bluuebunny/crossref_metadata_2025_split huggingface dataset:
Certain Investigation on IOT Based Smart Pill Carafe in Health Care
Authors: Vignesh  , Gopalan S Harihara , Arokia Mary Celsia J , Indumathy N , Harida A 
Published: May 2021

Abstract
During recent years, many technologies has been evolved for health care. It helps in quick recovery of patients in healthcare. As the population is increasing, the need of health prevention is also increasing day by day. In order to improve the patient health and to treat dehydration a bottle of saline is fed to the patient. Whenever a saline is fed to the patients, the care taker/nurse has to continuously monitor the patient. Assessing and managing of saline, good care for the patients are the most important thing in health care. The responsibility for monitoring the Glucose bottle levelis done bycare taker/nurse. The saline bottle should be checked and changed periodically. But, due to their busy schedule the nurse/caretaker may forget to change. In order to overcome this critical situation a system is designed to monitor the glucose bottle smartly is proposed using GSM( Global System for Mobile Communication). When the intravenous fluid level is below certain limit the IR sensor output voltage level changes based on the principle. The message output is compared continuously using comparator with a threshold value. When the liquid level reaches to its threshold value, the alert will be given through the LCD display. It will also provide intimation to the mobile phone with the help of GSM.
Mobile Application in Rental Batteries for Electronic Vehicles
Authors: Supriya M , Sangeetha V S , Subhasini A , Vaishnav M 
Published: May 2021

Abstract
People nowadays are more or less familiar with buying and selling batteries. But have not really experienced batteries renting or service systems online. Here we are going to develop an application for the users to get benefits of lending, renting, selling and buying a battery through an application. Also, this application make use of people to rent batteries for various reasons including Electronic Vehicles (EV). This Application contains list of Batteries that are available for the customer, and also acts as a one stop solution for all battery related problems. The Customer has another advantage that they can easily find service centers for batteries nearby. Especially in India, the production rate and Consumers of Electronic Vehicles are fairly increasing each and every day. This Application will create a better impact amongst people and will be a Boon factor for customers.
Arduino based firefighting Robot
Authors: Kirubakaran S , Rithanyaa S P , Thanavarsheni S P , Vigneshkumar E 
Published: May 2021

Abstract
A fire fighter’s work entails detecting and extinguishing fires. In this rapidly evolving technological age, the world is gradually moving toward automated systems. Firefighters, on the other hand, are often in danger of losing their lives. The majority of the deaths were caused by toxic gases found in the firefighting environment. As a result, in order to resolve these issues, our system was developed.
Medicine Lending Machine for Elderly Patients
Authors: Suresh C , Sri Krishna P , Shalini D , Rakeshraj J , Rajeshkumar N. 
Published: May 2021

Abstract
In this fast moving life style almost everything around us are getting automated. This in turn greatly reduces the time taken for a work and also increases efficiency. An automatic medicine lending machine is one that helps the patients and uneducated people to keep track on their medical pills in a timely manner. This machine contains containers that contain loaded pills that can be dispensed in timely manner. Major components in this machine are stepper motor, large storage space and inventory monitoring system. All these are monitored by a program fed microcontroller. This machine also contains the alarm system which reminds the patient to take pills at correct time. This machine also has a data storage system which stores the exact date and time that the patient took the medicine from the medical box. From the above concept we can conclude that, this medicine lending machine is feasible for elderly patients to take the medicines by alerting them at the right time.
Power Theft Recognition and data security in Smart Meter Reading of a Smart Grid
Authors: Vineeth V V , Ambrish V , Haricharann D V , Harshini V , Abilash C 
Published: May 2021

Abstract
Smart meter is an important component of smart grid environment has enormous features like precise measurement and possibility of two way communication among the entities involved in grid. Nevertheless, it has distinctive features like intricate structure, resource constriction and confidential sensitive data. These features make a meter structure more susceptible for attack and error. Power theft is identified as a major threat in meter infrastructure. Several literature has found to study this issue in detail because it poses a great threat to the overall grid architecture. This paper investigates the major thefts and threats in such an environment and identifies the essential safety prerequisites to be maintained by a smart meter. A risk model is identified using attack characteristics to figure out major risks. Different class of power theft detection mechanisms are analysed and reviewed to precisely define and understand the attack vulnerability in smart meters.
Anti-Theft Fuel Level Detector with Vehicle Tracking
Authors: Udhaya Kumar A , Vishnukanth S , Deepak kumar A , Nandalal V , Sathishkumar N 
Published: May 2021

Abstract
The appearance, deployment, as well as the evaluation of a computing device for the Fleet Management Solution including trucks that transport fuel are presented in this article. The key aim is to build a framework that can track the backlog instantaneously. The approach are imagined any road tankers that transport petrol transport End customers, such as service stations, get petrol in oil warehouses. However, as code, this technique is reliant on hardware. Shipment electronics, Diy on-board, Wireless communications, and Gp modules are all included. make up the hardware version 0.5. whereas LabView is used for data functions in PC code 0.5. This approach proposes the use of an Automatic Electronic System (AES) to replace manual fuel monitoring. This system tests fuel volume and sends the details to the owner’s cell phone as well as the owner’s device through the GSM network. It also offers a tool for identifying stealing or fraud incidents in the event of gasoline robbery or discharge. Furthermore, the device will monitor the activities every carrier transporting energy in order to determine the location of any incidents Which should have occurred.. Thanks to inadequate and easy-to-acquire electronic elements, this approach allows for automated backlog tracking and tracking at a lower cost. GSM, GPS, AES, and ARDUNIO are some of the terminology used in this article.
Fake News Detection on Social Media Using Machine Learning
Authors: Santhosh Kumar A , Kalpana P , Sharan Athithya K , Sri Ajay Sundar V 
Published: May 2021

Abstract
The project examines the techniques behind detecting “fake news”, i.e. misleading news stories from trustworthy sources. The invention of the World Wide Web and the wide embracing of social media networks (such as Facebook, Twitter) opened the way for information sharing that has never before been seen in human history. The use of social media sites is becoming more independent as a forum for information creation and sharing than ever before. Some of the users are confusing and impractical. It’s no easy task to design a system that automatically highlights an article as dishonest or even misleading. You can tell if an email is reliable even if you are not an expert. And an authority in a particular area needs to go through the process of finding out the facts before reaching a judgement of what is true or not. Reviews suggest the use of the classifier algorithm to plump-up the detection of news stories via machine learning. But these models don’t represent the basic quality of language, such as word order and importance of words. It is very likely that two articles would have the same word count, but would have total differences in their content. The information technology group (information science) wasting in response to the matter. Fiercely each combatting the fake news may be a classical text classification effort that offers a simple proposal. There is a good deal of evidence that may be used for constructing a model of false news or real news. One suggestion is a kind of a Naive Bayes grouping, where articles that are deceptive, speculative, imaginative, or fresh or without researched supporting information may be considered one thing, while those that are measured as fully supported true information may be considered the other.
Co-mutation modules capture the evolution and transmission patterns of SARS-CoV-2
Authors: Qin Luyao , Ding Xiao , Li Yongjie , Chen Qingfeng , Meng Jing , Jiang Taijiao 
Published: May 2021

Abstract
The rapid spread and huge impact of the COVID-19 pandemic caused by the emerging SARS-CoV-2 have driven large efforts for sequencing and analyzing the viral genomes. Mutation analyses have revealed that the virus keeps mutating and shows a certain degree of genetic diversity, which could result in the alteration of its infectivity and pathogenicity. Therefore, appropriate delineation of SARS-CoV-2 genetic variants enables us to understand its evolution and transmission patterns. By focusing on the nucleotides that co-substituted, we first identified 42 co-mutation modules that consist of at least two co-substituted nucleotides during the SARS-CoV-2 evolution. Then based on these co-mutation modules, we classified the SARS-CoV-2 population into 43 groups and further identified the phylogenetic relationships among groups based on the number of inconsistent co-mutation modules, which were validated with phylogenetic trees. Intuitively, we tracked tempo-spatial patterns of the 43 groups, of which 11 groups were geographic-specific. Different epidemic periods showed specific co-circulating groups, where the dominant groups existed and had multiple sub-groups of parallel evolution. Our work enables us to capture the evolution and transmission patterns of SARS-CoV-2, which can contribute to guiding the prevention and control of the COVID-19 pandemic. An interactive website for grouping SARS-CoV-2 genomes and visualizing the spatio-temporal distribution of groups is available at https://www.jianglab.tech/cmm-grouping/.
DOP08 Serum proteomics predict endoscopic remission in patients with Crohn’s Disease
Authors: Alsoud D , Sudhakar P , Sabino J , Ferrante M , Verstockt B , Vermeire S 
Published: May 2021

Abstract

Background
Recent progress in deciphering the complex pathogenesis of Crohn’s disease (CD) has yielded several effective biologicals. However, ambitious therapeutic goals remain unfulfilled as almost 30% of patients are primary non-responders to a particular biological. This underscores the need for easy-to-implement biomarkers that predict (non-)remission. We aimed to identify serum protein biomarkers that predict endoscopic remission in CD patients.

Methods
Serum samples from 169 consecutive CD patients with active endoscopic disease (presence of ulcerations) before starting a biological [infliximab (IFX), adalimumab (ADA), vedolizumab (VDZ) or ustekinumab (UST)] to which they were naïve were collected. Patients were prospectively followed with endoscopic re-assessment after 6–12 months. There were 102 patients (Table 1) with endoscopic remission (SES ≤ 2 or disappearance of all ulcers), whereas 67 showed no improvement. Two independent and complementary proteomic platforms were used: 644 proteins belonging to predesigned assays were quantified using Proximity Extension Assay (PEA) technology (Olink Proteomics AB, Sweden). Second, wide protein discovery mass spectrometry (MS)-based technic (Caprion, Canada) was used and quantified another 985 proteins. A multivariate modelling framework was then applied on a randomly selected training sub-cohort (85%). Predictive performance of identified panels was assessed on the remaining test sub-cohort (15%). We sought to implement the same framework on the drug-specific subgroups; however, train/test splitting was not possible in IFX or ADA subgroups due to very few observations in the non-remission arms which diminishes the possibility for reliable predictive modelling.

Results
Applying the modelling framework on training sets from the general cohort, VDZ subgroup and UST subgroup, proteomic panels were selected and consisted of 26, 6 and 8 proteins, respectively, and showed high performance in the test sets (Table 2). VDZ and UST panels shared only 2 proteins each with the general panel, and had no predictive power (accuracy ≤ 0.5) when used to predict other subgroups, making them specific to their respective drugs. Selected proteins are involved among others in pro-inflammatory, extracellular matrix modelling, coagulation and cellular-vascular interaction pathways (Table 3).

Conclusion
Applying a multivariate machine learning algorithm on a wide pool of serum proteomics analysed through two discovery technics, we were able to identify 3 proteomic panels that can predict endoscopic (non)remission in patients with CD. Exact implication of these proteins in intestinal inflammation and a validation in an independent cohort is being further investigated.
DOP90 Physician global assessment of IBD Activity is associated with COVID-19 severity in patients aged less than 50 years
Authors: Ricciuto A , Lamb C , Benchimol E I , Walker G , Kennedy N , Kuenzig M E , Kaplan G , Griffiths A M , Reinisch W , Sebastian S 
Published: May 2021

Abstract

Background
SECURE-IBD is an international database that monitors COVID-19 outcomes in IBD patients. We examined the influence of IBD activity (reflected by Physician Global Assessment (PGA)) on COVID-19 severity, while exploring the modifying effect of age.

Methods
We analyzed 3,028 cases reported to SECURE-IBD from March 13-November 17, 2020. PGA was categorized as remission/mild (reference) vs moderate vs severe. Outcomes used as surrogates of severe SARS-CoV2 infection were hospitalization and a composite of ICU/ventilation/death. Using generalized estimating equations (GEE) to account for clustering by country, we determined the unadjusted association between disease activity and COVID-19 outcomes, overall and by age decade. We included the following covariates in multivariable GEE models a priori: time of COVID-19 diagnosis, age, sex, comorbidities (0, 1, ≥2), IBD type, systemic corticosteroids (CS), anti-TNF monotherapy, anti-TNF plus immune modulator, immune modulator monotherapy, and mesalamine. We included additional covariates (country GDP, race, BMI, anti-integrins and ustekinumab) if they changed the estimate by ≥10%. We also built models stratified by age; the age cut-off for stratification was determined using Joinpoint regression (selecting the age at which outcome rates significantly changed).

Results
COVID-19 was more severe in patients with more active IBD: hospitalization rates 19% (remission/mild), 26% (moderate) and 45% (severe); ICU/ventilation/death rates 5% (remission/mild), 6% (moderate) and 12% (severe) (p&lt;0.05, Figure 1). In unadjusted analyses, higher PGA was associated with an increased risk of hospitalization (moderate: OR 1.53, 95% CI 1.24–1.88; severe: OR 3.30, 95% CI 2.44–4.46) and ICU/ventilation/death (moderate: OR 1.44, 95% CI 1.10–1.87; severe: OR 2.58, 95% CI 1.71–3.90). As per Figure 2, the magnitude of association between severe PGA (vs remission/mild) and adverse outcomes was greatest in patients ≤50 years. Joinpoint regression also supported a significant change in the rate of ICU/ventilation/death at 50 years. In multivariable analyses (Figure 3), PGA remained significantly associated with hospitalization, but not ICU/ventilation/death. However, in multivariable analyses stratified by age, PGA was consistently associated with both hospitalization and ICU/ventilation/death in patients ≤50, but not &gt;50 years.

Conclusion
Our data suggest an association between IBD activity, as assessed by PGA, and severe COVID-19 outcome with an increased risk in younger patients. Adequate IBD treatment despite the pandemic is needed to avert poor outcome to symptomatic SARS-CoV2 infections.
N18 Multidisciplinary team importance in the view of the patients with Inflammatory Bowel Disease in Brazil
Authors: Herrerias G , Ribeiro J R , Beraldo R F , Hossne R S , Baima J P , Sassaki L Y 
Published: May 2021

Abstract

Background
Inflammatory Bowel Disease (IBD) is characterized by intestinal chronic inflammation that comprehend Crohn’s disease (CD) and ulcerative colitis (UC). Continuous care is essential. Constant contact with the multidisciplinary team (MDT) and its quality of care interferes with treatment adherence and patients’ quality of life (QoL). MDT must be composed by at least gastroenterologists, coloproctologists, nutritionists, nurses and psychologists. The study evaluated the importance of MDT in the patients view.

Methods
A cross-sectional, descriptive study was developed, including 94 patients from a Brazilian IBD reference center. Clinical data and the MDT relevance were evaluated. MDT importance was assessed through a questionnaire developed for the research with the answers: nothing important, unimportant, important and very important for each professional. The patients listed professionals in order of importance. QoL was assessed by IBDQ. Treatment adherence and disease knowledge were assessed by Morisky and CCKNOW questionnaires respectively.

Results
A total of 54 patients with CD and 40 with UC were included, 59.57% female and 53.19% with comorbidities. Previous hospitalization was reported by 54.26% and 36.17% were submitted by previous surgery. The majority referred previous consultation with a gastroenterologist (95.74%) and less than half with nutritionist (47.87%), IBD nurse (43.62%), psychologist (43.62%) and coloproctologist (23.40%). Gastroenterologist was considered important or very important by all patients, coloproctologist by 97.15%, IBD nurse 94.36%, endoscopist nurse 86.16%, stomatherapist 78.19%, nutritionist 88.46% and psychologist 80.55%. Regarding the order of importance, patients reported the gastroenterologist (87.50%) as the most important, followed by the coloproctologist (16.67%) and IBD nurse (14.10%). Patients with CD had more appointments with IBD nurse compared to UC patients (p = 0.007). QoL was considered excellent or good (64.51%). Drug adherence was low in 58.89% of patients. Knowledge about the disease was considered low (2.65 ± 1.65 points), being higher in patients with CD (p = 0.04).

Conclusion
Although the service has MDT, not all patients had the opportunity to visit all professionals. The lack of contact with the entire team, especially with the nurse, can reflect on low medication adherence and disease knowledge, impacting on disease control and QoL. Holistic patient care is recommended, emphasizing the importance of all professionals in the MDT for all patients with IBD.
P006 Host-genetics, dysbiosis, and clinical history explains fecal metabolic alterations in patients with Inflammatory Bowel Disease
Authors: Vich Vila A , Hu S , Andreu-Sánchez S , Collij V , Jansen D , Ruigrok R , Abu-Ali G , Parkinson J , Al Garawi A , Schneider J , Kurilshikov A , Björk J , Gacesa R , Fu J , Zhernakova A , Weersma R K 
Published: May 2021

Abstract

Background
The pathogenesis of inflammatory bowel diseases is characterized by gastrointestinal dysbiosis. Small molecules -or metabolites- present in feces can improve our understanding of host and microbes’ interactions. By exploring the relationship between host genetics, gut microbiota, and fecal metabolites composition from 500 patients with IBD and 255 population controls, we aimed to identify potential new biomarkers for the disease and to reveal host-microbiota interactions while considering factors like life-style and clinical history.

Methods
In short, we used shotgun sequencing to profile the microbiota composition, and an untargeted metabolomics platform (Metabolon INC., USA) was used to identify the levels of 1684 fecal metabolites. Whole exome sequencing and GSA Illumina chip were used to characterize host’s genetics. Multi-omics penalized regressions were used to explore the relationship between metabolite levels and the use of 44 types of medication, 144 long-term dietary patterns, and multiple patient characteristics. Random forest models were used to determine the discriminative power of metabolites.

Results
The levels of 597 fecal metabolites were altered in Crohn’s disease and 209 in patients with ulcerative colitis compared to population controls. Disease heterogeneity was reflected in the fecal metabolite profile; for example, disease location had a large impact on fecal bile-acid profile. Interestingly, metabolomics data could discriminate IBD samples from non-IBD samples (Random Forest AUC= 0.81). Genetic polymorphisms in the NAT2 gene were associated with the levels of multiple coffee metabolites. In both cohorts, IBD and non-IBD individuals, the increase in the abundance of several pathobionts was related to changes in the tryptophan, fatty-acids, and bilirubin metabolism. For example, the increase in abundance of R.gnavus was correlated with higher tryptamine levels, and the presence of bacterial starch degradation enzymes with increased concentrations of butyrate (FDR&lt;0.05). In fact, microbial composition and bacterial enzyme abundance could predict more than 40% of the variation in the levels of 80 metabolites.

Conclusion
Patients with IBD present a different fecal metabolite profile that can be used to distinguish IBD from non-IBD individuals. Metabolite patterns are strongly related to microbial composition, diet, and patient’s clinical characteristics. Overall, these results can help to understand the disease’s complexity considering host-microbiota interaction and point to new therapeutical directions.