Minimal hepatic encephalopathy: Effect of H. pylori infection and small intestinal bacterial overgrowth treatment on clinical outcomes

The effect Helicobacter pylori (Hp) infection and small intestinal bacterial over growth (SIBO) in minimal hepatic encephalopathy (MHE) is not well understood. The aim of the study was to determine the effect of eradication of Hp infection and SIBO treatment on MHE in patients with cirrhosis. Patients with cirrhosis were enrolled and MHE was determined by psychometric tests and critical flicker frequency analysis. Hp infection and SIBO were assessed by urea breath and Hydrogen breath tests respectively in patients with cirrhosis and in healthy volunteers. Patients with Hp infection and SIBO were given appropriate treatment. At six weeks follow-up, presence of Hp infection, SIBO and MHE status was reassessed. Ninety patients with cirrhosis and equal number of healthy controls were included. 55 (61.1%) patients in the cirrhotic group were diagnosed to have underlying MHE. Among cirrhotic group, Hp infection was present in 28 with MHE (50.9%) vs. in 15 without MHE (42.8%) (p = 0.45). Similarly, SIBO was present in 17 (30.9%) vs. 11 (31.4%) (p = 0.95) in patients with and without MHE respectively. In comparison with healthy controls, patients with cirrhosis were more frequently harboring Hp and SIBO (47.7% vs. 17.7% (p \u3c 0.001) and 31.1% vs. 4.4% (p \u3c 0.001) respectively. On follow-up, all patients showed evidence of eradication of Hp and SIBO infection. Treatment of SIBO significantly improved the state of MHE in cirrhotics, however eradication of Hp infection did not improve MHE significantly. Additionally, patients with low Model for End-Stage Liver Disease (MELD) score and belonging to Child class B had significantly better improvement in MHE. A large number of patients with cirrhosis had either active Hp infection or SIBO with or without MHE, compared to healthy controls. Treatment of SIBO significantly improved MHE in patients with cirrhosis, whereas eradication of Hp did not affect the outcome of MHE in these patients

Passive cooling analysis of an electronic chipset using nanoparticles and metal-foam composite PCM: An experimental study

Thermal management of electronic components is critical for long-term reliability and continuous operation, as the over-heating of electronic equipment leads to decrement in performance. The novelty of the current experimental study is to investigate the passive cooling of electronic equipment, by using nano-enriched phase change material (NEPCM) with copper foam having porosity of 97 %. The phase change material of PT-58 was used with graphene nanoplatelets (GNPs) and magnesium oxide (MgO) nanoparticles (NPs), having concentrations of 0.01 wt. % and 0.02 wt. %. Three power levels of 8 W, 16 W, and 24 W, with corresponding heating inputs of 0.77 kW/ m2, 1.54 kW/ m2 and 2.3 kW/ m2, respectively, were used to simulate the heating input to heat sink for thermal characterization. According to results, at 0.77 kW/ m2 heating input the maximum base temperature declined by 13.03 % in 0.02 wt. % GNPs-NEPCM/copper foam case. At heating input of 1.54 kW/ m2, the maximum base temperature reduction of 16 % was observed in case of 0.02 wt. % GNPs-NEPCM/copper foam and 13.1 % in case of 0.02 wt. % MgO-NEPCM/copper foam. Similarly, at heating input of 2.3 kW/ m2, the maximum temperature of base lessened by 12.58 % in case of 0.02 wt. % GNPs-NEPCM/copper foam. The highest time to reach the set point temperature of 50 ⁰ C, 60 ⁰ C, and 70 ⁰ C was in case of GNPs-NEPCM/copper foam composites, while at all power levels MgO-NEPCM/copper foam gave comparable performance to GNPs based composite. Similar trend was observed in the study of enhancement ratio in operation time. From the results, it is concluded that the copper foam incorporation in NEPCM is an effective measure to mitigate the heat sink base temperature and can provide best cooling efficiency at low and higher heating loads

VisTAS:Blockchain-based Visible and Trusted Remote Authentication System

The information security domain focuses on security needs at all levels in a computing environment in either the Internet of Things, Cloud Computing, Cloud of Things, or any other implementation. Data, devices, services, or applications and communication are required to be protected and provided by information security shields at all levels and in all working states. Remote authentication is required to perform different administrative operations in an information system, and Administrators have full access to the system and may pose insider threats. Superusers and administrators are the most trusted persons in an organisation. “Trust but verify” is an approach to have an eye on the superusers and administrators. Distributed ledger technology (Blockchain-based data storage) is an immutable data storage scheme and provides a built-in facility to share statistics among peers. Distributed ledgers are proposed to provide visible security and non-repudiation, which securely records administrators’ authentications requests. The presence of security, privacy, and accountability measures establish trust among its stakeholders. Securing information in an electronic data processing system is challenging, i.e., providing services and access control for the resources to only legitimate users. Authentication plays a vital role in systems’ security; therefore, authentication and identity management are the key subjects to provide information security services. The leading cause of information security breaches is the failure of identity management/authentication systems and insider threats. In this regard, visible security measures have more deterrence than other schemes. In this paper, an authentication scheme, “VisTAS,” has been introduced, which provides visible security and trusted authentication services to the tenants and keeps the records in the blockchain

A semantic rule based digital fraud detection

Digital fraud has immensely affected ordinary consumers and the finance industry. Our dependence on internet banking has made digital fraud a substantial problem. Financial institutions across the globe are trying to improve their digital fraud detection and deterrence capabilities. Fraud detection is a reactive process, and it usually incurs a cost to save the system from an ongoing malicious activity. Fraud deterrence is the capability of a system to withstand any fraudulent attempts. Fraud deterrence is a challenging task and researchers across the globe are proposing new solutions to improve deterrence capabilities. In this work, we focus on the very important problem of fraud deterrence. Our proposed work uses an Intimation Rule Based (IRB) alert generation algorithm. These IRB alerts are classified based on severity levels. Our proposed solution uses a richer domain knowledge base and rule-based reasoning. In this work, we propose an ontology-based financial fraud detection and deterrence model

Impact of Monetary Policy on Inflation Rate in Pakistan

This research paper empirically examines the relationship between the monetary policy and inflation and investigates the impact of monetary policy attributes such as Gross domestic product (GDP),Interest rate, export, Money Supply(M2),Foreign Direct lnvestment(FDI) and inflation on the economy of Pakistan. Multiply regression ordinary least square correlation analysis is used in estimating relationship between the monetary policy and inflation and their impact on economy of Pakistan measure as the GDP, interest rate, Money supply, Export. For analysis the 20 year

Comparative analysis of TF-IDF and loglikelihood method for keywords extraction of twitter data

Twitter has become the foremost standard of social media in today’s world. Over 335 million users are online monthly, and near about 80% are accessing it through their mobiles. Further, Twitter is now supporting 35+ which enhance its usage too much. It facilitates people having different languages. Near about 21% of the total users are from US and 79% of total users are outside of US. A tweet is restricted to a hundred and forty characters; hence it contains such information which is more concise and much valuable. Due to its usage, it is estimated that five hundred million tweets are sent per day by different categories of people including teacher, students, celebrities, officers, musician, etc. So, there is a huge amount of data that is increasing on a daily basis that need to be categorized. The important key feature is to find the keywords in the huge data that is helpful for identifying a twitter for classification. For this purpose, Term Frequency-Inverse Document Frequency (TF-IDF) and Loglikelihood methods are chosen for keywords extracted from the music field and perform a comparative analysis on both results. In the end, relevance is performed from 5 users so that finally we can take a decision to make assumption on the basis of experiments that which method is best. This analysis is much valuable because it gives a more accurate estimation which method’s results are more reliable

Privacy-aware relationship semantics–based XACML access control model for electronic health records in hybrid cloud

State-of-the-art progress in cloud computing encouraged the healthcare organizations to outsource the management of electronic health records to cloud service providers using hybrid cloud. A hybrid cloud is an infrastructure consisting of a private cloud (managed by the organization) and a public cloud (managed by the cloud service provider). The use of hybrid cloud enables electronic health records to be exchanged between medical institutions and supports multipurpose usage of electronic health records. Along with the benefits, cloud-based electronic health records also raise the problems of security and privacy specifically in terms of electronic health records access. A comprehensive and exploratory analysis of privacy-preserving solutions revealed that most current systems do not support fine-grained access control or consider additional factors such as privacy preservation and relationship semantics. In this article, we investigated the need of a privacy-aware fine-grained access control model for the hybrid cloud. We propose a privacy-aware relationship semantics–based XACML access control model that performs hybrid relationship and attribute-based access control using extensible access control markup language. The proposed approach supports fine-grained relation-based access control with state-of-the-art privacy mechanism named Anatomy for enhanced multipurpose electronic health records usage. The proposed (privacy-aware relationship semantics–based XACML access control model) model provides and maintains an efficient privacy versus utility trade-off. We formally verify the proposed model (privacy-aware relationship semantics–based XACML access control model) and implemented to check its effectiveness in terms of privacy-aware electronic health records access and multipurpose utilization. Experimental results show that in the proposed (privacy-aware relationship semantics–based XACML access control model) model, access policies based on relationships and electronic health records anonymization can perform well in terms of access policy response time and space storage

Improved Generalization for Secure Data Publishing

In data publishing, privacy and utility are essential for data owners and users respectively, which cannot coexist well. This incompatibility puts the data privacy researchers under an obligation to find newer and reliable privacy preserving tradeoff-techniques. Data providers like many public and private organizations (e.g. hospitals and banks) publish microdata of individuals for various research purposes. Publishing microdata may compromise the privacy of individuals. To prevent the privacy of individuals, data must be published after removing personal identifiers like name and social security numbers. Removal of the personal identifiers appears as not enough to protect the privacy of individuals. K-anonymity model is used to publish microdata by preserving the individual's privacy through generalization. There exist many state-of-the-arts generalization-based techniques, which deal with pre-defined attacks like background knowledge attack, similarity attack, probability attack and so on. However, existing generalization-based techniques compromise the data utility while ensuring privacy. It is an open question to find an efficient technique that is able to set a trade-off between privacy and utility. In this paper, we discussed existing generalization hierarchies and their limitations in detail. We have also proposed three new generalization techniques including conventional generalization hierarchies, divisors based generalization hierarchies and cardinality-based generalization hierarchies. Extensive experiments on the real-world dataset acknowledge that our technique outperforms among the existing techniques in terms of better utility

A word sense disambiguation corpus for Urdu

The aim of word sense disambiguation (WSD) is to correctly identify the meaning of a word in context. All natural languages exhibit word sense ambiguities and these are often hard to resolve automatically. Consequently WSD is considered an important problem in natural language processing (NLP). Standard evaluation resources are needed to develop, evaluate and compare WSD methods. A range of initiatives have lead to the development of benchmark WSD corpora for a wide range of languages from various language families. However, there is a lack of benchmark WSD corpora for South Asian languages including Urdu, despite there being over 300 million Urdu speakers and a large amounts of Urdu digital text available online. To address that gap, this study describes a novel benchmark corpus for the Urdu Lexical Sample WSD task. This corpus contains 50 target words (30 nouns, 11 adjectives, and 9 verbs). A standard, manually crafted dictionary called Urdu Lughat is used as a sense inventory. Four baseline WSD approaches were applied to the corpus. The results show that the best performance was obtained using a simple Bag of Words approach. To encourage NLP research on the Urdu language the corpus is freely available to the research community

Effects of a high-dose 24-h infusion of tranexamic acid on death and thromboembolic events in patients with acute gastrointestinal bleeding (HALT-IT): an international randomised, double-blind, placebo-controlled trial

Background: Tranexamic acid reduces surgical bleeding and reduces death due to bleeding in patients with trauma. Meta-analyses of small trials show that tranexamic acid might decrease deaths from gastrointestinal bleeding. We aimed to assess the effects of tranexamic acid in patients with gastrointestinal bleeding. Methods: We did an international, multicentre, randomised, placebo-controlled trial in 164 hospitals in 15 countries. Patients were enrolled if the responsible clinician was uncertain whether to use tranexamic acid, were aged above the minimum age considered an adult in their country (either aged 16 years and older or aged 18 years and older), and had significant (defined as at risk of bleeding to death) upper or lower gastrointestinal bleeding. Patients were randomly assigned by selection of a numbered treatment pack from a box containing eight packs that were identical apart from the pack number. Patients received either a loading dose of 1 g tranexamic acid, which was added to 100 mL infusion bag of 0·9% sodium chloride and infused by slow intravenous injection over 10 min, followed by a maintenance dose of 3 g tranexamic acid added to 1 L of any isotonic intravenous solution and infused at 125 mg/h for 24 h, or placebo (sodium chloride 0·9%). Patients, caregivers, and those assessing outcomes were masked to allocation. The primary outcome was death due to bleeding within 5 days of randomisation; analysis excluded patients who received neither dose of the allocated treatment and those for whom outcome data on death were unavailable. This trial was registered with Current Controlled Trials, ISRCTN11225767, and ClinicalTrials.gov, NCT01658124. Findings: Between July 4, 2013, and June 21, 2019, we randomly allocated 12 009 patients to receive tranexamic acid (5994, 49·9%) or matching placebo (6015, 50·1%), of whom 11 952 (99·5%) received the first dose of the allocated treatment. Death due to bleeding within 5 days of randomisation occurred in 222 (4%) of 5956 patients in the tranexamic acid group and in 226 (4%) of 5981 patients in the placebo group (risk ratio [RR] 0·99, 95% CI 0·82–1·18). Arterial thromboembolic events (myocardial infarction or stroke) were similar in the tranexamic acid group and placebo group (42 [0·7%] of 5952 vs 46 [0·8%] of 5977; 0·92; 0·60 to 1·39). Venous thromboembolic events (deep vein thrombosis or pulmonary embolism) were higher in tranexamic acid group than in the placebo group (48 [0·8%] of 5952 vs 26 [0·4%] of 5977; RR 1·85; 95% CI 1·15 to 2·98). Interpretation: We found that tranexamic acid did not reduce death from gastrointestinal bleeding. On the basis of our results, tranexamic acid should not be used for the treatment of gastrointestinal bleeding outside the context of a randomised trial