Name Tag Research Articles

Earth’s spheres: Conceptual and definitional debates

Eduard Suess’s invention of the word ‘biosphere’ sparked a trend of coining sphere-words, which has since evolved into something of a craze. Some of these words, such as atmosphere and hydrosphere, are simply name tags for their respective Earth spheres. Others, such as geosphere, are also used mainly as names but they carry more than one meaning. However, many sphere-words, including pedosphere, biosphere, ecosphere, anthroposphere, sociosphere, and technosphere, are far more than just names, bearing as they do, weighty conceptual connotations that fuel considerable debate. At a time when Earth and life scientists are attempting to understand the workings of the planet as a whole by modelling the interaction of its component spheres, and when they are collaborating with sociologists, anthropologists, and members of other human sciences to tackle current environmental challenges, it seems an opportune moment to probe the origin and meaning of words for the Earth spheres they investigate. To be sure, Earth System modelling is helping understand changes resulting from the interaction of all the Earth’s spheres, including the anthroposphere, over various time and space scales, while multidisciplinary, interdisciplinary, and transdisciplinary research is helping to address such global problems as sustainable development, climate change, water supply, and biodiversity loss. An awareness of the origin, development, and disputed meanings of many sphere-words that these approaches employ should prove salutary for their multifarious practitioners.

Next-Gen Linguistic Intelligence Image Summarizer for Documents Using Attention Model

Abstract: The process of producing a succinct synopsis of a text involves two primary techniques: both abstractive and extractive While abstractive summarising rephrases text in a way that is more human-like, extractive summarization chooses important statements straight. handbook Because it takes time and money to summarise because it requires reading through big texts, an automated text model with lots of features It is suggested to use both extractive and abstractive methods for summarising. Important sentences that are enhanced by linguistic features are identified by a feature-rich extractor. These sentences are then further enhanced by an abstracter that adds components such named entity tags and part-of-speech tags. Moreover, a loss function is presented to match attentions at the word and sentence levels. At last the summarized text is converted into image by using parsing and other relatable techniques.

Patient Perspectives Regarding Healthcare Professional Attire.

Introduction Physician attire has been shown to influence patients' impression of their healthcare provider. Scrubs and formal office attire are interchangeably worn by physicians. This study aimed to determine differences in scrubs and formal office attire on patient perceptions of professionalism, friendliness, aptitude, and empathy. Methods A single-center questionnaire study was conducted and a total of 150 patients were included. Patients were recruited from the inpatient and outpatient settings. Patients completed a questionnaire in which they rated 22 photographs. The photographs comprised a series of randomly arranged vignettes, with each participating physician appearing twice - once in formal office attire, once in scrubs. The physicians served as their own controls. Patients were asked to rate the depicted physicians based on the following four criteria - professionalism, friendliness, aptitude, and empathy. Each criterion was rated on an 11-point scale (0-10). Comprehensive demographic information, including age, gender, and race, was collected. Results A total of 150 responses were collected (50 inpatient and 50 orthopaedic surgery outpatient, 50 general medicine outpatient). Scrubs were rated significantly higher than formal office attire in all domains: professionalism [mean 7.52 (SD 1.95) vs. 6.69 (SD 2.38), p< 0.001], friendliness [mean 7.54 (SD 1.86) vs. 6.87 (SD 2.23), p< 0.001], aptitude [mean 7.44 (SD 1.99) vs. 6.72 (SD 2.36), p < 0.001] and empathy [mean 7.36 (SD 2.01) vs. 6.71 (SD 2.36), p < 0.001]. The perceived age of the physician did not affect any of the domain scores. Female physicians scored poorer in professionalism [mean 6.95 (SD 2.30) vs. 7.20 (SD 2.16), p < 0.05] compared to male physicians, but this difference resolved when analyzing only physicians wearing Scrubs. Conclusion Patients view physicians in scrubs as having higher professionalism, friendliness, aptitude, and empathy as compared to physicians in formal office attire. Physicians should don standardized colored scrubs with a prominent name tag to improve patient perceptions.

LEAN SIX SIGMA APPROACH TO IMPROVE THE PRODUCTION PROCESS IN THE GARMENT COMPANY: A CASE STUDY

PT “X” is a company engaged in the garment industry. The company is facing problems that inhibit the production process. These problems comprise an excess of product defects beyond the specified limits, a considerable rate of product returns, delays in product shipment, and disorderly arrangements in storing raw material. This study aims to determine the root causes of problems in the PT “X” and provide recommendations for improvement using the concept of lean six sigma. The waste assessment model is used to identify the dominant waste, while the value stream analysis tools is a method used to analyze the causes of the dominant waste. From the research results, four dominant wastes are identified, namely waste defects, unnecessary inventory, waiting and unnecessary motion, with percentages of 27.02%, 15.92%, 14.32% and 14.0% respectively. The results of the analysis using mapping tools show the details of waste in each dominant waste. Proposed recommendations for improvement are made using the failure mode and effect analysis based on the highest risk priority number for each dominant waste. The recommendations proposed by the researchers include implementing a standard operating procedure and work instruction for the sewing process; scheduling machine maintenance using reliability centered maintenance II; planning and scheduling materials using material requirement planning; implementing line balancing; and designing name tags, visual displays, and storage rack layout.

Developing a standardized categorization system for energy efficiency measures (1836-RP)

The growth of legislation to reduce energy use in existing buildings is producing a rich new trove of data about energy efficiency measures (EEMs), which has the potential to unlock new insights into the built environment. However, the lack of standardized EEM naming conventions and categorization methods is currently a major barrier to aggregating and analyzing this data. The goal of this study was to develop and test a novel standardized system for categorizing EEMs. The system consists of two components: a three-level building element-based categorization hierarchy, and a set of measure name tags, which are used to label an EEM and categorize it on the hierarchy. A demonstration and testing process was developed and applied to two sample datasets to evaluate the ability of the system to categorize a variety of EEMs. The results show that most EEMs can easily be categorized manually according to the new system, and highlight several challenges for automated categorization, including EEM names that are missing an element, contain a term not in the tag list, or contain synonyms or abbreviations. These results provide a replicable and systematic framework for the translation, aggregation, and analysis of EEM datasets from different sources.

Empowering health care workers with personalized data-driven feedback to boost hand hygiene compliance

Achieving high hand hygiene compliance among health care workers is a challenge, requiring effective interventions. This study investigated the impact of individualized feedback on hand hygiene compliance using an electronic monitoring system. A quasi-experimental intervention design with pretest-post-test was conducted in an orthopedic surgical ward. Participants served as their own controls. A 3-month baseline was followed by a 3-month intervention period. Hand hygiene events were recorded through sensors on dispensers, name tags, and near patient beds. Health care workers received weekly email feedback reports comparing their compliance with colleagues. Nineteen health care workers (17 nurses, 2 doctors) were included. Hand hygiene compliance significantly improved by approximately 15% (P<.0001) across all rooms during the intervention. The most substantial improvement occurred in patient rooms (17%, P<.0001). Compliance in clean and contaminated rooms increased by 10% (P=.0068) and 5% (P=.0232). The average weekly email open rate for feedback reports was 46%. Individualized feedback via email led to significant improvements in hand hygiene compliance among health care workers. The self-directed approach proved effective, and continuous exposure to the intervention showed promising results.

Equipment that should be carried by a physician who goes to the earthquake region for emergency assistance during the winter season

In February 2023, two major earthquakes in Turkey affected 10 cities. We wanted to share our experience with the equipment that the first responders in the earthquake area should take with them, apart from medical supplies.The equipment required for patient care is as follows; stethoscope, trauma scissors, flashlight, and headlamp (for power outage situation), safety glasses, scrubs (spare), mask, medical gloves, regularly used drugs (such as decongestants, antibiotics, analgesics), battery, hospital ID, notepad, pen. Personal equipment that is not necessary for patient care is as follows; backpack (with name tag), power bank (to keep in touch), list of basic contact numbers, thermos (for tea and coffee), enough ready-made food to last at least three days (dry foods, energy, and protein bars, instant sachet soup, etc.), water bottle, fork, spoon, glass, garbage bag, whistle, work gloves, ear protection, sleeping bag and mat (tent if possible), personal hygiene items (soap, toothbrush, toothpaste, wet wipes, napkins).

Pre-Publication Data Linking in Taxonomy and Biodiversity: The ARPHA and Metotaxa-Metostem Publishing Systems

The traditional way of publishing in PDF makes it difficult to retrospectively convert the legacy literature into data. This presentation will discuss pre-publication tagging as an alternative solution for publishing FAIR (Findable, Accessible, Interoperable, Resuable) biodiversity data. The Metotaxa-Metostem workflow Тhe MetoTaxa project aims to create a new digital production chain for the European Journal of Taxonomy, which enables the pre-publication semantic structuring of text, automatic tagging and semantic enrichment (annotation). The system is based on a single-source publishing model, where the development of an XML file enables technical editors to automatically enrich text and produce multiple digital outputs. This makes it possible to structure generic or domain-specific sections of articles (e.g., Introduction; Material and methods; Taxon names or Мaterial examined). Thanks to the GoldenGate API developed by Plazi, the Text Encoding Intiative (TEI) XML source file is automatically annotated with JATS TaxPub tags: taxon names are labeled and each authorship can be checked via Catalogue of Life, each element of the material examined is parsed thanks to the preformatting of the text (Chester et al. 2019). Also, each bibliographic reference is parsed into Journal Article Tag Suite (JATS) elements (author names, title, journal, etc.), which automatically links references to their in-text citations. Pre-publication tagging will be carried out by the technical editors and then checked by the authors before publication, and will be sent to databases such as Global Biodiversity Information Facility (GBIF) or Biodiversity Literature Repository (BLR) as soon as the article is published. We will also briefly present MetoStem, which offers a technical solution for the digital transformation of monographs, and particularly floras. The tools and methods developed by this project will enable advanced publication of interoperable structured text and data. ARPHA Publishing Platform Launched in 2010 by Pensoft, ARPHA (Penev et al. 2010) is the first ever scholarly publishing platform to support pre-publication semantic tags and enhancements to entities (e.g., taxon treatments, taxon names, sequences) in the JATS TaxPub XML format developed by Plazi, which are then embedded into the HTML version of the article. Having proved advantageous for biodiversity scientists, Pensoft’s pre-publication tagging workflow has since been adopted by over 30 biodiversity journals hosted on ARPHA. The second development stage of ARPHA was marked by the launch of ARPHA Writing Tool (AWT)*1 and Biodiversity Data Journal in 2013. AWT supports import of Darwin Core structured data from GBIF, Barcode of Life Data Systems (BOLD) and Integrated Digitized Biocollections (iDigBio) directly into manuscripts. These are also exported automatically as published material citations to GBIF. AWT also provides several other unique tools encompassed within the ARPHA-BioDiv toolbox (Penev et al. 2017). Currently, AWT is being redeveloped into a standalone, freely accessible installation (AWT 2.0), based on a micro-service architecture. It enables new semantic enhancements during the authoring process, which can be confirmed by the authors before manuscript submission. Such enhancements include the in-text citations context by CiTO ontology; automated tagging of taxon names and linking to their identifiers in authoritative sources; annotator tool; nanopublication module; automated search and import of references; treatment citation module; export/import to/from JATS TaxPub; and internal communication tool for contributors.

Enhancing professionalism of first-year medical students through early nursing practice training and attitude education

Purpose: This study aimed to clarify the attitudes, behaviors, and learning experiences of first-year medical students participating in a nursing practice training aimed at enhancing their professionalism.Methods: A questionnaire survey was conducted among first-year medical students after their nursing practical training to understand their learning experiences. Descriptive statistics was performed for each questionnaire item. For free-text responses, descriptions were grouped by input data with similar content and meaning, and analyzed qualitatively. Others’ evaluation and self-evaluation were analyzed quantitatively.Results: Most students were actively engaged and fulfilled in the training. The free comments generated these categories: “nursing care,” “roles of nurses,” “patient impressions,” “multidisciplinary cooperation,” “communication,” and “what is required of physicians. On the first day, all items evaluated had higher mean scores in the others’ evaluation than in the self-evaluation. On the second day, for “maintains standards of personal appearance (including uniform, hair, and name tag),” the others’ evaluation means were higher than the self-evaluation means. T-tests showed a significant difference in “maintains standards of personal appearance (including uniform, hair, and name tag)” (t=-2.103, degrees of freedom [df]=71.104, p&lt;0.05) and “attends to patients with a polite manner” (t=-2.087, df=74, p&lt;0.05) for both the high and low groups.Conclusion: Greeting, appearance, communication skills, and attitude were found to be the important bases of attitude education in the nursing training ideally involving multidisciplinary professionals. The medical students were able to grasp what is required of doctors and objectively view such position from the viewpoints of nurses and patients.

The Interpretive Interview. An Interview Form Centring on Research Participants’ Constructions

One might be tempted to ask: Is discussing qualitative interviewing with yet another name tag on it once again old wine in a new bottle? In this contribution, I argue that describing our interviewing and data analysis still needs some reflection: It is a fine cuvée (ending the vinophile metaphor here) that you might want to get a taste of herewith: Discussing qualitative interviewing deepens the understanding of the kind of interviewing Kathy Charmaz proposed while building explicitly on its traditions within social scientific hermeneutics. Charmaz was kind enough to refer to my work – so it is my honour to proceed with my thinking following our time together in Vienna. In this paper, I will focus on the way of doing qualitative interviews that in the end leads to a data quality that, to the largest extent possible, fits our exigencies in interpretively oriented research. Put in a nutshell, we are seeking an interview form that puts the interview partners at the core of the communicative act and in the drivers’ seats of the interview situation. We thus end up with interview material that is rich in stories told and connections made at the free choice of the participants. This stands in contrast to the idea that qualitative interviews should always be based on interview guidelines. The latter can be clearly differentiated from the interpretive interview style proposed here – and is per se not a bad choice as long as it fits the overall methodology and the ensuing research interests.

Perioperative misgendering experiences in patients undergoing gender-affirming surgery: a call for a gender-inclusive healthcare environment.

Transgender individuals have long experienced discrimination and exclusion from medicine. Misgendering occurs when an individual is referred to using a gender or address incongruent with their identity. We evaluated the incidence of misgendering throughout the perioperative experience for patients undergoing gender-affirming surgery (GAS). Patients diagnosed with gender dysphoria who previously received GAS by the senior author were contacted to complete an IRB-approved survey to evaluate instances of misgendering while in the hospital for GAS. Study results were summarized using descriptive statistics. Of 471 patients contacted, 182 completed the survey (38.6%). The most cited gender identity was transfemale (28.0%). Most patients reported respect for their gender identity (60.4%) and name (76.8%) during their perioperative experience. Twenty-two percent cited triggering experiences, and 15.4% reported interactions with healthcare employees causing them to reach out to a support system. Misgendering most commonly included incorrect use of patients' preferred names and/or pronouns (n = 50, 86.2%), most commonly at surgical check-in (n = 10, 45.5%). Recommendations to improve feelings of gender congruence during patients' stay included updated names and gender identities in electronic medical records (80.8%), and names and pronouns listed on curtains and doors (52.3%) and name tags (51.5%). Until now, the exact incidence of misgendering among patients seeking GAS have not been well established. Despite high levels of satisfaction, a large proportion still reported serious instances of misgendering. Improvements must be made to the perioperative experience to reduce misgendering and provide support and comfort during the sensitive period surrounding patients' gender transition.Level of evidence: Not gradable. The online version contains supplementary material available at 10.1007/s00238-022-02040-2.

Neural Attention Model for Abstractive Text Summarization Using Linguistic Feature Space

Summarization generates a brief and concise summary which portrays the main idea of the source text. There are two forms of summarization: abstractive and extractive. Extractive summarization chooses important sentences from the text to form a summary whereas abstractive summarization paraphrase using advanced and nearer-to human explanation by adding novel words or phrases. For a human annotator, producing summary of a document is time consuming and expensive because it requires going through the long document and composing a short summary. An automatic feature-rich model for text summarization is proposed that can reduce the amount of labor and produce a quick summary by using both extractive and abstractive approach. A feature-rich extractor highlights the important sentences in the text and linguistic characteristics are used to enhance results. The extracted summary is then fed to an abstracter to further provide information using features such as named entity tags, part of speech tags and term weights. Furthermore, a loss function is introduced to normalize the inconsistency between word-level and sentence-level attentions. The proposed two-staged network achieved a ROUGE score of 37.76% on the benchmark CNN/DailyMail dataset, outperforming the earlier work. Human evaluation is also conducted to measure the comprehensiveness, conciseness and informativeness of the generated summary.

GE-Blender: Graph Based Knowledge Enhancement for Blender

In spite of the considerable accomplishments in open-domain dialogue generation, the presence of unseen entities can substantially impact the task, resulting in a performance decline in model-driven dialogue generation. While previous research has utilized retrieved knowledge of seen entities to augment model representation, a comprehensive exploration of unseen entities, including their potential co-occurrence and semantic associations within the entity category, remains largely uncharted. In this study, we propose an approach to address this challenge. We construct a graph by extracting entity nodes, enhancing the contextual representation of unseen entities by leveraging the 1-hop surrounding nodes of associated entities. Furthermore, we introduce a named entity tag prediction task to address the issue of unseen entities not present in the constructed graph. We conduct our experiments on an open dataset Wizard of Wikipedia and the empirical results indicate that our approach outperforms the state-of-the-art approaches on Wizard of Wikipedia.

Named Entity Recognition For Quranic Text Using Rule Based Approaches

The variety and difference between domains for textual data require customization in the Natural Language Processing component especially in Named Entity Recognition where different domains contain several types of entities. The current NER model is deemed not fit to accurately extract entities from Quranic text due to its unique content. This paper describes the building of a rule-based Named Entity Recognition method to extract the entities that exist in the English translation to the meaning of the Quranic text and its performance evaluation. Named entity tagging, a common task in-text annotation, in which entities (nouns) in the unstructured text are identified and assigned a class. A few rules are built to extract several types of entities such as the name of prophets and people, creation, location, time, and the various names of God. The rules are built mainly using regular expressions and gazetteers. The rules that have been built result in high precision and recall as well as a satisfactory F-score of over 90%. The results from this experiment can be used as annotation in building a machine learning model to extract entities from the same type of domain specifically on the Quranic text or generally in the Islamic domain text.

NAMED ENTITY RECOGNITION FOR QURANIC TEXT USING RULE BASED APPROACHES

The variety and difference between domains for textual data require customization in the Natural Language Processing component especially in Named Entity Recognition where different domains contain several types of entities. The current NER model is deemed not fit to accurately extract entities from Quranic text due to its unique content. This paper describes the building of a rule-based Named Entity Recognition method to extract the entities that exist in the English translation to the meaning of the Quranic text and its performance evaluation. Named entity tagging, a common task in-text annotation, in which entities (nouns) in the unstructured text are identified and assigned a class. A few rules are built to extract several types of entities such as the name of prophets and people, creation, location, time, and the various names of God. The rules are built mainly using regular expressions and gazetteers. The rules that have been built result in high precision and recall as well as a satisfactory F-score of over 90%. The results from this experiment can be used as annotation in building a machine learning model to extract entities from the same type of domain specifically on the Quranic text or generally in the Islamic domain text.

Feasibility and Utility of Wearable Bluetooth and RFID Sensors to Measure Care Interactions

Abstract Clinical care interactions influence important health outcomes in older adults such as nosocomial infections, falls, and care satisfaction. However, traditional measurements of interactions are often time-consuming, costly, biased, or they interfere with normal clinical care. Wearable sensors measure interpersonal contact with a high degree of spatial and temporal detail and accuracy when applied to examining the spread of infection. This study aims to test the feasibility of implementing two types of commercially available wearable sensors to collect spatial and temporal data for measuring care interactions in health care settings. EMBC02 (Bluetooth) and OpenBeacon (RFID) sensors were tested in a simulation laboratory. Five nursing students wore the sensors along with name tags and enacted a scenario of a fallen nursing home resident. Sensor data were plotted in Python and compared with video recordings of the simulated care interaction to determine sensor usability, accuracy, and precision. EMBC02 and OpenBeacon detected multiple wearers and provided spatial and temporal data. OpenBeacon showed better usability and validity than EMBC02 for using proximity data collected by sensors to infer care interactions. Both OpenBeacon and EMCB02 showed some limitations in accuracy and precision, such as increased data missingness due to idling function and high data noise. Bluetooth and RFID sensors measure different aspects of proximity. OpenBeacon outperformed EMBC02 for measuring care interactions. Combining Bluetooth with RFID may provide richer information for measuring and understanding care interactions. Simulation laboratories can be leveraged to test health technology before use in clinical research.

Uncomfortable yet necessary: The impact of PPE on communication in emergency medicine.

The efficacy of pre-hospital emergency services is heavily dependent on the effective communication of care providers. This effective communication occurs between providers as part of a team and also among providers interacting with family members and patients. The COVID-19 pandemic introduced a number of communication challenges to emergency care, which are primarily linked to the increased use of personal protective equipment (PPE). We sought to analyze the impacts of the COVID-19 pandemic on emergency medical service (EMS) workers and pre-hospital care delivery. We conducted focus groups and one-on-one interviews with fire-based EMS first responders between September 2021 and 2022. Interviews included questions about job-related stress, EMS skills, work experiences and changes during COVID-19. Interviews were recorded, independently dual coded and analyzed for themes. Two hundred twenty-three first responders participated in 40 focus groups and 40 lead paramedics participated in individual interviews. We found that additional use of PPE was reported to have significantly impaired efficiency and perceptions of quality of care-among EMS team members and also between EMS workers and patients. EMS personnels also experienced on-scene hostility on arrival (from both families and other agencies). Extensive use of PPE muffles voices, obscures facial expressions and can cause team members to have difficulty recognizing and communicating with one another and can be a barrier to showing empathy and connecting with patients. Creative solutions such as putting a hand on someone's shoulder, wearing name tags on suits and explaining rationale for perceived delays were mentioned as methods to transcend these barriers. The appearance of providers in heavy PPE can be unsettling and create barriers to human connection, particularly for pediatric patients. Human connection is an important element of health-care delivery and healing. These findings shed light on new skills that are needed to initiate and maintain human connection in these times of PPE use, especially full-body PPE. Awareness of the communication and empathy barriers posed by PPE is the first step to improving provider-patient interactions in pre-hospital EMS. Additionally, 'communication-friendly' adaptations of PPE equipment may be an important area for future research and development in manufacturing and the health-care industry.

Multisensory encoding of names via name tags facilitates remembering

AbstractAssociating names to faces can be challenging, in part because this task lacks an inherent semantic relationship between a face and name. The current study seeks to understand whether bolstering names with cross‐modal cues—specifically, name tags—may aid memory for face and name pairings. In a series of five experiments, we investigated whether the presentation of congruent vocalized and written names at encoding might benefit subsequent cued recall and recognition memory tasks. The results showed that participants, cued with a picture of a face, were more likely to recall the associated name when those names were encoded with a name tag (a congruent visual cue) compared to when no supporting cross‐modal cue was available. The findings were consistent with a benefit of multisensory encoding, above any effect from the availability of independent unisensory traces, extending previous findings of multisensory learning and memory benefits to a naturalistic associative memory task.

Addressing Implicit Bias to Acknowledge the Experience of Under-represented in Medicine Colleagues and Improve Patient Care.

This article recounts episodes of implicit bias I have experienced as an emergency physician and explores how we can move in a better direction to benefit everyone. I was a toddler when my family moved to the US from Jamaica. A few years after that, I announced that I was going to be a doctor. I made this decision based on zero data. At the time, I had no idea that only 1/3 of 1% of the US population are physicians. And of that number only 2% are Black women. I walk into every patient room the same way, wearing blue scrubs &amp; a long white coat with my name embroidered on it - visibly rubbing some hand sanitizer in so they know I care about spreading germs, a stethoscope hangs on a holster from my scrub pants and a name tag is clipped to my chest with my photo with a second bright orange tag with the word DOCTOR in all caps. "Hello, I'm Dr. Ennis, I'm the emergency physician. What brings you here today?" I greet everyone in the room &amp; shake hands if offered and then I pause. Deliberately. I pause because the first and only thing they saw when I walked in the room was a black woman with dreads. Despite the costume, the optics I present do not say doctor. Addressing racism as it impacts the health of our patients and the sense of belonging for all our colleagues demands true effort &amp; focus.

Sounds of Accompaniment

Sounds of Accompaniment