measures were the changes in lumbar spine and hip BMD and the changes in HRQL, the Short Form-36 questionnaire (SF-36). Additional comparisons were based on the FI. LSD multiple comparisons were used in the comparisons of BMD, SF-36 domain scores and FI.Results: The patients had significantly higher L1-4, total hip, femoral neck and trochanter BMD (P < 0.05) with improved HRQL (P < 0.05) over two years of treatment of once-yearly ZOL 5mg. FI was reduced (P < 0.05) with oral daily elemental calcium and vitamin D in the treatment course.Conclusions: ZOL improves BMD and HRQL, especially in the physical aspects, over two years of treatment in women with postmenopausal osteoporosis, and can help improve balance ability. (Endokrynol Pol 2014; 65 (2): 96–104)Wstęp: Osteoporoza to schorzenie cechujące się obniżeniem masy kostnej i wytrzymałości mechanicznej kości z towarzyszącym zwiększeniem ryzyka złamań. Złamania osteoporotyczne, będące najpoważniejszym powikłaniem osteoporozy, wiążą się nie tylko z obniżoną gęstością mineralną tkanki kostnej (BMD, bone mineral density) ale też z upadkami. Z osteoporozą i złamaniami wiąże się obniżenie jakości życia związanej ze stanem zdrowia (HRQoL, health-related quality of life). Kwas zoledronowy (ZOL) to bisfosfonian w postaci dożylnej przeznaczony do podawania raz w roku, w przypadku którego w badaniach klinicznych z grupą kontrolną wykazano skuteczność i bezpieczeństwo w zwiększaniu BMD i zmniejszaniu ryzyka złamań.Materiał i metody: Autorzy przeprowadzili samodzielnie kontrolowane, prospektywne badanie z udziałem 220 znajdujących się w wieku pomenopauzalnym kobiet z osteoporozą (średnia wieku 67 lat), które otrzymały jednorazowo roztwór ZOL w dawce 5 mg na początku badania i 12 miesięcy później. Na początku badania, w 12. miesiącu i w 24. miesiącu badania (za każdym razem przed podaniem ZOL) oznaczano BMD, HRQoL i wskaźnik upadków (FI, fall index). Główne punkty końcowe obejmowały zmiany BMD w odcinku lędźwiowym kręgosłupa i BMD w okolicy biodra, a także zmiany HRQoL w kwestionariuszu SF-36. Dodatkowe porównania będą oparte na FI. W porównaniach wartości BMD, liczby punktów w poszczególnych domenach kwestionariusza SF-36 i wartości FI zastosowano metodę wielokrotnych porównań najmniejszej istotnej różnicy.Wyniki: U pacjentek stwierdzono znamiennie większe wartości BMD na poziomie L1–4, BMD w całkowitym obszarze biodra, BMD w obrębie szyjki kości udowej oraz BMD w obrębie krętarza (p < 0,05) oraz znamienną poprawę HRQoL (p < 0,05) w okresie 2 lat leczenia podawanym raz w roku ZOL w dawce 5 mg. Stwierdzono też zmniejszenie FI (p < 0,05) dzięki codziennemu przyjmowaniu wapnia i witaminy D w okresie leczenia.Wnioski: Stosowanie ZOL prowadzi do poprawy BMD i HRQoL, zwłaszcza w aspekcie fizycznym, w okresie 2 lat stosowania u kobiet z osteoporozą pomenopauzalną, i może przyczyniać się do poprawy zdolności utrzymania równowagi. (Endokrynol Pol 2014; 65 (2): 96–104

Contrastive Attention for Automatic Chest X-ray Report Generation

Recently, chest X-ray report generation, which aims to automatically generate descriptions of given chest X-ray images, has received growing research interests. The key challenge of chest X-ray report generation is to accurately capture and describe the abnormal regions. In most cases, the normal regions dominate the entire chest X-ray image, and the corresponding descriptions of these normal regions dominate the final report. Due to such data bias, learning-based models may fail to attend to abnormal regions. In this work, to effectively capture and describe abnormal regions, we propose the Contrastive Attention (CA) model. Instead of solely focusing on the current input image, the CA model compares the current input image with normal images to distill the contrastive information. The acquired contrastive information can better represent the visual features of abnormal regions. According to the experiments on the public IU-X-ray and MIMIC-CXR datasets, incorporating our CA into several existing models can boost their performance across most metrics. In addition, according to the analysis, the CA model can help existing models better attend to the abnormal regions and provide more accurate descriptions which are crucial for an interpretable diagnosis. Specifically, we achieve the state-of-the-art results on the two public datasets.Comment: Appear in Findings of ACL 2021 (The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021)