Miracle-dz/UniFAR-FTUs huggingface dataset:
Secure and Efficient Federated Learning Through Layering and Sharding Blockchain

Introducing blockchain into Federated Learning (FL) to build a trusted edge computing environment for transmission and learning has attracted widespread attention as a new decentralized learning pattern. However, traditional consensus mechanisms and architectures of blockchain systems face significant challenges in handling large-scale FL tasks, especially on Internet of Things (IoT) devices, due to their substantial resource consumption, limited transaction throughput, and complex communication requirements. To address these challenges, this paper proposes ChainFL, a novel two-layer blockchain-driven FL system. It splits the IoT network into multiple shards within the subchain layer, effectively reducing the scale of information exchange, and employs a Direct Acyclic Graph (DAG)-based mainchain as the mainchain layer, enabling parallel and asynchronous cross-shard validation. Furthermore, the FL procedure is customized to integrate deeply with blockchain technology, and a modified DAG consensus mechanism is designed to mitigate distortion caused by abnormal models. To provide a proof-of-concept implementation and evaluation, multiple subchains based on Hyperledger Fabric and a self-developed DAG-based mainchain are deployed. Extensive experiments demonstrate that ChainFL significantly surpasses conventional FL systems, showing up to a 14% improvement in training efficiency and a threefold increase in robustness.
Influence Based Defense Against Data Poisoning Attacks in Online Learning

Data poisoning is a type of adversarial attack on training data where an attacker manipulates a fraction of data to degrade the performance of machine learning model. There are several known defensive mechanisms for handling offline attacks, however defensive measures for online learning, where data points arrive sequentially, have not garnered similar interest. In this work, we propose a defense mechanism to minimize the degradation caused by the poisoned training data on a learner's model in an online setup. Our proposed method utilizes an influence function which is a classic technique in robust statistics. Further, we supplement it with the existing data sanitization methods for filtering out some of the poisoned data points. We study the effectiveness of our defense mechanism on multiple datasets and across multiple attack strategies against an online learner.
Semi-Supervised Superpixel-Based Multi-Feature Graph Learning for Hyperspectral Image Data

Graphs naturally lend themselves to model the complexities of hyperspectral image (HSI) data as well as to serve as semi-supervised classifiers by propagating given labels among nearest neighbors. In this work, we present a novel framework for the classification of HSI data in light of a very limited amount of labeled data, inspired by multi-view graph learning and graph signal processing. Given an a priori superpixel-segmented HSI, we seek a robust and efficient graph construction and label propagation method to conduct semi-supervised learning (SSL). Since the graph is paramount to the success of the subsequent classification task, particularly in light of the intrinsic complexity of HSI data, we consider the problem of finding the optimal graph to model such data. Our contribution is two-fold. First, we propose a multi-stage edge-efficient semi-supervised graph learning framework for HSI data, which exploits given label information through pseudo-label features embedded in the graph construction. Second, we examine and enhance the contribution of multiple superpixel features embedded in the graph on the basis of pseudo-label features in an extension of the previous framework, which is less reliant on excessive parameter tuning. Ultimately, we demonstrate the superiority of our approaches in comparison with state-of-the-art methods through extensive numerical experiments.
Ranking of average treatment effects with generalized random forests for time‐to‐event outcomes

Linkage between drug claims data and clinical outcome allows a data‐driven experimental approach to drug repurposing. We develop an estimation procedure based on generalized random forests for estimation of time‐point specific average treatment effects in a time‐to‐event setting with competing risks. To handle right‐censoring, we propose a two‐step procedure for estimation, applying inverse probability weighting to construct time‐point specific weighted outcomes as input for the generalized random forest. The generalized random forests adaptively handle covariate effects on the treatment assignment by applying a splitting rule that targets a causal parameter. Using simulated data we demonstrate that the method is effective for a causal search through a list of treatments to be ranked according to the magnitude of their effect on clinical outcome. We illustrate the method using the Danish national health registries where it is of interest to discover drugs with an unexpected protective effect against relapse of severe depression.
Handling Long-Tail Queries with Slice-Aware Conversational Systems

We have been witnessing the usefulness of conversational AI systems such as Siri and Alexa, directly impacting our daily lives. These systems normally rely on machine learning models evolving over time to provide quality user experience. However, the development and improvement of the models are challenging because they need to support both high (head) and low (tail) usage scenarios, requiring fine-grained modeling strategies for specific data subsets or slices. In this paper, we explore the recent concept of slice-based learning (SBL) (Chen et al., 2019) to improve our baseline conversational skill routing system on the tail yet critical query traffic. We first define a set of labeling functions to generate weak supervision data for the tail intents. We then extend the baseline model towards a slice-aware architecture, which monitors and improves the model performance on the selected tail intents. Applied to de-identified live traffic from a commercial conversational AI system, our experiments show that the slice-aware model is beneficial in improving model performance for the tail intents while maintaining the overall performance.
Via Machinae: Searching for Stellar Streams using Unsupervised Machine Learning

We develop a new machine learning algorithm, Via Machinae, to identify cold stellar streams in data from the Gaia telescope. Via Machinae is based on ANODE, a general method that uses conditional density estimation and sideband interpolation to detect local overdensities in the data in a model agnostic way. By applying ANODE to the positions, proper motions, and photometry of stars observed by Gaia, Via Machinae obtains a collection of those stars deemed most likely to belong to a stellar stream. We further apply an automated line-finding method based on the Hough transform to search for line-like features in patches of the sky. In this paper, we describe the Via Machinae algorithm in detail and demonstrate our approach on the prominent stream GD-1. Though some parts of the algorithm are tuned to increase sensitivity to cold streams, the Via Machinae technique itself does not rely on astrophysical assumptions, such as the potential of the Milky Way or stellar isochrones. This flexibility suggests that it may have further applications in identifying other anomalous structures within the Gaia dataset, for example debris flow and globular clusters.
RoboStack Using the Robot Operating System alongside the Conda and Jupyter Data Science Ecosystems

In a parallel development, a large suite of scientific libraries in the machine learning, deep learning, and data science domains has emerged: NumPy, SciPy, Pandas, OpenCV, the Natural Language Toolkit, PyTorch, and TensorFlow to name a few. These libraries have wide ranging applications including computer vision, computer graphics and natural language processing – all of which are also highly relevant in robotics.
Evidence for Ultra-diffuse Galaxy Formation through Tidal Heating of Normal Dwarfs

We have followed up two ultra-diffuse galaxies (UDGs), detected adjacent to stellar streams, with Hubble Space Telescope (HST) imaging and H i mapping with the Jansky Very Large Array in order to investigate the possibility that they might have a tidal origin. With the HST F814W and F555W images we measure the globular cluster (GC) counts for NGC 2708-Dw1 and NGC 5631-Dw1 as 2−1+1 and 5−2+1 , respectively. NGC 2708-Dw1 is undetected in H i down to a 3σ limit of log (M H i /M ⊙) = 7.3, and there is no apparent H i associated with the nearby stellar stream. There is a 2σ H i feature coincident with NGC 5631-Dw1. However, this emission is blended with a large gaseous tail emanating from NGC 5631 and is not necessarily associated with the UDG. The presence of any GCs and the lack of clear H i connections between the UDGs and their parent galaxies strongly disfavor a tidal dwarf galaxy origin, but cannot entirely rule it out. The GC counts are consistent with those of normal dwarf galaxies, and the most probable formation mechanism is one where these UDGs were born as normal dwarfs and were later tidally stripped and heated. We also identify an overluminous (M V = −11.1) GC candidate in NGC 2708-Dw1, which may be a nuclear star cluster transitioning to an ultra-compact dwarf as the surrounding dwarf galaxy gets stripped of stars.
Optimal Acupuncture Methods for Nonspecific Low Back Pain: A Systematic Review and Bayesian Network Meta-Analysis of Randomized Controlled Trials

Background Nonspecific low back pain (NLBP) is a common disabling disease that cannot be attributed to a specific, recognizable pathology. The use of acupuncture for NLBP is supported by several guidelines and systematic reviews. However, the efficacy of different acupuncture methods for NLBP management is still debated. This study ranked the effectiveness of acupuncture methods using network meta-analysis to screen out the optimal acupuncture methods and expound the current controversies for their effective application in health policies as well as guiding clinical operations. Methods The following databases were searched for relevant randomized controlled trials (RCTs) from inception to December 20, 2020: China National Knowledge Infrastructure, VIP Database for Chinese Technical Periodicals, WANFANG Database, Chinese biomedical literature service system, PubMed, Web of Science, Embase, and Cochrane Library. Relevant registration platforms, including the International Standard Randomised Controlled Trial Number Register (ISRCTN) and Chinese Clinical Trial Registry (ChiCTR), were also searched. Manual retrieval and tracking of references was also performed. Pairwise meta-analysis and Bayesian network meta-analysis using Revman and ADDIS, respectively, were performed and standardized mean differences examined. The primary outcome was visual analog scale (VAS) score and the secondary outcome was Oswestry Disability Index (ODI) score. Safety was defined as the incidence of adverse events. Results A total of 30 trials with 3196 participants were analyzed; 16.67% of which showed a high risk of bias. The results indicated that fire acupuncture plus manual acupuncture, auricular needling, and electroacupuncture plus warm acupuncture were most effective in reducing VAS score. The most effective interventions for reducing ODI score were manual acupuncture plus conventional medicines, followed by moxibustion and manual acupuncture plus moxibustion. Manual acupuncture plus moxibustion was dominant in the cluster ranking. Acupuncture showed a lower incidence of adverse events (7.70%) than other interventions (conventional medicines, routine care, and placebo; 12.24%). Conclusion We found that manual acupuncture plus moxibustion is the most effective way to reduce NLBP pain and disability. Acupuncture is safer than other interventions. However, more direct comparative evidence from high-quality, large-sample, multicenter RCTs is needed to validate these findings.
Technical Aspects of Intensive Care Unit Management: A Single-Center Experience at a Tertiary Academic Hospital

Purpose Special technical issues associated with the function and maintenance of medical devices arise in intensive care units (ICUs). This study explored the level of comfort of ICU staff in dealing with selected equipment, the factors that are associated with the staff’s ease of adaptation to new technologies, and the role of technical support staff. Patients and Methods This is a single-center cross-sectional questionnaire-based survey that was conducted in February 2018 and targeted nurses working in the ICUs of King Saud University Medical City in Riyadh, Saudi Arabia. Results Among the 297 nurses who completed the survey, almost all of the respondents (99.3%) were aware of the ICU equipment preventive maintenance program. Most of the nurses had received training on how to use infusion pumps (96.2%), cardiac monitoring systems (78.0%), and cardiac defibrillation devices (73.9%). Sixty nurses (20.2%) indicated that at least one super user was available for at least one device. About half of the staff reported one device whose user manual was available. Most nurses reported having no resources regarding updates on medical devices. Conclusion Our findings revealed an alarming need to address technical issues related to medical devices used in the ICU and to design a framework for the safe operation of medical devices based on international practices. It is necessary to empower the role of the super user and medical device clinical educator as well as to optimize communication between the national regulatory body of medical devices and healthcare providers, especially those working in acute care areas.
Physical Activity of Type 2 Diabetes Mellitus Patients and Non-Diabetes Participants in Yangon, Myanmar: A Case-Control Study Applying the International Physical Activity Questionnaires (IPAQ-S)

Background Despite the evidence that physical activity (PA) can prevent type 2 diabetes mellitus (T2DM), limited research investigated the level of PA among diabetes and non-diabetes in Myanmar, where there is the escalating prevalence of diabetes recently. We investigated PA as modified the risk of diabetes, in a case-control study. Methods We conducted a case-control study which included 150 cases and 150 controls age 25–74 years (Mean age 43.3±14.7 years) among the cases and (55.1±10.9 years) among the controls, both sex and residence in Yangon. Cases were newly diagnosed with T2DM within six months before data collection, with laboratory-confirmed fasting blood glucose level ≥126mg/dl. Controls were community residents, without diabetes, confirmed with a laboratory test. The IPAQ-S was used to assess the PA level. Multiple logistic regression analysis was applied in STATA 15, using the interaction terms for age and PA, adjusting age, sex and BMI. Results In comparison to controls, cases were older and having less PA knowledge. The levels of vigorous PA were mean 254.9±standard deviations (SD) 845.6 METsmin.wk−1 among controls, 73.06±392.1 cases, moderate PA 631.5±1240.8 METsmin.wk−1 among controls and 1050.9±1601.6 cases and walking PA 569.8±1060 METsmin.wk−1 among controls and 777.4±1249 cases, respectively. The multiple logistic regression analysis showed adjusted odds ratios (aOR) 3.84, 95% confidence interval (CI) 1.18–12.42 (P<0.05) for those aged 40 and older, with moderate PA and aOR 18.01, Cl 6.45–50.26 (P<0.001) for those aged 40 and older, with low PA. Comparing the strength of association, the risk of T2DM among people aged 40 and older with moderate PA is lower than age over 40 with low PA. Conclusion PA lessened the risk of T2DM, posted by increasing age. The findings highlighted the importance of promoting PA to reduce the T2DM prevalence in the context of Yangon, Myanmar, a low- and middle-income Asian country.
HMGB1/TLR4 Signaling Affects Regulatory T Cells in Acute Lung Injury

Background High-mobility group box-1 protein (HMGB1) serves as the prototypic damage-associated molecular pattern molecule, and TLR4 is considered a receptor for HMGB1. Regulatory T cells (Tregs) play a crucial role in infectious diseases. The role of HMGB1 in the modulation of Tregs is of great interest. Methods Serum HMGB1 and Treg proportions were detected in 58 patients with acute lung injury (ALI) and 36 healthy volunteers. The correlations of these parameters with disease severity were analyzed. The WT and TLR4-/- mice were administered HMGB1 by intratracheal injection. After 48 h, the mice were sacrificed. The morphological changes and wet/dry ratio of the lung were measured. Spleen CD4+CD25+ Tregs were sorted from spleen cells, the expression of FOXP3 and CTLA-4, and releasing of cytokines was detected. CD4+CD25+ Tregs were cocultured with effector T cells, the inhibitory effect, and release of cytokines was detected. Results Significantly increased plasma levels of HMGB1 and reduced CD4+CD25+CD127low Tregs were detected in ALI patients. In the mouse model, lung injury was significantly increased after HMGB1 instillation in the WT and TLR4-/- groups compared with control group. The lung wet/dry ratio and the TNF-α and IL-1β contents in BALF were significantly increased, and the severity of WT mice was higher than that of TLR4-/- mice. The expression of FOXP3 and CTLA-4 in TLR4-/- mice was significantly increased compared with that in WT mice and was associated with a similar trend of IL-10 and TGF-β levels (p<0.05). In coculture with effector T cells, Tregs isolated from TLR4-/- mice exhibited decreased IL-2 and IFN-γ and increased IL-4 levels compared with Tregs from WT mice. Increased polarization of TLR4-/- CD4+CD25+ Treg cells to Th2 cells was observed. Conclusion In HMGB1-induced lung injury, HMGB1 affects the expression of FOXP3 and CTLA-4 through TLR4, thus reducing the immunosuppressive function of Treg cells.
Optical Coherence Tomography-Guided Femtosecond LASIK in the Setting of Corneal Scarring

Purpose To report the outcomes of femtosecond-assisted laser in situ keratomileusis (LASIK) in patients with previous corneal scarring using optical coherence tomography (OCT) imaging to determine flap depths. Methods The charts of 11 eyes of 9 patients with previous off-visual axis corneal scarring that underwent femtosecond LASIK using OCT guidance for flap depth determination were retrospectively reviewed at a single private practice institution. The baseline characteristics, intraoperative findings and postoperative outcomes were analyzed. Results All 11 eyes underwent femtosecond laser flap creation and LASIK without any significant intraoperative complications. Uncorrected visual acuity improved postoperatively (p<0.0001) and remained stable at 3 months follow-up. None of the subjects lost any lines of best spectacle corrected visual acuity or developed any flap complications during the postoperative period. Conclusion The OCT-guided femtosecond laser technique described in this report can provide a safe and effective method to deliver LASIK in the setting of previous corneal scarring. Future investigations are required to further validate the findings in this study.
A Smart Multifunctional Nanoparticle for Enhanced Near-Infrared Image-Guided Photothermal Therapy Against Gastric Cancer

Background Surgery is considered to be a potentially curative approach for gastric cancer. However, most cases are diagnosed at a very advanced stage for the lack of typical symptoms in the initial stage, which makes it difficult to completely surgical resect of tumors. Early diagnosis and precise personalized intervention are urgent issues to be solved for improving the prognosis of gastric cancer. Herein, we developed an RGD-modified ROS-responsive multifunctional nanosystem for near-infrared (NIR) imaging and photothermal therapy (PTT) against gastric cancer. Methods Firstly, the amphiphilic polymer was synthesized by bromination reaction and nucleophilic substitution reaction of carboxymethyl chitosan (CMCh) and 4-hydroxymethyl-pinacol phenylborate (BAPE). Then, it was used to encapsulate indocyanine green (ICG) and modified with RGD to form a smart multifunctional nanoparticle targeted to gastric cancer (CMCh-BAPE-RGD@ICG). The characteristics were determined, and the targeting capacity and biosafety were evaluated both in vitro and in vivo. Furthermore, CMCh-BAPE-RGD@ICG mediated photothermal therapy (PTT) effect was studied using gastric cancer cells (SGC7901) and SGC7901 tumor model. Results The nanoparticle exhibited suitable size (≈ 120 nm), improved aqueous stability, ROS-responsive drug release, excellent photothermal conversion efficiency, enhanced cellular uptake, and targeting capacity to tumors. Remarkably, in vivo studies suggested that CMCh-BAPE-RGD@ICG could accurately illustrate the location and margin of the SGC7901 tumor through NIR imaging in comparison with non-targeted nanoparticles. Moreover, the antitumor activity of CMCh-BAPE-RGD@ICG-mediated PTT could effectively suppress tumor growth by inducing necrosis and apoptosis in cancer cells. Additionally, CMCh-BAPE-RGD@ICG demonstrated excellent biosafety both in vitro and in vivo. Conclusion Overall, our study provides a biocompatible theranostic nanoparticle with enhanced tumor-targeting ability and accumulation to realize NIR image-guided PTT in gastric cancer.
Migraine with Brainstem Aura Accompanied by Disorders of Consciousness

Abstract Migraine with brainstem aura (MBA) accompanied by disorders of consciousness (DOC) is a rare subtype of migraine. The pathophysiology of MBA with DOC has not been elucidated yet. Some patients have a family history of migraine, and women are more affected than men. The aura symptoms are diverse; however, when MBA is combined with DOC, the clinical manifestations are more complicated. Coma is the most common clinical manifestation. The overall duration of the patient’s DOC is short and can often return to normal within half an hour. Headache often occurs after regaining consciousness and can also occur at the same time as DOC. The most common headache is located at the occipital region. Although DOC is reversible, considering the current small number of cases, we still need to improve our understanding of the disease to avoid misdiagnosis. The MBA patient’s electroencephalogram and cerebral blood flow perfusion may have transient changes and may return to normal in the interictal period or after the DOC. Although triptans have traditionally been contraindicated in MBA under drug instructions, the evidence of basilar artery constriction, as postulated in MBA, is lacking. Lasmiditan is currently the first and only 5-HT 1F receptor agonist approved by the Food and Drug Administration. The calcitonin gene-related peptide receptor antagonists and monoclonal antibody therapies may be the most promising for future consideration. Here, the pathophysiology, clinical manifestations, diagnostic tools, and treatment progress for MBA with DOC are reviewed.