77 research outputs found

    Impact Analysis of False Data Injection Attack on Smart Grid State Estimation Under Random Packet Losses

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    Supervisory control and data acquisition (SCADA) system has been widely used in traditional power systems for operation and control. As increasingly more ICT technologies are deployed to improve the smartness of the power grid, cyber security is becoming an important issue in the development of smart grids, for example, false data injection attack (FDIA) poses a serious threat. The paper analyzes the impact of false data injection attack on smart grid state estimation under random packet losses. First, a measurement model of power grids under random packet loss is established, and an attack vector range that can fool the attack detector is acquired. Then, a mean square error matrix of weighted least squares estimation is proposed, taking into account potential false data injection attacks. A IEEE-14 nodes system is used to evaluate the performance of the weighted least squares state estimation under three different scenarios, namely false data injection attack only, random packet loss only, and under both random packet loss and false data injection attack

    Chronic pancreatitis: Pediatric and adult cohorts show similarities in disease progress despite different risk factors

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    Objectives: To investigate the natural history of chronic pancreatitis (CP), patients in the North American Pancreatitis Study2 (NAPS2, adults) and INternational Study group of Pediatric Pancreatitis: In search for a cuRE (INSPPIRE, pediatric) were compared. Methods: Demographics, risk factors, disease duration, management and outcomes of 224 children and 1,063 adults were compared using appropriate statistical tests for categorical and continuous variables. Results: Alcohol was a risk in 53% of adults and 1% of children (p<0.0001); tobacco in 50% of adults and 7% of children (p<0.0001). Obstructive factors were more common in children (29% vs 19% in adults, p=0.001). Genetic risk factors were found more often in children. Exocrine pancreatic insufficiency was similar (children 26% vs adult 33%, p=0.107). Diabetes was more common in adults than children (36% vs 4% respectively, p<0.0001). Median emergency room visits, hospitalizations, and missed days of work/school were similar across the cohorts. As a secondary analysis, NAPS2 subjects with childhood onset (NAPS2-CO) were compared to INSPPIRE subjects. These two cohorts were more similar than the total INSPPIRE and NAPS2 cohorts, including for genetic risk factors. The only risk factor significantly more common in the NAPS2-CO cohort compared with the INSPPIRE cohort was alcohol (9% NAPS2-CO vs 1% INSPPIRE cohorts, p=0.011). Conclusions: Despite disparity in age of onset, children and adults with CP exhibit similarity in demographics, CP treatment, and pain. Differences between groups in radiographic findings and diabetes prevalence may be related to differences in risk factors associated with disease and length of time of CP

    Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

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    Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers

    Chemical Derivatization Processes Applied to Amine Determination in Samples of Different Matrix Composition

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    Multicenter evaluation of the clinical utility of laparoscopy-assisted ERCP in patients with Roux-en-Y gastric bypass

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    Background and Aims The obesity epidemic has led to increased use of Roux-en-Y gastric bypass (RYGB). These patients have an increased incidence of pancreaticobiliary diseases yet standard ERCP is not possible due to surgically altered gastroduodenal anatomy. Laparoscopic-ERCP (LA-ERCP) has been proposed as an option but supporting data are derived from single center small case-series. Therefore, we conducted a large multicenter study to evaluate the feasibility, safety, and outcomes of LA-ERCP. Methods This is retrospective cohort study of adult patients with RYGB who underwent LA-ERCP in 34 centers. Data on demographics, indications, procedure success, and adverse events were collected. Procedure success was defined when all of the following were achieved: reaching the papilla, cannulating the desired duct and providing endoscopic therapy as clinically indicated. Results A total of 579 patients (median age 51, 84% women) were included. Indication for LA-ERCP was biliary in 89%, pancreatic in 8%, and both in 3%. Procedure success was achieved in 98%. Median total procedure time was 152 minutes (IQR 109-210) with median ERCP time 40 minutes (IQR 28-56). Median hospital stay was 2 days (IQR 1-3). Adverse events were 18% (laparoscopy-related 10%, ERCP-related 7%, both 1%) with the clear majority (92%) classified as mild/moderate whereas 8% were severe and 1 death occurred. Conclusion Our large multicenter study indicates that LA-ERCP in patients with RYGB is feasible with a high procedure success rate comparable with that of standard ERCP in patients with normal anatomy. ERCP-related adverse events rate is comparable with conventional ERCP, but the overall adverse event rate was higher due to the added laparoscopy-related events

    The use of OverStitchTM for the treatment of intestinal perforation, fistulas and leaks

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    Gastrointestinal perforations, leaks and fistulas may complicate endoscopic and surgical procedures. Surgical repair is associated with significant morbidity. Therapeutic endoscopic tools and techniques have included the application of tissue sealants, clip closure, and stent placement. Endoscopic suturing is a rapidly evolving minimally invasive technique. The OverStitchTM (Apollo Endosurgery, USA) is currently the only available endoscopic suturing system. Although technically more difficult than clip closure, endoscopic suturing allows closure of larger defects. In some settings, outcomes similar to surgical management with less morbidity may be achieved. This review describes the OverStitchTM endoscopic suturing system and the published literature regarding its use for perforations, leaks and fistulas

    HNTSumm: Hybrid text summarization of transliterated news articles

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    Data generated from social networking sites, blogs, digital magazines, and news websites is the largest human-generated data. Summarization is the process of extracting the crux of a document which when done manually can be tedious and deluging. Automatic text summarization is an approach that encapsulates long documents into a few sentences or words by enwrapping the gist and the principal information of the document. With the growth of social networking sites, eBooks, and e-Papers, the prevalence of transliterated words in text corpora is also on the rise. In this paper, we propose a word embeddings-based algorithm called HNTSumm by combining the advantages of unsupervised and supervised learning methods. The proposed algorithm HNTSumm algorithm is an imminent method for automatic text summarization of huge volumes of data that can learn word embeddings for words transliterated from other languages to English by utilizing weighted word embeddings from a Neural Embedding Model. Further, the amalgamation of extractive and abstractive approaches yields a concise and unambiguous summary of the text documents as the extractive approach eliminates redundant information. We employ a hybrid version of the Sequence-to-sequence models to generate an abstractive summary for the transliterated words. The feasibility of this algorithm was evaluated using two different news summary datasets and the accuracy scores were computed with the ROUGE evaluation metric. Experimental results corroborate the higher performance of the proposed algorithm and show HNTSumm outperforms relevant state-of-the-art algorithms for datasets with transliterated words
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