Robust Outlier Detection Method Based on Local Entropy and Global Density

By now, most outlier-detection algorithms struggle to accurately detect both point anomalies and cluster anomalies simultaneously. Furthermore, a few K-nearest-neighbor-based anomaly-detection methods exhibit excellent performance on many datasets, but their sensitivity to the value of K is a critical issue that needs to be addressed. To address these challenges, we propose a novel robust anomaly detection method, called Entropy Density Ratio Outlier Detection (EDROD). This method incorporates the probability density of each sample as the global feature, and the local entropy around each sample as the local feature, to obtain a comprehensive indicator of abnormality for each sample, which is called Entropy Density Ratio (EDR) for short in this paper. By comparing several competing anomaly detection methods on both synthetic and real-world datasets, it is found that the EDROD method can detect both point anomalies and cluster anomalies simultaneously with accurate performance. In addition, it is also found that the EDROD method exhibits strong robustness to the number of selected neighboring samples, the dimension of samples in the dataset, and the size of the dataset. Therefore, the proposed EDROD method can be applied to a variety of real-world datasets to detect anomalies with accurate and robust performances

Intelligent H2S release coating for regulating vascular remodeling

Coronary atherosclerotic lesions exhibit a low-pH chronic inflammatory response. Due to insufficient drug release control, drug-eluting stent intervention can lead to delayed endothelialization, advanced thrombosis, and unprecise treatment. In this study, hyaluronic acid and chitosan were used to prepare pH-responsive self-assembling films. The hydrogen sulfide (H2S) releasing aspirin derivative ACS14 was used as drug in the film. The film regulates the release of the drug adjusted to the microenvironment of the lesion, and the drug balances the vascular function by releasing the regulating gas H2S, which comparably to NO promotes the self-healing capacity of blood vessels. Drug releasing profiles of the films at different pH, and other biological effects on blood vessels were evaluated through blood compatibility, cellular, and implantation experiments. This novel method of self-assembled films which H2S in an amount, which is adjusted to the condition of the lesion provides a new concept for the treatment of cardiovascular diseases

Altered metabolic-functional coupling in the epileptogenic network could predict surgical outcomes of mesial temporal lobe epilepsy

ObjectiveTo investigate the relationship between glucose metabolism and functional activity in the epileptogenic network of patients with mesial temporal lobe epilepsy (MTLE) and to determine whether this relationship is associated with surgical outcomes.Methods18F-FDG PET and resting-state functional MRI (rs-fMRI) scans were performed on a hybrid PET/MR scanner in 38 MTLE patients with hippocampal sclerosis (MR-HS), 35 MR-negative patients and 34 healthy controls (HC). Glucose metabolism was measured using 18F-FDG PET standardized uptake value ratio (SUVR) relative to cerebellum; Functional activity was obtained by fractional amplitude of low-frequency fluctuation (fALFF). The betweenness centrality (BC) of metabolic covariance network and functional network were calculated using graph theoretical analysis. Differences in SUVR, fALFF, BC and the spatial voxel-wise SUVR-fALFF couplings of the epileptogenic network, consisting of default mode network (DMN) and thalamus, were evaluated by Mann-Whitney U test (using the false discovery rate [FDR] for multiple comparison correction). The top ten SUVR-fALFF couplings were selected by Fisher score to predict surgical outcomes using logistic regression model.ResultsThe results showed decreased SUVR-fALFF coupling in the bilateral middle frontal gyrus (PFDR = 0.0230, PFDR = 0.0296) in MR-HS patients compared to healthy controls. Coupling in the ipsilateral hippocampus was marginally increased (PFDR = 0.0802) in MR-HS patients along with decreased BC of metabolic covariance network and functional network (PFDR = 0.0152; PFDR = 0.0429). With Fisher score ranking, the top ten SUVR-fALFF couplings in regions from DMN and thalamic subnuclei could predict surgical outcomes with the best performance being a combination of ten SUVR-fALFF couplings with an AUC of 0.914.ConclusionThese findings suggest that the altered neuroenergetic coupling in the epileptogenic network is associated with surgical outcomes of MTLE patients, which may provide insight into their pathogenesis and help with preoperative evaluation

Catechol-chitosan/polyacrylamide hydrogel wound dressing for regulating local inflammation

Chronic wounds and the accompanying inflammation are ongoing challenges in clinical treatment. They are usually accompanied by low pH and high oxidative stress environments, limiting cell growth and proliferation. Ordinary medical gauze has limited therapeutic effects on chronic wounds, and there is active research to develop new wound dressings. The chitosan hydrogel could be widely used in biomedical science with great biocompatibility, but the low mechanical properties limit its development. This work uses polyacrylamide to prepare double-network (DN) hydrogels based on bioadhesive catechol-chitosan hydrogels. Cystamine and N, N′-Bis(acryloyl)cystamine, which can be cross-linking agents with disulfide bonds to prepare redox-responsive DN hydrogels and pH-responsive nanoparticles (NPs) prepared by acetalized cyclodextrin (ACD) are used to intelligently release drugs against chronic inflammation microenvironments. The addition of catechol groups and ACD-NPs loaded with the Resolvin E1 (RvE1), promotes cell adhesion and regulates the inflammatory response at the wound site. The preparation of the DN hydrogel in this study can be used to treat and regulate the inflammatory microenvironment of chronic wounds accurately. It provides new ideas for using inflammation resolving factor loaded in DN hydrogel of good biocompatibility with enhanced mechanical properties to intelligent regulate the wound inflammation and promote the wound repaired

Upregulation of Heme Oxygenase-1 Endues Immature Dendritic Cells With More Potent and Durable Immunoregulatory Properties and Promotes Engraftment in a Stringent Mouse Cardiac Allotransplant Model

Heme oxygenase-1 (HO-1) is critical for the ability of immature dendritic cells (imDCs) to suppress T-cell responses. Induction of high HO-1 expression may markedly improve the tolerogenic capacity of imDCs. Here, we generated bone marrow-derived DCs (BMDCs) from BALB/c mice with low doses of GM-CSF and IL-4. The adherent BMDCs were obtained as imDCs. Upregulation of HO-1 in imDCs (HO-1hi-imDCs) was achieved by cobalt protoporphyrin treatment. HO-1hi-imDCs proved to be more maturation-resistant than conventional imDCs, with an enhanced ability to inhibit allogeneic T-cell proliferation stimulated by anti-CD3/CD28 antibodies. When donor-derived DC adoptive transfer was performed in a stringent mouse cardiac allotransplant model, the extent of graft prolongation observed with HO-1hi imDCs was superior to that obtained with conventional imDCs. T-cell activation and proliferation in cardiac allograft recipients was more strongly suppressed in the HO-1hi imDC transfusion group than that in the untreated imDC group. Furthermore, donor HO-1hi imDCs were able to maintain a status of high HO-1 expression and survived longer in the recipient spleens than did untreated imDCs after adoptive transfer. In vitro-generated HO-1hi imDCs had an enhanced tolerogenic capacity to modulate alloimmune responses both in vitro and in vivo, and thus may offer a novel antigen-specific and cost-effective strategy to induce transplant tolerance

Project Managers’ Career Development in the Contract Research Organization

A trend towards projectification of work has given rise to increasing attention in the implications of career development for project professionals in the contract research organization. To meet this trend, the purpose of this project is to understand how project managers experience their career development and how organization influence career development of project managers. My study adapts the social cognitive career theory (SCCT) framework as a lens to investigate the complex interplay between different factors from individual and organizational aspects that form the project managers’ career development. The thesis answers the following research questions: Overall RQ. How could project managers build their career through contract research projects in project-based organization (PBO)? RQ1. How do project managers experience their career development in contract research organization (CRO)? RQ2. How does contract research organization (CRO) influence the careers development of project managers? I conducted a case study in the technology institute of a contract research organization, using semi-structured interviews with 25 project managers to collect data to analyze my theoretical propositions. My revised new SCCT framework has practical implication for project practitioners to build and flourish their career, and emphasize the key factor in organizational influence which has significant impact on career development of their project managers. Project practitioners need to be proactive in managing their careers, while project-based organizations need to see the importance of developing specialization in career model for their project managers. Moreover, this thesis presents theoretical implication for the integration of career literature and project management literature and enriches the field of human resource management and project-based organization domain in the academy

NMLPA: Uncovering Overlapping Communities in Attributed Networks via a Multi-Label Propagation Approach

With the enrichment of the entity information in the real world, many networks with attributed nodes are proposed and studied widely. Community detection in these attributed networks is an essential task that aims to find groups where the intra-nodes are much more densely connected than the inter-nodes. However, many existing community detection methods in attributed networks do not distinguish overlapping communities from non-overlapping communities when designing algorithms. In this paper, we propose a novel and accurate algorithm called Node-similarity-based Multi-Label Propagation Algorithm (NMLPA) for detecting overlapping communities in attributed networks. NMLPA first calculates the similarity between nodes and then propagates multiple labels based on the network structure and the node similarity. Moreover, NMLPA uses a pruning strategy to keep the number of labels per node within a suitable range. Extensive experiments conducted on both synthetic and real-world networks show that our new method significantly outperforms state-of-the-art methods

Fast Distributed Inference Serving for Large Language Models

Large language models (LLMs) power a new generation of interactive AI applications exemplified by ChatGPT. The interactive nature of these applications demand low job completion time (JCT) for model inference. Existing LLM serving systems use run-to-completion processing for inference jobs, which suffers from head-of-line blocking and long JCT. We present FastServe, a distributed inference serving system for LLMs. FastServe exploits the autoregressive pattern of LLM inference to enable preemption at the granularity of each output token. FastServe uses preemptive scheduling to minimize JCT with a novel skip-join Multi-Level Feedback Queue scheduler. Based on the new semi information-agnostic setting of LLM inference, the scheduler leverages the input length information to assign an appropriate initial queue for each arrival job to join. The higher priority queues than the joined queue are skipped to reduce demotions. We design an efficient GPU memory management mechanism that proactively offloads and uploads intermediate states between GPU memory and host memory for LLM inference. We build a system prototype of FastServe based on NVIDIA FasterTransformer. Experimental results show that compared to the state-of-the-art solution Orca, FastServe improves the average and tail JCT by up to 5.1$\times$ and 6.4$\times$, respectively

Magnetic Weyl Semimetal in BaCrSe2 with Long‐Distance Distribution of Weyl Points

Abstract Weyl semimetals (WSMs) have attracted great attentions that provide intriguing platforms for exploring fundamental physical phenomena and future topotronics applications. Despite the fact that numerous WSMs are achieved, WSMs with long‐distance distribution of Weyl points (WPs) in given material candidates remain elusive. Here, the emergence of intrinsic ferromagnetic WSMs in BaCrSe2 with the nontrivial nature explicitly confirmed by the Chern number and Fermi arc surface states analysis is theoretically demonstrated. Remarkably, unlike previous WSMs for which opposite chirality WPs are located very close to each other, the WPs of BaCrSe2 host a long‐distance distribution, as much as half of the reciprocal space vector, suggesting that the WPs are highly robust and difficult to be annihilated by perturbations. The presented results not only advance the general understanding of magnetic WSMs but also put forward potential applications in topotronics