Familiar Tools Research Articles

Барьеры телемедицины и пути их преодоления.

The ongoing discussion of telemedicine suggests that there are barriers to the widespread adoption of telemedicine technologies in clinical practice. The article is the first to classify the barriers of the introduction of telemedicine technologies into practice. There are 4 main barriers: technological, legal, economic and methodological. At the end of the description of each barrier, ways to overcome them are given. The technological barrier includes: the inconvenience of using existing tools, poor integration of telemedicine platforms with existing medical information systems (MIS), Poor standardization of information exchange protocols between sources (devices), information systems from different manufacturers, a small amount and low quality of digitized information about the state of human health and others. In the legal barrier, it is prohibited to make a diagnosis and prescribe treatment when providing medical care using telemedicine technologies, and also there are requirements for the workplace of a doctor providing TM-consultation. Financial barriers are represented by the difficulties of financing telemedicine - the lack of compulsory medical insurance tariffs, the erroneous opinion that telemedicine should reduce healthcare costs or does not require separate financing at all. The lack of methodological support for telemedicine - clinical studies, publications, methodological and clinical recommendations, training courses and programs on telemedicine for students, leads to a low commitment of doctors to use telemedicine in their work. The process of implementing telemedicine technologies is unavoidable. However, there is no doubt that telemedicine will eventually become a familiar and indispensable tool in the hands of doctors. Sooner or later, even without our active participation, these barriers will be overcome.

Action goals and the praxis network: an fMRI study

The praxis representation network (PRN) of the left cerebral hemisphere is typically linked to the control of functional interactions with familiar tools. Surprisingly, little is known about the PRN engagement in planning and execution of tool-directed actions motivated by non-functional but purposeful action goals. Here we used functional neuroimaging to perform both univariate and multi-voxel pattern analyses (MVPA) in 20 right-handed participants who planned and later executed, with their dominant and non-dominant hands, disparate grasps of tools for different goals, including: (1) planning simple vs. demanding functional grasps of conveniently vs. inconveniently oriented tools with an intention to immediately use them, (2) planning simple—but non-functional—grasps of inconveniently oriented tools with a goal to pass them to a different person, (3) planning reaching movements directed at such tools with an intention to move/push them with the back of the hand, and (4) pantomimed execution of the earlier planned tasks. While PRN contributed to the studied interactions with tools, the engagement of its critical nodes, and/or complementary right hemisphere processing, was differently modulated by task type. E.g., planning non-functional/structural grasp-to-pass movements of inconveniently oriented tools, regardless of the hand, invoked the left parietal and prefrontal nodes significantly more than simple, non-demanding functional grasps. MVPA corroborated decoding capabilities of critical PRN areas and some of their right hemisphere counterparts. Our findings shed new lights on how performance of disparate action goals influences the extraction of object affordances, and how or to what extent it modulates the neural activity within the parieto-frontal brain networks.

Impaired Affordance Perception as the Basis of Tool Use Deficiency in Alzheimer's Disease.

The present study investigated whether defective affordance perception capacity underpins tool use deficits in patients with Alzheimer’s disease (AD). An affordance, a concept James Gibson introduced, scales environmental objects to an animal’s action capabilities, thus offering opportunities for action. Each man-made artifact carries both a primary affordance (its designed function) and secondary affordances. In Experiment 1, participants identified secondary affordances of objects as a measure of their ability to identify alternative uses of familiar tools. A single response Go/No-Go task was administered to 4 groups: AD, mild cognitive impairment (MCI), Parkinson’s disease (PD), and elderly controls (EC). Groups were matched for age and years of education. The AD group performed poorest, followed by MCI, and PD and EC. EC and PD groups’ results failed to reach statistical significance, and the AD group performed at chance. In Experiment 2, participants judged the physical properties of the same objects used in Experiment 1. Even AD patients performed reliably, ruling out a visual processing deficit as the basis for their poor performance in Experiment 1. Results suggest that degraded affordance detection capacity can differentiate AD from normal aging and other neurodegenerative disorders and could be an affordable marker for AD, even in the early stages of AD.

Bioelectricity Buzz.

Bioelectricity Buzz.

Venous cannula occlusion during cardiopulmonary bypass recognized by ultrasonography of the internal jugular vein

BackgroundOcclusion or malposition of the venous cannula during cardiopulmonary bypass (CPB) increases central venous pressure (CVP). When high CVP is measured, we need to determine if it is actually high or if it is measured due to catheter occlusion or technical problems with the measurement.Case presentationWe experienced a case of excessively high CVP due to malposition of the venous cannula during CPB. A 78-year-old woman underwent an aortic arch replacement for acute aortic dissection. During CPB, CVP increased up to 78 mmHg, and the time above 50 mmHg was 48 min. In this case, ultrasonography of the internal jugular vein (IJV) was useful to confirm high CVP.ConclusionsUltrasonography is now a familiar diagnostic tool and can be used at any time. We should consider ultrasonography as the first choice for diagnosing the cause of high CVP during CPB.

Machine Reading at Scale: A Search Engine for Scientific and Academic Research

The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day lives, with familiar tools such as search engines carving a path through this unknown. In the research world, articles on a myriad of topics with distinct complexity levels are published daily, requiring specialized tools to facilitate the access and assessment of the information within. Recent endeavors in artificial intelligence, and in natural language processing in particular, can be seen as potential solutions for breaking information overload and provide enhanced search mechanisms by means of advanced algorithms. As the advent of transformer-based language models contributed to a more comprehensive analysis of both text-encoded intents and true document semantic meaning, there is simultaneously a need for additional computational resources. Information retrieval methods can act as low-complexity, yet reliable, filters to feed heavier algorithms, thus reducing computational requirements substantially. In this work, a new search engine is proposed, addressing machine reading at scale in the context of scientific and academic research. It combines state-of-the-art algorithms for information retrieval and reading comprehension tasks to extract meaningful answers from a corpus of scientific documents. The solution is then tested on two current and relevant topics, cybersecurity and energy, proving that the system is able to perform under distinct knowledge domains while achieving competent performance.

Assessment of mathematical creative thinking: A systematic review

With the increasing attention to mathematical creative thinking (MCT) in mathematics education, there has been a concomitant rise in the need to and interest in investigating how to assess MCT skills. Thus, a systematic review was conducted on how MCT has been assessed in the literature. We reviewed 70 journal articles to analyze specific MCT assessments from four perspectives: educational context, assessment of the familiar mathematics context, measurement tools, and reliability and validity of evidence. We found that (a) additional MCT measurements tools are necessary for secondary and high school levels; (b) the most familiar mathematics context for assessing MCT focuses Aon the curriculum of students according to the class level; (c) tools for assessing MCT often used open-ended questions, interview, multiple-choice, questionnaire, open-ended based on ethnomathematics, and Torrance Test of Creative Thinking (TTCT); and (d) the validity and reliability of the evidence of the MCT assessment tool should be collected and reported in further research. This systematic review identifies research gaps and topics for further research to conceptualize and assess MCT skills. The findings are expected to benefit researchers and teachers, to help them decide the best measurement tool to use in MCT assessment.

FMEA-AI: AI fairness impact assessment using failure mode and effects analysis

Recently, there has been a growing demand to address failures in the fairness of artificial intelligence (AI) systems. Current techniques for improving fairness in AI systems are focused on broad changes to the norms, procedures and algorithms used by companies that implement those systems. However, some organizations may require detailed methods to identify which user groups are disproportionately impacted by failures in specific components of their systems. Failure mode and effects analysis (FMEA) is a popular safety engineering method and is proposed here as a vehicle to support the conducting of “AI fairness impact assessments” in organizations. An extension to FMEA called “FMEA-AI” is proposed as a modification to a familiar tool for engineers and manufacturers that can integrate moral sensitivity and ethical considerations into a company’s existing design process. Whereas current impact assessments focus on helping regulators identify an aggregate risk level for an entire AI system, FMEA-AI helps companies identify safety and fairness risk in multiple failure modes of an AI system. It also explicitly identifies user groups and considers an objective definition of fairness as proportional satisfaction of claims in calculating likelihood and severity of fairness-related failures. This proposed method can help industry analysts adapt a widely known safety engineering method to incorporate AI fairness considerations, promote moral sensitivity and overcome resistance to change.

STRATISFIMAL LAYOUT: A modular optimization model for laying out layered node-link network visualizations

Node-link visualizations are a familiar and powerful tool for displaying the relationships in a network. The readability of these visualizations highly depends on the spatial layout used for the nodes. In this paper, we focus on computing layered layouts, in which nodes are aligned on a set of parallel axes to better expose hierarchical or sequential relationships. Heuristic-based layouts are widely used as they scale well to larger networks and usually create readable, albeit sub-optimal, visualizations. We instead use a layout optimization model that prioritizes optimality - as compared to scalability - because an optimal solution not only represents the best attainable result, but can also serve as a baseline to evaluate the effectiveness of layout heuristics. We take an important step towards powerful and flexible network visualization by proposing Stratisfimal Layout, a modular integer-linear-programming formulation that can consider several important readability criteria simultaneously - crossing reduction, edge bendiness, and nested and multi-layer groups. The layout can be adapted to diverse use cases through its modularity. Individual features can be enabled and customized depending on the application. We provide open-source and documented implementations of the layout, both for web-based and desktop visualizations. As a proof-of-concept, we apply it to the problem of visualizing complicated SQL queries, which have features that we believe cannot be addressed by existing layout optimization models. We also include a benchmark network generator and the results of an empirical evaluation to assess the performance trade-offs of our design choices. A full version of this paper with all appendices, data, and source code is available at osf.io/qdyt9 with live examples at https://visdunneright.github.io/stratisfimal/.

Artificial Intelligence Based Optimal Functional Link Neural Network for Financial Data Science

In present digital era, data science techniques exploit artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to have an impact and develop their businesses. Data science integrates the conventions of econometrics with the technological elements of data science. It make use of machine learning (ML), predictive and prescriptive analytics to effectively understand financial data and solve related problems. Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations. At the same time, it is needed to develop an effective tool which can assist small to medium sized enterprises to forecast business failure as well as financial crisis. AI becomes a familiar tool for several businesses due to the fact that it concentrates on the design of intelligent decision making tools to solve particular real time problems. With this motivation, this paper presents a new AI based optimal functional link neural network (FLNN) based financial crisis prediction (FCP) model for SMEs. The proposed model involves preprocessing, feature selection, classification, and parameter tuning. At the initial stage, the financial data of the enterprises are collected and are preprocessed to enhance the quality of the data. Besides, a novel chaotic grasshopper optimization algorithm (CGOA) based feature selection technique is applied for the optimal selection of features. Moreover, functional link neural network (FLNN) model is employed for the classification of the feature reduced data. Finally, the efficiency of the FLNN model can be improvised by the use of cat swarm optimizer (CSO) algorithm. A detailed experimental validation process takes place on Polish dataset to ensure the performance of the presented model. The experimental studies demonstrated that the CGOA-FLNN-CSO model has accomplished maximum prediction accuracy of 98.830%, 92.100%, and 95.220% on the applied Polish dataset Year I-III respectively.

Physical understanding in neurodegenerative diseases

ABSTRACT This quantitative review gives an overview of physical understanding (i.e., the ability to represent and use the laws of physics to interact with the physical world) impairments in Alzheimer’s disease (AD), semantic dementia (SD), and corticobasal syndrome (CBS), as assessed mainly with mechanical problem-solving and tool use tests. This review shows that: (1) SD patients have apraxia of tool use because of semantic tool knowledge deficits, but normal performance in tests of physical understanding; (2) AD and CBS patients show impaired performance in mechanical problem-solving tests, probably not because of intrinsic deficits of physical understanding, but rather because of additional cognitive (AD) or motor impairments (CBS); (3) As a result, the performance in mechanical problem-solving tests is not a good predictor of familiar tool use in dementia; (4) Actual deficits of physical understanding are probably observed only in late stages of neurodegenerative diseases, and associated with functional loss.

100 years after Liepmann–Lesion correlates of diminished selection and application of familiar versus novel tools

100 years ago, Liepmann highlighted the role of left ventro-dorsal lesions for impairments in conceptual (rather ventral) and motor (more dorsal) related aspects of apraxia. Many studies thereafter attributed to an extended left fronto-temporo-parietal network. Yet, to date there are only few studies that looked at apraxic performance in the selection and application of familiar versus novel tools.In the current study we applied modern voxel-based lesion-symptom mapping (VLSM) to analyze neural correlates of impaired selection and application of familiar versus novel tools. 58 left (LBD) and 51 right brain damaged (RBD) stroke patients participated in the Novel Tools Test (NTT) and the Familiar Tools Test (FTT) of the Diagnostic Instrument for Limb Apraxia (DILA-S). We further assessed performance in control tasks, namely semantic knowledge (BOSU), visuo-spatial working memory (Corsi Block Tapping) and meaningless imitation of gestures (IML).Impaired tool use was most pronounced after LBD. Our VLSM results in the LBD group suggested that selection- versus application-related aspects of praxis and semantics of familiar versus novel tool use can be behaviorally and neuro-anatomically differentiated. For impairments in familiar tool tasks, the major focus of lesion maps was rather ventral while deficiencies in novel tool tasks went along with rather dorsal lesions. Affected selection processes were linked to rather anterior lesions, while impacted application processes went along with rather posterior lesion maps. In our study, particular tool selection processes were rather specific for familiar versus novel tools. Foci for lesion overlaps of experimental and control tasks were noticed ventrally for semantic knowledge and FTT, in fronto-parietal regions for working memory and NTT, and ventro-dorsally for imitation of meaningless gestures and the application of NTT and FTT.We visualized our current interpretation within a neuroanatomical model for apraxia of tool use.

66.1 PREPARATION BEFORE PRESCRIBING BUPRENORPHINE: WHAT DO I NEED TO DO?

Clinician questions and concerns about prescribing buprenorphine for opioid use disorder in adolescents, especially minors, prevent many from actually taking the leap to accepting patients, even after finishing the federally mandated buprenorphine waiver training. This overview will review common clinical questions and answers before starting treatment to improve feelings of readiness. A vignette of a typical treatment course will be used to give an overview of what buprenorphine treatment looks like before and during long-term treatment, with emphasis on common issues that arise for prescribers and how adequate preparation ahead of time can make dealing with these situations much easier. The scientific literature (and gaps within) about patient and clinician experiences and published guidelines will be reviewed. Psychiatrists can make slight modifications to their current practice to accommodate requirements for prescribing buprenorphine. Release of health information forms currently in use can be modified to allow for discussion of opioid use disorder treatment with parents. Labs used to check lithium levels or monitor antipsychotic medications can also process drug tests. Networks for referrals to a higher level of care can be cultivated just as is done for mental health needs. Treatment agreements can facilitate thorough discussion of risks and benefits and clearly outline clinician and patient responsibilities and improve the quality of treatment. Child and adolescent psychiatrists are well positioned to use buprenorphine to treat adolescents with opioid use disorder using many familiar clinical tools. Preparing for common problems ahead of time improves clinician confidence and willingness to start treatment.

Penerapan Metode Preference Rangking Organization Methof for Encrichment Evaluation (PROMETHEE II) Dalam Penyeleksian Penyiar Radio

One of the media that presents information quickly and is supported by high technology, one of which is radio. Radio as the oldest and most familiar communication media tool in the world continues to survive amidst many new media such as the internet. Radio up to now is still believed to be an information and communication media tool favored by many people because it has an important role in disseminating information about information about education, entertainment or other advertisements and events. To convey this information needed Human Resources (HR) is needed, namely broadcasters. In selecting the radio broadcaster must meet the requirements or criteria, so that they are chosen to be broadcasters. One solution to these problems is right by using a Decision Support System (SPK). Decision Support System (SPK) can help radio stations in making decisions on the selection of good radio broadcasters and increasing the efficiency of the decision. The promethee II method is one of the Multi Criteria Decision Making (MCDM) methods which means that it determines or sequences in a multicriteria analysis, this method is known because the concept is efficient and simple, in addition to solving problems related to multicriteria, others.

Children's planning of efficient tool use in a social context.

Efficient joint action requires that we anticipate situational demands both regarding our own and another person's perspective, and adapt our actions accordingly. Accordingly, when handing over a tool somebody else, it is advantageous to anticipate our future hand orientation (motor imagery), as well as the future orientation of the tool (mental rotation) relative to the other person, in order to make the transfer as smooth and efficient as possible. Furthermore, familiarity with specific tools might facilitate planning. We tested thirty-two 5.5- to 7-year-old children on a tool transfer task, asking if they consider another person's comfort when handing over different tools, and whether tool familiarity, motor imagery, and mental rotation are related to their grip choices. We compared the children's performance to that of an adult control group. Besides a rather low performance on the transfer task, we found differences in children's consideration of another person's comfort related to the specific tools they interacted with. Specifically, the unfamiliar tool (a bar) was transferred more efficiently than the familiar tools (hammer/brush). In addition, the results suggest a relation between children's consideration of another person's comfort and their mental rotation score, but no relation with their motor imagery score.

A new approach to the complex Helmholtz equation with applications to diffusion wave fields, impedance spectroscopy and unsteady Stokes flow

Abstract A new transform pair representing solutions to the complex Helmholtz equation in a convex 2D polygon is derived using the theory of Bessel’s functions and Green’s second identity. The derivation is a direct extension of that given by Crowdy (2015, A transform method for Laplace’s equation in multiply connected circular domains. IMA J. Appl. Math., 80, 1902–1931) for ‘Fourier–Mellin transform’ pairs associated with Laplace’s equation in various domain geometries. It is shown how the new transform pair fits into the collection of ideas known as the Fokas transform where the key step in solving any given boundary value problem is the analysis of a global relation. Here we contextualize those global relations from the point of view of ‘reciprocal theorems’, which are familiar tools in the study of the effective properties of physical systems. A survey of the many uses of this new transform approach to the complex Helmholtz equation in applications is given. This includes calculation of effective impedance in electrochemical impedance spectroscopy and in other spectroscopy methods in diffusion wave field theory, application to the 3$\omega $ method for measuring thermal conductivity and to unsteady Stokes flow. A theoretical connection between this analysis of the global relations and Lorentz reciprocity in mathematical physics is also pointed out.

Paraphrase, categories, and ontology

AbstractThe method of paraphrasing away apparent ontological commitments is a familiar tool for trimming one's ontology. Even so, I argue that aiming to avoid commitment via paraphrase is unjustified. The reason is the standard motivations for paraphrase rest on implicit yet faulty principles regarding ontological categories and categorization‐ or so I argue. These results also provide indirect support for a permissivist approach to ontology.

Дистанционные медицинские консультации пациентов: что изменилось в России за 20 лет

Introduction. 2020 has sparked explosive growth in telemedicine, especially remote patient consultation and remote patient monitoring techniques. Materials and methods. The authors analyzed data from 169 articles from Pubmed and 47 articles from Elibrary.ru, 117 analytical reviews of Internet resources, Federal Laws on the keywords «remote patient consultation», «mobile applications for patients», «telemedicine», «pandemic». For this publication, 49 publications were selected, as well as the authors' own opinions and experiences. Results. Today remote consulting in Russia is used in the case of an initial consultation – a preventive appointment, referral to clinics, obtaining a second medical opinion with the possibility of prescribing additional examinations. Over the past 20 years, there has been an active growth in the development of remote consultations, long-term monitoring of patients' health, the introduction of mobile applications for monitoring vital signs of the body. An important point is the legal regulation of the provisions on the use of telemedicine technologies, however, it remains imperfect and requires improvement. The COVID pandemic has become a driver for the development of TM technologies in the state healthcare system. Conclusions. TM has transformed from conventional consultations to long-term (continuous) monitoring of health status using medical devices, which can be considered one of the most promising new areas with clinical efficacy. TM technologies are gradually becoming a familiar tool in clinical practice and may become routine for doctors and patients even after the end of the pandemic.

Segregation Surfaces

Summary Social scientists have developed dozens of different ways to quantify urban segregation with numerical statistics. Behind the scenes, some of these measurements are defined using multivariable functions that model the distribution of various groups in a geographical region. Using Bayes’ theorem and kernel density estimation, we describe how to summarize population data in terms of smooth, two-dimensional surfaces. These surfaces give us ways of identifying neighborhood boundaries and visualizing segregation patterns. We also propose two new segregation measures using some familiar tools from third-semester calculus. Applications to United States census data are included.

What was it like to be an ESL teacher in 2020? Reflections from the prek-12 community

Suddenly, with the advent of COVID-19, our familiar teaching tools disappeared. How, in a two-dimensional world, were teachers to connect with students? This is a question we have all been asking ourselves since last spring — and when we began to discuss this forum, it was the question we posed to our community. We asked student teachers, cooperating teachers, and student-teacher supervisors to reflect on a single moment from this past year. We hoped to document — and to share — a few moments from the actual experience being an ESL teacher during the 2020 school year.