Web Search Tools Research Articles

6889 Potential Impact of Parental Origin of Inheritance in Presentation of Familial Partial Lipodystrophy

Abstract Disclosure: D. Gilio: None. M.C. Foss de Freitas: Advisory Board Member; Self; PTC Therapeutics. Speaker; Self; Amryt. O. Besci: None. M. Celik Guler: None. A. Neidert: None. I. Yildirim: None. B. Akinci: Advisory Board Member; Self; Amryt. Consulting Fee; Self; Regeneron Pharmaceuticals, Alnylam Pharmaceuticals, Amryt, AstraZeneca, Boehringer Ingelheim, Lilly, MSD, Novartis Pharmaceuticals, Novo Nordisk, Sanofi-Aventis, Servier, Third Rock Ventures. E.A. Oral: Advisory Board Member; Self; Amryt, Regeneron Pharmaceuticals. Consulting Fee; Self; Regeneron Pharmaceuticals, Amryt, Third Rock Ventures. Grant Recipient; Self; Regeneron Pharmaceuticals, Amryt. Research Investigator; Self; Novo Nordisk, Fractyl, Ionis Pharmaceuticals Inc., GI Dynamics, Rhythm Pharmaceuticals. Other; Self; Amryt. Background: Familial partial lipodystrophy Type 2 (FPLD2) caused by autosomal dominant LMNA variants is characterized by partial loss of subcutaneous adipose tissue in the limbs, trunk, and gluteal region with accumulation in other parts of the body, such as the face and neck. It is usually associated with different degrees of insulin resistance and hypertriglyceridemia and body composition patterns. We wanted to know the contributing factors for the different metabolic abnormalities and body composition presentations of FPLD2. We hypothesized that parental inheritance line may be a contributory factor to the expression of the metabolic phenotype and body composition characteristics. Methods: We retrospectively collected clinical data of 77 FPLD2 cases from the Divisions of Metabolism and Endocrinology of 3 different sites: the University of Michigan, the University of São Paulo and The Turkish Lipodystrophy Study Group (TuLip). We further selected 53 published cases curated from 15 studies in the literature. For inclusion of the studies, we used web search tools including PubMed, OMIM and Google Scholar. Only patients where we could assess the genetic inheritance were included in this study. Data collected included demographic information, medical history and laboratory results. Results: 79 patients inherited the LMNA variant from the mother (Group 1; 18 males and 61 females), and 51 patients inherited it from the father (Group 2; 14 males and 37 females). The median age at lipodystrophy diagnosis was lower in Group 1 than in Group 2. Diabetes was reported in more than half of the groups; however, the prevalence rates were not significantly different. The mean age (± SEM) at first diagnosis of diabetes was 30 ± 15 years in Group 1 and 32 ± 11 years in Group 2; the microvascular complications were present in 8 patients with diabetes in Group 1 (36.3%) and in 5 patients in Group 2 (23.8%). Both groups' mean triglycerides levels were >150 mg/dL, with a trend of higher triglycerides in Group 2 than in Group 1. Episodes of acute pancreatitis were identified in 9 patients (19.5%) of Group 1 and 10 patients (31.2%) of Group 2; however, patients in Group 1 showed 1.7 episodes of pancreatitis per person while Group 2 showed 8.1 episodes per person on average. The fatty liver disease was the most common liver abnormality identified and it seemed to be more frequent in Group 2 than in Group 1. There was no difference between the two groups in relation to the body mass index (BMI) and the ratio of percent fat mass of the trunk to percent fat mass of the legs (FMR); however, the DEXA (dual x-ray absorptiometry) showed a higher total fat mass in Group 1 compared to Group 2 (22.2 versus 17.3 Kg, p=0.040) in the presence of comparable total lean mass. Conclusion: Our data suggest that there is a difference in body fat mass according to the genetic inheritance, however the metabolic impact is not completely clear and require more detailed analysis. Presentation: 6/1/2024

Information Retrieval Based Legal Search System

Calculating the similarity between two legal documents to find similar legal judgments is an important challenge in legal information. Efficiently computing this similarity by expanding widely used information retrieval and search engine techniques has practical applications in a number of tasks, like locating pertinent prior cases for a specific case document. Programmed data recovery frameworks or reports are the main parts of today’s selected emotional support networks or web indexes to reduce data overload. Investigating methodologies to work on the presentation of report recovery frameworks and web search tools is a working area of research. Various methods have been pro- posed in this research paper to explore ways to search the common law system for cases with a similar outcome. Building a legal decision support system is intended to increase efficiency by assisting stakeholders—including judges and attorneys—in finding related rulings promptly. In order to prepare arguments, a lawyer typically has to review earlier decisions that are comparable to (or pertinent to) the current case. The attorney examines the judgement database to discover similar judgements. Legal rulings are complex in nature and refer to other judgments. For this, proper techniques are needed for quality analysis of judgments and correct deductions from them. A proper analysis of several types of similarity measures, such as all-term-based similarity methods, legal terms, co-citations, and bibliographic links, performed to look for comparable conclusions. According to experimental findings, the law term similarity approach outperforms all term cosine similarity methods. The out- comes also demonstrate that the co-citation approach performs worse than the bibliographic linkage similarity method and improves performance over the co-citation approach. After proper analysis of various methods in this field, proper comparison can be made between documents and similar legal documents can also be easily searched based on their similarity pattern and can be used to make meaningful deductions.

Multi Label Automatic Image Annotation Neural Network to Handle Multi Media Image Retrieval

The present-day business online web indexes have embraced electronic picture search to further develop precision in picture information recovery. However Re-positioning is expectedly considered as a successful cycle for deciding the situation with electronic picture web search tools, yet it experiences a lack of a couple of. Consequently, some grouping methods, particularly (Novel Image Re-positioning System) NIRS have to be proposed to carry out inquiry picture re-positioning with semantic marks in electronic picture information recovery, which naturally recovers results in view of visual semantic highlights for various question or catchphrase extensions. To get to productive picture with the annotation is an aggressive concept in present. So that in the present paper, we are going to propose the Unsupervised Multi Labeled Image Annotate Learning Approach (UMLIALA) to decrease complexity in indexing of image with mining of web related convex optimization and classify required image data from large image data sets. And also use group based approximation calculation to improve accuracy in retrieval of images from different image data sources. Experiments of proposed approach give better and efficient results when compare to traditional approaches in terms of different image exploration parameters studies on different large image data sets.

Infectivity, Morbidity, Emerged Variants of SARS-CoV-2 and Vaccination in Indian Perspectives from First Wave to Second Wave of COVID-19

More than one year since coronavirus disease 2019 was declared a deadly disease by World Health Organization, the deadly severe acute respiratory syndrome Coronavirus 2 continues to disrupt public life worldwide. Several nations have seen a two-wave design in revealed instances of COVID 19 pandemic, with a first wave of infection during early 2K20 followed by the ongoing second wave. An investigation of the predominance of COVID-19 in India from the first wave to the second wave was utilized to characterize critical contrasts, infection patterns, lethality, and therapeutic measures through extensive vaccination pan-India free of cost. The quantitative transmission brought about COVID-19, including meteorological boundaries and topographical locale information, was gathered using web search tools and available literature and substantiated by factual advanced numerical tools. Experimental information showed that the qualities of the infection impacts do change between the two-time frames. The examination between the first wave and second wave, where COVID-19 flare-ups were now turning out to be scourged, was contemplated. Contrasts in age reach and seriousness of the infection have been accounted for, albeit the relative qualities of the two waves remain to a great extent obscure. The present investigation recommends that variability in environmental temperature and moisture contents may not be the significant components influencing the COVID-19 mortality during different waves of infection. The second wave of COVID-19 is influencing a large portion of the world, and especially the middle age group person relies on the principal top.

Comparative Study of Multimedia Question Answering System Models

Question Answering Systems is a mechanized way to deal with finding right solution to the inquiries posed by human in their own language. The enormous measure of data returned by web crawlers like Google, Yahoo, and so on, clients are over-burden to track down the right data from the web search tools. This QA approach takes care of these issues. Rather than returning a rundown of reports and connections from the momentum web crawler, the QA framework gives data from a bunch of replied, alongside reasonable media information. Question answering procedures plans to exploit top to bottom etymological and media content investigation just as area information to return accurate responses to regular language questions. QA framework has rundown of boundary like: question size, m-dimension, technique count, answer cardinality, and answer range. This paper investigates the advancement of mixed media question replying research, their plan boundary, and subtleties its future perspectives. Multiple Line Questions and Video Question Answering methods have been discussed at length and their performance measured on QA framework parameters.

AI-Assisted Design Concept Exploration Through Character Space Construction.

We propose an AI-assisted design concept exploration tool, the “Character Space Construction” (“CSC”). Concept designers explore and articulate the target product aesthetics and semantics in language, which is expressed using “Design Concept Phrases” (“DCPs”), that is, compound adjective phrases, and contrasting terms that convey what are not their target design concepts. Designers often utilize this dichotomy technique to communicate the nature of their aesthetic and semantic design concepts with stakeholders, especially in an early design development phase. The CSC assists this designers' cognitive activity by constructing a “Character Space” (“CS”), which is a semantic quadrant system, in a structured manner. A CS created by designers with the assistance of the CSC enables them to discern and explain their design concepts in contrast with opposing terms. These terms in a CS are retrieved and combined in the CSC by using a knowledge graph. The CSC presents terms and phrases as lists of candidates to users from which users will choose in order to define the target design concept, which is then visualized in a CS. The participants in our experiment, who were in the “arts and design” profession, were given two conditions under which to create DCPs and explain them. One group created and explained the DCPs with the assistance of the proposed CSC, and the other did the same task without this assistance, given the freedom to use any publicly available web search tools instead. The result showed that the group assisted by the CSC indicated their tasks were supported significantly better, especially in exploration, as measured by the Creativity Support Index (CSI).

Analysis of Mathematical Aspect Rank Algorithm in Google Page

Page Rank algorithm is the core concept used in Google Search Engine . It is a widely known algorithm which helps in giving rank to the web pages and hence, it determines the order in which they are to be displayed during a search .It was developed in 1998.Almost all web search tools still use the Page Rank algorithm as their foundation. In this paper, we will get an overview of application of linear algebra and graphs in Google's Page Rank algorithm.

Tracking COVID-19 using taste and smell loss Google searches is not a reliable strategy

Web search tools are widely used by the general public to obtain health-related information, and analysis of search data is often suggested for public health monitoring. We analyzed popularity of searches related to smell loss and taste loss, recently listed as symptoms of COVID-19. Searches on sight loss and hearing loss, which are not considered as COVID-19 symptoms, were used as control. Google Trends results per region in Italy or state in the US were compared to COVID-19 incidence in the corresponding geographical areas. The COVID-19 incidence did not correlate with searches for non-symptoms, but in some weeks had high correlation with taste and smell loss searches, which also correlated with each other. Correlation of the sensory symptoms with new COVID-19 cases for each country as a whole was high at some time points, but decreased (Italy) or dramatically fluctuated over time (US). Smell loss searches correlated with the incidence of media reports in the US. Our results show that popularity of symptom searches is not reliable for pandemic monitoring. Awareness of this limitation is important during the COVID-19 pandemic, which continues to spread and to exhibit new clinical manifestations, and for potential future health threats.

WITHDRAWN: Design and analysis of low power self-controlled content addressable memory architecture

Abstract Content-Addressable Memory (CAM) is optimized equipment for equal search with enhanced features. CAMs are equipment web search tools that are a lot quicker than adjusted algorithmic methodologies for search-concentrated applications. The equal pursuit plot guarantees a fast inquiry activity yet at the expense of high force utilization. Equal NOR & NAND-type CAMs are reasonable for good pursuit speed and low-power-utilization relevance, individually. The fundamental test in structuring this undertaking is to diminish the force utilization without decreasing the speed and memory thickness. Here this memory is utilized to upgrade the exhibition level while looking through information from memory. The focal point of this work is on the memory cell plan, for coordinate goal and speed address recognition. As of late, a pre sans charge ML structure has been proposed however with insufficient capture execution. In this undertaking, Parity Bit Based Pre without charge CAM is proposed to lessen the force and speed up. These are appropriate for both high capture speed and low force utilization applications. Essentially, these are utilized for bundle sending in arrange switches. Likewise in this venture, the Parity-bit based Self-Controlled Pre charge–Free CAM is used as a blocking site or go about as an IP channel and a CAM-helped SRAM circuit is utilized for lessening the force and improving the capture speed. This plan is re-enacted utilizing Tanner instrument.

Knowledge and awareness on the use of gold and silver nanoparticles in endodontics practice - A survey

To make mindfulness and teach professionals about the impact of consolidating gold and silver NPs on the shear bond quality in endodontics. Silver and Gold nanoparticles have uncommon attributes that settle on them as great decisions as fillers for dental caries filling. They could remain in nanoscale in the nearness of appropriate stabilizers which implies little collection or bunching and consistently dispersed particles. They have high synthetic dependability and make them simple to be integrated and controlled. Biocompatibility makes them nontoxic for living beings. Some considered the nearness of nanoparticles could redirect the miniaturized scale split and viably increment the protection from the applied force to diminish the clinical disappointments because of less bond quality composite. This study will be helpful. This overview assesses the information and mindfulness on the utilization of gold and silver nanoparticles in endodontic practice. An absolute number of 20 articles were chosen—period (or) term considered for reference articles 2000 to 2020. The information for this article was gathered from web search tools like PUBMED, GOOGLE SCHOLAR, MESH, COCHRANE, SEMANTIC SCHOLAR. Through this examination, we have talked about the mindfulness utilization of gold and silver nanoparticles in endodontic practice. It makes professionals know about the benefits of gold and silver nanoparticles.

A Concept-Based Approach for Generating Better Topics for Web Search Results

As the web is accessible to a vast population around the globe, web users today pose a large number of queries, with dynamic, vague and unclear intentions, using the web search tools, as a consequence of which organizing search results have become an all the more challenging task. Further, because of such web queries, it is difficult for web search tools to comprehend the exact user context, and thus they retrieve an extensive volume of results, a significant portion of which are unnecessary for the user. One of the answers to this problem is a strategy called search result clustering (SRC), which bunches the search results and presents them to users with many options for the query. In this work, we have proposed an approach that initially classifies the related topics and lays them out in the form of concepts, and then building search results clusters by designating each to the relevant topic and finally, providing relevant labels for these topics. We examine the effectiveness of our approach by measuring it against two most popular non-commercial methods in this field, specifically Lingo and STC, with two standard datasets, ODP and Ambient, and a newly developed dataset, Ex-Ambient, which is a rigorously extended version of the Ambient Dataset. We performed analysis on both qualitative and quantitative dimensions. We define a qualitative dimension as the expressiveness of the cluster label generated, while quantitative dimension regards the correctness of the document assigned to the cluster. The experimental results presented by the proposed method were encouraging in contrast with Lingo and STC for all the datasets and both the dimensions.

Comparative Analysis of Ranking Algorithms Used On Web

With the evolution in technology huge amount of data is being generated, and extracts the necessary data from large volumes of data. This process is significantly complex. Generally the web contains bulk of raw data and the process of converting this data to information mining process can be performed. At whatever point the user places some inquiry on particular web search tool, outcomes are produced with respect to the requests which are dependent on the magnitude of the document created via web information retrieval tools. The results are obtained using calculations and implementation of well written algorithms. Well known web search tools like Google and other varied engines contain their specific manner to compute the page rank, various outcomes are obtained on various web crawlers for a same inquiry because the method for deciding the importance of the sites contrasts among number of algorithm. In this research, an attempt to analyze well-known page ranking calculation on the basis of their quality and shortcomings. This paper places the light on a portion of the extremely mainstream ranking algorithm and attempts to discover a better arrangement that can optimize the time spent on looking through the list of sites.

Biomedical Data Mining for Web Relevance Checking

Now a day's web is the primary wellspring of data in each field. Web is additionally extending exponentially step by step procedure. To get the applicability of data is very tedious and is anything but an extremely simple assignment. For the most part of clients go for the different web indexes to look through any data. However, here and there web search tools are not ready to give valuable outcomes as the vast majority of the web archives are available in an unstructured way. Information mining is the extraction of data from an enormous database. This project can be useful in diagnostics, treatment, and counteraction of any ailment. There are large numbers of archives on the web about biomedical an explicit term so to acquire a pertinent record is exceptionally troublesome. The objective of this project is to apply content mining strategies to recover helpful biomedical web records. Here an increasingly productive instrument is proposed which utilizes the advanced SVM algorithm, grouping calculation where it can aggregate the comparable archives in a single spot. In this paper proposed smartly designed web mining algorithms to extract the textual form of information on web pages and to apply for web applications. This proposed system gives more helpful in all biomedical sectors. Search engines can be used to do the regression on the web pages into the biomedical structure. This methodology will assist the client in getting all the important relevant biomedical information in one place. On contrasting my methodology and the first SVM algorithm calculation that we use with an improved k-mean algorithm and found that our calculation on a normal giving 99.72 % results.

As Mulheres e o parto midiatizado

As ferramentas de busca na internet são uma das primeiras fontes de informação sobre qualquer assunto atualmente. O parto enquanto prática social reflete a realidade midiatizada. Neste artigo, é feita uma análise dos principais resultados de termos de pesquisa utilizados no Google Search que evidenciam o parto como um assunto que ganhou destaque no cotidiano da população e da mídia. Com uma breve análise do discurso de notícias em sites sobre o parto de Ivete Sangalo, Kate Middleton e Eliana, é possível verificar como o assunto vem sendo tratado pela mídia, demonstrando como a própria sociedade encara o tema. Para realizar este artigo, utilizamos as bases teóricas de Patrick Charaudeau, Eni Orlandi e Maria Immacolata Vassallo de Lopes.

Impact of Polypharmacy on Candidate Biomarker miRNomes for the Diagnosis of Fibromyalgia and Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: Striking Back on Treatments

Fibromyalgia (FM) and myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) are diseases of unknown etiology presenting complex and often overlapping symptomatology. Despite promising advances on the study of miRNomes of these diseases, no validated molecular diagnostic biomarker yet exists. Since FM and ME/CFS patient treatments commonly include polypharmacy, it is of concern that biomarker miRNAs are masked by drug interactions. Aiming at discriminating between drug-effects and true disease-associated differential miRNA expression, we evaluated the potential impact of commonly prescribed drugs on disease miRNomes, as reported by the literature. By using the web search tools SM2miR, Pharmaco-miR, and repoDB, we found a list of commonly prescribed drugs that impact FM and ME/CFS miRNomes and therefore could be interfering in the process of biomarker discovery. On another end, disease-associated miRNomes may incline a patient’s response to treatment and toxicity. Here, we explored treatments for diseases in general that could be affected by FM and ME/CFS miRNomes, finding a long list of them, including treatments for lymphoma, a type of cancer affecting ME/CFS patients at a higher rate than healthy population. We conclude that FM and ME/CFS miRNomes could help refine pharmacogenomic/pharmacoepigenomic analysis to elevate future personalized medicine and precision medicine programs in the clinic.

Webportal vs google for finding government information on the web: From a website-centric approach to a web ecology perspective

Webportals – websites that operate as front doors or guides into government on the web – are central to government web strategy and presence. However, little is known about their success in enabling people to quickly and accurately access public sector information and services. In these days of Google and generic web search engines, government webportals are not the only way to find government on the web. This paper argues that an effective evaluation of government webportals requires shifting from a website perspective to a whole-of-web (or web ecology) perspective. This perspective is illuminated by an online quasi-experiment of the effectiveness of the British government’s webportal, www.gov.uk. Participants’ performance in using the webportal to find information about public services were compared with those using commercial web search tools (such as Google). There was mixed evidence that the portal provided greater accuracy in finding public service information, but no evidence for greater speeds. The findings suggest that government web strategy focus less on creating large webportals and more on small functionally-defined web units that offer enhanced opportunities for commercial search engine discoverability and flexibility for change.

Application of Webometrics Techniques for Measuring and Evaluating Visibility of University Library Websites in Sri Lanka

A library website plays an enhanced role compared to its traditional physical library while providing a wide variety of library services to its users. Evaluation of library websites is a key to realize the extent of user acceptance acceptance acceptanceacceptanceacceptance acceptance of the website and to improve the overall quality of the website. Under such backdrop, this paper provides a framework for ranking university library websites in Sri Lanka based on two standard webometric methods. The proposed framework consists of quantitative web presence measuring attributes namely; size, visibility, rich files and scholars along with simple and comprehensible mathematical calculations. The library administrators can get awareness about whether their website has effectively represented itself on the internet with better performance from the ranking results. The findings of the study will guide to the librarians to evaluate the strengths and weaknesses accordingly with the performance of their library websites. In general, the effective presence of these library websites on the internet can be passed on as the top by having proper number of site pages in the website that impact their perceivability through web search tools and accordingly the quantity of received external links. Meanwhile, libraries having low rich files can publish more rich files on the web to improve their overall rank. The research approach, criteria and their relative impact provide useful information in monitoring the effectiveness of the current websites and provide strategic suggestions to develop enhanced websites.

The Characteristics of Voice Search

The growing popularity of mobile search and the advancement in voice recognition technologies have opened the door for web search users to speak their queries rather than type them. While this kind of voice search is still in its infancy, it is gradually becoming more widespread. In this article, we report a comprehensive voice search query log analysis of a commercial web search engine’s mobile application. We compare voice and text search by various aspects, with special focus on the semantic and syntactic characteristics of the queries. Our analysis suggests that voice queries focus more on audio-visual content and question answering and less on social networking and adult domains. In addition, voice queries are more commonly submitted on the go. We also conduct an empirical evaluation showing that the language of voice queries is closer to natural language than the language of text queries. Our analysis points out further differences between voice and text search. We discuss the implications of these differences for the design of future voice-enabled web search tools.

Using Primo for undergraduate research: a usability study

Purpose The purpose of this paper is to observe how undergraduate students approach open-ended searching for a research assignment, specifically as it affected their use of the discovery interface Primo. Design/methodology/approach In total, 30 undergraduate students were provided with a sample research assignment and instructed to find resources for it using web tools of their choice, followed by the Primo discovery tool. Students were observed for 30 minutes. A survey was provided at the end to solicit additional feedback. Sources students found were evaluated for relevance and utility. Findings Students expressed a high level of satisfaction with Primo despite some difficulty navigating through more complicated tasks. Despite their interest in the tool and previous exposure to it, it was usually not the first discovery tool students used when given the research assignment. Students approached the open-ended search environment much like they would with a commercial search engine. Originality/value This paper focused on an open-ended search environment as opposed to a known-item scenario in order to assess students’ preferences for web search tools and how a library discovery layer such as Primo was a part of that situation. Evaluation of the resources students found relevant were also analyzed to determine to what degree the students understood the level of quality they exhibited and from which tool they were obtained.

An Enhanced Web Document Search Engine using a Semantic Network

With the rapid advancement of ICT technology, the World Wide Web (referred to as the Web) has become the biggest information repository whose volume keeps growing on a daily basis. The challenge is how to find the most wanted information from the Web with a minimum effort. This paper presents a novel ontology-based framework for searching the related web pages to a given term within a few given specific websites. With this framework, a web crawler first learns the content of web pages within the given websites, then the topic modeller finds the relations between web pages and topics via key words found on the web pages using the Latent Dirichlet Allocation (LDA) technique. After that, the ontology builder establishes an ontology which is a semantic network of web pages based on the topic model. Finally, a reasoner can find the related web pages to a given term by making use of the ontology. The framework and related modelling techniques have been verified using a few test websites and the results convince its superiority over the existing web search tools.