Current Chinese bryological literature (4)

According to our collections of literature, about 400 scientific papers dealing with Chinese bryophytes have been published in China and abroad during 1990’s. Among these, more than 50 % were published in different scientific journals in China and often written in Chinese with English abstract, which are not well known and assessable for foreign bryologists. Therefore, in addition to previous Chinese literature I-III (Cao et al. 1990, Li et Zhang 1993, 1994), we present the fourth part of Chinese literature herewith. It is hoped that this up-dated list will provide useful information for all people who are interested in bryological research

Replacing the Irreplaceable: Fast Algorithms for Team Member Recommendation

In this paper, we study the problem of Team Member Replacement: given a team of people embedded in a social network working on the same task, find a good candidate who can fit in the team after one team member becomes unavailable. We conjecture that a good team member replacement should have good skill matching as well as good structure matching. We formulate this problem using the concept of graph kernel. To tackle the computational challenges, we propose a family of fast algorithms by (a) designing effective pruning strategies, and (b) exploring the smoothness between the existing and the new team structures. We conduct extensive experimental evaluations on real world datasets to demonstrate the effectiveness and efficiency. Our algorithms (a) perform significantly better than the alternative choices in terms of both precision and recall; and (b) scale sub-linearly.Comment: Initially submitted to KDD 201

Responsible Active Learning via Human-in-the-loop Peer Study

Active learning has been proposed to reduce data annotation efforts by only manually labelling representative data samples for training. Meanwhile, recent active learning applications have benefited a lot from cloud computing services with not only sufficient computational resources but also crowdsourcing frameworks that include many humans in the active learning loop. However, previous active learning methods that always require passing large-scale unlabelled data to cloud may potentially raise significant data privacy issues. To mitigate such a risk, we propose a responsible active learning method, namely Peer Study Learning (PSL), to simultaneously preserve data privacy and improve model stability. Specifically, we first introduce a human-in-the-loop teacher-student architecture to isolate unlabelled data from the task learner (teacher) on the cloud-side by maintaining an active learner (student) on the client-side. During training, the task learner instructs the light-weight active learner which then provides feedback on the active sampling criterion. To further enhance the active learner via large-scale unlabelled data, we introduce multiple peer students into the active learner which is trained by a novel learning paradigm, including the In-Class Peer Study on labelled data and the Out-of-Class Peer Study on unlabelled data. Lastly, we devise a discrepancy-based active sampling criterion, Peer Study Feedback, that exploits the variability of peer students to select the most informative data to improve model stability. Extensive experiments demonstrate the superiority of the proposed PSL over a wide range of active learning methods in both standard and sensitive protection settings.Comment: 15 pages, 8 figure

Knowledge-Aware Federated Active Learning with Non-IID Data

Federated learning enables multiple decentralized clients to learn collaboratively without sharing the local training data. However, the expensive annotation cost to acquire data labels on local clients remains an obstacle in utilizing local data. In this paper, we propose a federated active learning paradigm to efficiently learn a global model with limited annotation budget while protecting data privacy in a decentralized learning way. The main challenge faced by federated active learning is the mismatch between the active sampling goal of the global model on the server and that of the asynchronous local clients. This becomes even more significant when data is distributed non-IID across local clients. To address the aforementioned challenge, we propose Knowledge-Aware Federated Active Learning (KAFAL), which consists of Knowledge-Specialized Active Sampling (KSAS) and Knowledge-Compensatory Federated Update (KCFU). KSAS is a novel active sampling method tailored for the federated active learning problem. It deals with the mismatch challenge by sampling actively based on the discrepancies between local and global models. KSAS intensifies specialized knowledge in local clients, ensuring the sampled data to be informative for both the local clients and the global model. KCFU, in the meantime, deals with the client heterogeneity caused by limited data and non-IID data distributions. It compensates for each client's ability in weak classes by the assistance of the global model. Extensive experiments and analyses are conducted to show the superiority of KSAS over the state-of-the-art active learning methods and the efficiency of KCFU under the federated active learning framework.Comment: 14 pages, 12 figure

1-(3-Chloro­benz­yloxy)urea

The asymmetric unit of the crystal structure of the title compound, C8H9ClN2O2, contains four independent mol­ecules. The dihedral angles between the urea N—(C=O)—N planes and the benzene rings are 83.3 (3), 87.8 (1), 89.1 (1) and 17.5 (2)° in the four mol­ecules. Extensive N—H⋯O hydrogen bonding is present in the crystal structure

Efficient derivation of dopaminergic neurons from SOX1(-) floor plate cells under defined culture conditions.

BACKGROUND: Parkinson's disease (PD) is a severe neurodegenerative disease associated with loss of dopaminergic neurons. Derivation of dopaminergic neurons from human embryonic stem cells (hESCs) could provide new therapeutic options for PD therapy. Dopaminergic neurons are derived from SOX(-) floor plate (FP) cells during embryonic development in many species and in human cell culture in vitro. Early treatment with sonic hedgehog (Shh) has been reported to efficiently convert hESCs into FP lineages. METHODS: In this study, we attempted to utilize a Shh-free approach in deriving SOX1(-) FP cells from hESCs in vitro. Neuroectoderm conversion from hESCs was achieved with dual inhibition of the BMP4 (LDN193189) and TGF-β signaling pathways (SB431542) for 24 h under defined culture conditions. RESULTS: Following a further 5 days of treatment with LDN193189 or LDN193189 + SB431542, SOX1(-) FP cells constituted 70-80 % of the entire cell population. Upon treatment with Shh and FGF8, the SOX1(-) FP cells were efficiently converted to functional Nurr1(+) and TH(+) dopaminergic cells (patterning), which constituted more than 98 % of the entire cell population. However, when the same growth factors were applied to SOX1(+) cells, only less than 4 % of the cells became Nurr1(+), indicating that patterning was effective only if SOX1 expression was down-regulated. After transplanting the Nurr1(+) and TH(+) cells into a hemiparkinsonian rat model, significant improvements were observed in amphetamine induced ipslateral rotations, apomorphine induced contra-lateral rotations and Rota rod motor tests over a duration of 8 weeks. CONCLUSIONS: Our findings thus provide a convenient approach to FP development and functional dopaminergic neuron derivation.published_or_final_versio

Electroconvulsive therapy for agitation in schizophrenia: Meta-analysis of randomized controlled trials

Background: Agitation poses a significant challenge in the treatment of schizophrenia. Electroconvulsive therapy (ECT) is a fast, effective and safe treatment for a variety of psychiatric disorders, but no meta-analysis of ECT treatment for agitation in schizophrenia has yet been reported. Aims: To systematically evaluate the efficacy and safety of ECT alone or ECT-antipsychotics (APs) combination for agitation in schizophrenia. Methods: Systematic literature search of randomized controlled trials (RCTs) was performed. Two independent evaluators selected studies, extracted data about outcomes and safety with available data, conducted quality assessment and data synthesis. The Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) was used to judge the level of the overall evidence of main outcomes. Results: Seven RCTs from China, including ECT alone (4 RCTs with 5 treatment arms, n=240) and ECT-APs combination (3 RCTs, n=240), were identified. Participants in the studies were on average 34.3(4.5) years of age and lasted an average of 4.3(3.1) weeks of treatment duration. All 7 RCTs were non-blinded, and were rated as low quality based on Jadad scale. Meta-analysis of the pooled sample found no significant difference in the improvement of the agitation sub-score of the Positive and Negative Syndrome Scale (PANSS) when ECT alone (weighted mean difference=-0.90, (95% confidence interval (CI): -2.91, 1.11), p=0.38) or ECT-APs combination (WMD=-1.34, (95%CI: -4.07, 1.39), p=0.33) compared with APs monotherapy. However, ECT alone was superior to APs monotherapy regarding PANSS total score (WMD=-7.13, I2=0%, p=0.004) and its excitement sub-score (WMD=-1.97, pI2=0%, p=0.004) and its excitement sub-score at 7 and 14 days (WMD=-1.97 to -1.92, p=0.002 to 0.0001) after ECT. The ECT-APs combination was superior to APs monotherapy with respect to the PANSS total score at treatment endpoint (WMD=-10.40, p=0.03) and 7 days (WMD=-5.01, p=0.02). Headache ( number-needed-to-harm (NNH)=3, 95%CI=2-4) was more frequent in the ECT alone group compared to AP monotherapy. According to the GRADE approach, the evidence levels of main outcomes were rated as ‘‘very low’’ (37.5%) and “low” (50%). Conclusion: Pooling of the data based on 7 RCTs from China found no advantage of ECT alone or ECT-APs combination in the treatment of agitation related outcomes in schizophrenia patients. However, ECT alone or ECT-APs combination were associated with significant reduction in the PANSS total score. High-quality RCTs are needed to confirm the current interpretations. Review registration number: CRD4201400668

Revisiting Network-Level Attacks on Blockchain Network

Many attacks presented on Bitcoin are facilitated by its real world implementation, which is rather centralized. In addition, communications between Bitcoin nodes are not encrypted, which can be explored by an attacker to launch attacks. In this paper, we give a brief overview of possible routing attacks on Bitcoin. As future work, we will identify possible central points in the Bitcoin network, evaluate potential attacks on it, and propose solutions to mitigate the identified issues