On Dynamic Resource Allocation for Blockchain Assisted Federated Learning over Wireless Channels

Blockchain assisted federated learning (BFL) has been intensively studied as a promising technology to process data at the network edge in a distributed manner. In this paper, we focus on BFL over wireless environments with varying channels and energy harvesting at clients. We are interested in proposing dynamic resource allocation (i.e., transmit power, computation frequency for model training and block mining for each client) and client scheduling (DRACS) to maximize the long-term time average (LTA) training data size with an LTA energy consumption constraint. Specifically, we first define the Lyapunov drift by converting the LTA energy consumption to a queue stability constraint. Then, we construct a Lyapunov drift-plus-penalty ratio function to decouple the original stochastic problem into multiple deterministic optimizations along the time line. Our construction is capable of dealing with uneven durations of communication rounds. To make the one-shot deterministic optimization problem of combinatorial fractional form tractable, we next convert the fractional problem into a subtractive-form one by Dinkelbach method, which leads to the asymptotically optimal solution in an iterative way. In addition, the closed-form of the optimal resource allocation and client scheduling is obtained in each iteration with a low complexity. Furthermore, we conduct the performance analysis for the proposed algorithm, and discover that the LTA training data size and energy consumption obey an [$\mathcal{O}(1/V)$, $\mathcal{O}(\sqrt{V})$] trade-off. Our experimental results show that the proposed algorithm can provide both higher learning accuracy and faster convergence with limited time and energy consumption based on the MNIST and Fashion-MNIST datasets

Federated Learning with Differential Privacy: Algorithms and Performance Analysis

In this paper, to effectively prevent information leakage, we propose a novel framework based on the concept of differential privacy (DP), in which artificial noises are added to the parameters at the clients side before aggregating, namely, noising before model aggregation FL (NbAFL). First, we prove that the NbAFL can satisfy DP under distinct protection levels by properly adapting different variances of artificial noises. Then we develop a theoretical convergence bound of the loss function of the trained FL model in the NbAFL. Specifically, the theoretical bound reveals the following three key properties: 1) There is a tradeoff between the convergence performance and privacy protection levels, i.e., a better convergence performance leads to a lower protection level; 2) Given a fixed privacy protection level, increasing the number $N$ of overall clients participating in FL can improve the convergence performance; 3) There is an optimal number of maximum aggregation times (communication rounds) in terms of convergence performance for a given protection level. Furthermore, we propose a $K$-random scheduling strategy, where $K$ ($1<K<N$) clients are randomly selected from the $N$ overall clients to participate in each aggregation. We also develop the corresponding convergence bound of the loss function in this case and the $K$-random scheduling strategy can also retain the above three properties. Moreover, we find that there is an optimal $K$ that achieves the best convergence performance at a fixed privacy level. Evaluations demonstrate that our theoretical results are consistent with simulations, thereby facilitating the designs on various privacy-preserving FL algorithms with different tradeoff requirements on convergence performance and privacy levels

Prescribing patterns of low doses of antipsychotic medications in older Asian patients with schizophrenia, 2001-2009

Background: This study examined the use of low doses of antipsychotic medications (300mg/day CPZeq or less) in older Asian patients with schizophrenia and its demographic and clinical correlates. Methods: Information on hospitalized patients with schizophrenia, aged 55 years or older, was extracted from the database of the Research on Asian Psychotropic Prescription Patterns (REAP) study (2001-2009). Data on 1,452 patients in eight Asian countries and territories including China, Hong Kong, Japan, Korea, Singapore, Taiwan, India, and Malaysia were analyzed. Sociodemographic and clinical characteristics and antipsychotic prescriptions were recorded using a standardized protocol and data collection procedure. Results: The prescription frequency for low doses of antipsychotic medications was 40.9% in the pooled sample. Multiple logistic regression analysis of the whole sample showed that patients on low doses of antipsychotic medications were more likely to be female, have an older age, a shorter length of illness, and less positive symptoms. Of patients in the six countries and territories that participated in all the surveys between 2001 and 2009, those in Japan were less likely to receive low doses of antipsychotics. Conclusion: Low doses of antipsychotic medications were only applied in less than half of older Asian patients with schizophreni

Cross-National Differences in Victimization : Disentangling the Impact of Composition and Context

Varying rates of criminal victimization across countries are assumed to be the outcome of countrylevel structural constraints that determine the supply ofmotivated o¡enders, as well as the differential composition within countries of suitable targets and capable guardianship. However, previous empirical tests of these ‘compositional’ and ‘contextual’ explanations of cross-national di¡erences have been performed upon macro-level crime data due to the unavailability of comparable individual-level data across countries. This limitation has had two important consequences for cross-national crime research. First, micro-/meso-level mechanisms underlying cross-national differences cannot be truly inferred from macro-level data. Secondly, the e¡ects of contextual measures (e.g. income inequality) on crime are uncontrolled for compositional heterogeneity. In this paper, these limitations are overcome by analysing individual-level victimization data across 18 countries from the International CrimeVictims Survey. Results from multi-level analyses on theft and violent victimization indicate that the national level of income inequality is positively related to risk, independent of compositional (i.e. micro- and meso-level) di¡erences. Furthermore, crossnational variation in victimization rates is not only shaped by di¡erences in national context, but also by varying composition. More speci¢cally, countries had higher crime rates the more they consisted of urban residents and regions with lowaverage social cohesion.

Probiotic Lactobacillus paracasei effect on cariogenic bacterial flora

Lactobacillus paracasei has been demonstrated to inhibit the growth of many pathogenic microbes such as Streptococcus mutans, in vitro. However, its clinical application remains unclear. Here, we examined whether a novel probiotic L. paracasei GMNL-33 may reduce the caries-associated salivary microbial counts in healthy adults. Seventy-eight subjects (aged 20 to 26) had completed this double-blinded, randomized, placebo-controlled study. A probiotic/test (n = 42) and a control group (n = 36) took a L. paracasei GMNL-33 and a placebo oral tablet three times per day for 2 weeks, respectively. Bacterial counts of salivary S. mutans, lactobacilli, and salivary buffer capacity were measured with chair-side kits at the beginning (T1), the completion (T2) of medication, and 2 weeks after medication (T3). The results did not show differences in the counts of S. mutans and lactobacilli between probiotic and control groups at T1, T2, and T3. Nevertheless, within the probiotic group, an interesting probiotic effect was noticed. Between T1 and T2, no inhibitory effect against S. mutans was observed. However, a significant count reduction in the salivary S. mutans was detected between T2 and T3 (p = 0.016). Thus, a 2-week period of medication via oral administration route may be needed for L. paracasei GMNL-33 to be effective in the probiotic action