5,993 research outputs found
PROSEDUR PEMERIKSAAN RADIOGRAFI CALCANEUS PADA KLINIS SPUR DI INSTALASI RADIOLOGI RS BHAYANGKARA PROF. AWALOEDIN DJAMIN SEMARANG
No full textProsedur pemeriksaan radiografi calcaneus pada klinis spur di Instalasi Radiologi RS Bhayangkara Prof. Awaloedin Djamin Semarang hanya dilakukan dengan proyeksi mediolateral perbandingan. Hal tersebut berbeda dengan literatur yang menggunakan 2 proyeksi, yaitu axial (plantodorsal) dan lateral (mediolateral). Penelitian ini bertujuan mengetahui prosedur pemeriksaan radiografi calcaneus pada klinis spur, mengetahui alasan hanya menggunakan proyeksi mediolateral perbandingan, dan mengetahui informasi diagnostik yang didapatkan pada proyeksi mediolateral perbandingan dalam mendiagnosa spur. Jenis penelitian ini kualitatif dengan pendekatan studi kasus. Waktu penelitian pada Februari-April 2022. Penelitian dilakukan dengan cara observasi, wawancara dengan radiografer, radiolog, dokter pengirim dan pasien. Data observasi diolah dan dianalisis menggunakan koding terbuka, data hasil wawancara diolah dan dianalisis serta disajikan dalam bentuk kuotasi sehingga dapat ditarik kesimpulan. Hasil penelitian menunjukkan bahwa pemeriksaan radiografi calcaneus klinis spur di Instalasi Radiologi RS Bhayangkara Prof. Awaloedin Djamin Semarang hanya menggunakan proyeksi mediolateral perbandingan, persiapan pasien melepas alas kaki dan benda disekitar obyek, pasien duduk pada meja pemeriksaan dengan kedua knee pasien difleksikan, kedua calcaneus menempel pada pertengahan IR ukuran 24x30cm, beri softbag pada kedua knee, arahkan sinar vertikal tegak lurus, FFD 100 cm dengan titik bidik pada pertengahan IR diantara kedua calcaneus, faktor eksposi 57 kV 6.4 mAs menggunakan modalitas pesawat sinar-x konvensional. Alasan hanya menggunakan proyeksi mediolateral perbandingan yaitu keterbatasan sistem BPJS pasien rawat jalan hanya sekali foto dalam sehari serta untuk membandingkan kedua calcaneus. Proyeksi mediolateral perbandingan pada pemeriksaan radiografi calcaneus spur dinilai dapat menampakkan kelainan spur dan anatomi calcaneus seperti navicular, talonavicular joint, talus, talocalcaneal joint, tibiotalar joint dan calcaneus
astromatt42/digb_sfgs: Release for 10.21203/rs.3.rs-106679/v1
No full textThis release was used to compute the results in https://doi.org/10.21203/rs.3.rs-106679/v1
For any queries please contact the corresponding author
#nowplaying-rs
No full text<p>The nowplaying-rs dataset features context- and content features of listening events. It contains 11.6 million music listening events of 139K users and 346K tracks collected from Twitter. The dataset comes with a rich set of item content features and user context features, as well as timestamps of the listening events. Moreover, some of the user context features imply the cultural origin of the users, and some others - like hashtags - give clues to the emotional state of a user underlying a listening event.</p>
<p>The dataset contains three files:</p>
<ul>
<li>user_track_hashtag_timestamp.csv contains basic information about each listening event. For each listening event, we provide an id, the user_id, track_id, hashtag, created_at </li>
<li>context_content_features.csv: contains all context and content features. For each listening event, we provide the id of the event, user_id, track_id, artist_id, content features regarding the track mentioned in the event (instrumentalness, liveness, speechiness, danceability, valence, loudness, tempo, acousticness, energy, mode, key) and context features regarding the listening event (coordinates (as geoJSON), place (as geoJSON), geo (as geoJSON), tweet_language, created_at, user_lang, time_zone, entities contained in the tweet).</li>
<li>sentiment_values.csv contains sentiment information for hashtags. It contains the hashtag itself and the sentiment values gathered via four different sentiment dictionaries: AFINN, Opinion Lexicon, Sentistrength Lexicon and vader. For each of these dictionaries we list the minimum, maximum, sum and average of all sentiments of the tokens of the hashtag (if available, else we list empty values). However, as most hashtags only consist of a single token, these values are equal in most cases. Please note that the lexica are rather diverse and therefore, are able to resolve very different terms against a score. Hence, the resulting csv is rather sparse. The file contains the following comma-separated values: <hashtag, vader_min, vader_max, vader_sum,vader_avg, afinn_min, afinn_max, afinn_sum, afinn_avg, ol_min, ol_max, ol_sum, ol_avg, ss_min, ss_max, ss_sum, ss_avg >, where we abbreviate all scores gathered over the Opinion Lexicon with the prefix 'ol'. Similarly, 'ss' stands for SentiStrength. </li>
</ul>
<p>Please note that user_track_hashtag_timestamp.csv and context_content_features.csv partly provide the same features. We deliberately chose to do so to be able to provide useable files that do not have to be matched and joined with each other to perform e.g., simple recommendation tasks.</p>
<p>Please also find the training and test-splits for the dataset in this repo. Also, Asmita provides prototypical implementations of a context-aware recommender system based on the dataset at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM.</p>
<p><br>
If you make use of this dataset, please cite the following paper where we describe and experiment with the dataset:</p>
<p>@inproceedings{smc18,<br>
title = {#nowplaying-RS: A New Benchmark Dataset for Building Context-Aware Music Recommender Systems},<br>
author = {Asmita Poddar and Eva Zangerle and Yi-Hsuan Yang},<br>
url = {http://mac.citi.sinica.edu.tw/~yang/pub/poddar18smc.pdf},<br>
year = {2018},<br>
date = {2018-07-04},<br>
booktitle = {Proceedings of the 15th Sound & Music Computing Conference},<br>
address = {Limassol, Cyprus},<br>
note = {code at https://github.com/asmitapoddar/nowplaying-RS-Music-Reco-FM},<br>
tppubtype = {inproceedings}<br>
}</p>
Treatable traits qualifying for nonpharmacological interventions in COPD patients upon first referral to a pulmonologist: the COPD sTRAITosphere
No full textIntroduction: The present study assessed the prevalence of nine treatable traits (TTs) pinpointing nonpharmacological interventions in patients with COPD upon first referral to a pulmonologist, how these TTs co-occurred and whether and to what extent the TTs increased the odds having a severely impaired health status.Methods: Data were collected from a sample of 402 COPD patients. A second sample of 381 patients with COPD was used for validation. Nine TTs were assessed: current smoking status, activity-related dyspnoea, frequent exacerbations <12 months, severe fatigue, depressed mood, poor physical capacity, low physical activity, poor nutritional status and a low level of self-management activation. For each TT the odds ratio (OR) of having a severe health status impairment was calculated. Furthermore, a graphic representation was created, the COPD sTRAITosphere, to visualise TTs prevalence and OR.Results: On average 3.9 +/- 2.0 TTs per patient were observed. These TTs occurred relatively independently of each other and coexisted in 151 unique combinations. A significant positive correlation was found between the number of TTs and Clinical COPD Questionnaire total score (r=0.58; p<0.001). Patients with severe fatigue (OR: 8.8), severe activity-related dyspnoea (OR: 5.8) or depressed mood (OR: 4.2) had the highest likelihood of having a severely impaired health status. The validation sample corroborated these findings.Conclusions: Upon first referral to a pulmonologist, COPD patients show multiple TTs indicating them to several nonpharmacological interventions. These TTs coexist in many different combinations, are relatively independent and increase the likelihood of having a severely impaired health status.We would like to express our gratitude to all pulmonologists, respiratory nurses, pulmonary function technicians and workers of the clinometric department from both Bernhoven and Radboudumc who contributed to the collection of data for this study and for the interesting discussions we had during the process of explaining the results
Development of the ProPal-COPD tool to identify patients with COPD for proactive palliative care
No full textRG Duenk,1 C Verhagen,1 EM Bronkhorst,2 RS Djamin,3 GJ Bosman,4 E Lammers,5 PNR Dekhuijzen,6 KCP Vissers,1 Y Engels,1,* Y Heijdra6,* 1Department of Anesthesiology, Pain and Palliative Medicine, 2Department of Health Evidence, Radboud University Medical Center, Nijmegen, 3Department of Respiratory Medicine, Amphia Hospital, Breda, 4Department of Respiratory Medicine, Slingeland Hospital, Doetinchem, 5Department of Respiratory Medicine, Gelre Hospitals, Zutphen, 6Department of Pulmonary Diseases, Radboud University Medical Center, Nijmegen, the Netherlands *These authors contributed equally to this work Background: Our objective was to develop a tool to identify patients with COPD for proactive palliative care. Since palliative care needs increase during the disease course of COPD, the prediction of mortality within 1 year, measured during hospitalizations for acute exacerbation COPD (AECOPD), was used as a proxy for the need of proactive palliative care.Patients and methods: Patients were recruited from three general hospitals in the Netherlands in 2014. Data of 11 potential predictors, a priori selected based on literature, were collected during hospitalization for AECOPD. After 1 year, the medical files were explored for the date of death. An optimal prediction model was assessed by Lasso logistic regression, with 20-fold cross-validation for optimal shrinkage. Missing data were handled using complete case analysis.Results: Of 174 patients, 155 patients were included; of those 30 (19.4%) died within 1 year. The optimal prediction model was internally validated and had good discriminating power (AUC =0.82, 95% CI 0.81–0.82). This model relied on the following seven predictors: the surprise question, Medical Research Council dyspnea questionnaire (MRC dyspnea), Clinical COPD Questionnaire (CCQ), FEV1% of predicted value, body mass index, previous hospitalizations for AECOPD and specific comorbidities. To ensure minimal miss out of patients in need of proactive palliative care, we proposed a cutoff in the model that prioritized sensitivity over specificity (0.90 over 0.73, respectively). Our model (ProPal-COPD tool) was a stronger predictor of mortality within 1 year than the CODEX (comorbidity, age, obstruction, dyspnea, and previous severe exacerbations) index.Conclusion: The ProPal-COPD tool is a promising multivariable prediction tool to identify patients with COPD for proactive palliative care. Keywords: COPD, exacerbation, proactive palliative care, prognosis, mortalit
Converter USB/RS 485
No full textThis thesis is describing problematic of realisation of converter from USB type media into the universal RS-485 bus which is mainly used for the industrial applications (author is using frequently as a device in order to enable communication between server and RFID devices). This thesis contains theoretical information, realisation of the device itself and assesment of reached targets
Converter USB/RS 485
No full textThis thesis is describing problematic of realisation of converter from USB type media into the universal RS-485 bus which is mainly used for the industrial applications (author is using frequently as a device in order to enable communication between server and RFID devices). This thesis contains theoretical information, realisation of the device itself and assesment of reached targets
Voxelwise rs-fMRI representation learning: A non-linear variational approach
No full textResting-state fMRI (rs-fMRI) has become an important imaging modality and is commonly used to study intrinsic brain networks. These networks can be obtained by decomposing rs-fMRI data into components, using independent component analysis (ICA). Recently, these ICA components have been used as inputs for neural networks to learn complex relations between the intrinsic networks of the brain and mental disorders or demographic variables. Instead of training a non-linear classifier on these linearly decomposed components, this work asks whether unsupervised representation learning can lead to linearly separable representations for multiple downstream tasks. We propose to apply non-linear representation learning to voxelwise rs-fMRI data. Learning the non-linear representations is done using two versions of a variational autoencoder (VAE). The first version is a vanilla VAE with 3D residual blocks in both its encoder and decoder. The second version is based on the identifiable VAE and uses a time-dependent prior. The models train to reconstruct the original input data from latent variables it infers. Three predictive models then evaluate the predictive power of the latent variables on an age regression, a sex classification, and a schizophrenia classification task. Each of the predictive models performs predictions for each of the three tasks. The predictive models are a support vector machine (SVM), a k-nearest neighbor (k-NN) model, and a long short-term memory (LSTM) neural network.We show that our method performs exceptionally well on the age regression and sex classification tasks without any supervision. These results imply that VAEs can model predictive variations in their latent spaces for demographic variables. The models, however, do not do well on the schizophrenia classification task, even when the models are pretrained. Despite the lower performance on the schizophrenia classification task, the overall results are encouraging and pave the way for future work on voxelwise representation learning.Electrical Engineering | Embedded SystemsBiomedical Engineerin
СРАВНИТЕЛЬНАЯ ХАРАКТЕРИСТИКА ИЗДАНИЙ РОМАННОГО ТВОРЧЕСТВА МИР ДЖАЛАЛА
No full textIn the article, the author of advanced ideas, explores published copies of novelist Mir Jalal's novels "The Resurrection Man (1936)", "The Open Book (1945)", "People of the Same Age,1948", "The New City (1951)", "Where are we going” (1957) comparative analysis. The repeated publication of the novels of the Soviet in the Soviet era or in the modern era, always proves the relevance of the talented creator. Two of the five novels of Mir Jalal, the one we talked about, have been the subject of past and the third one.In the article, the author of advanced ideas, explores published copies of novelist Mir Jalal's novels "The Resurrection Man (1936)", "The Open Book (1945)", "People of the Same Age,1948", "The New City (1951)", "Where are we going” (1957) comparative analysis. The repeated publication of the novels of the Soviet in the Soviet era or in the modern era, always proves the relevance of the talented creator. Two of the five novels of Mir Jalal, the one we talked about, have been the subject of past and the third one
Modeling a variable surface resistance (rs) for alfalfa and assessing the ASCE rs performance in the reference evapotranspiration equation
No full text2016 Fall.Includes bibliographical references.Accurate quantification of crop water requirement is necessary for proper irrigation water management. The knowledge of actual crop evapotranspiration (ETc) is important and is necessary for estimating irrigation water requirements. The most common procedure of obtaining actual crop evapotranspiration (ETc) is by first calculating the reference crop evapotranspiration (ETr) and then multiplying it with the appropriate crop coefficients (Kc). If the surface resistance (rs) of a particular crop can be modeled, then ETc can be directly calculated without using Kc. The overall objectives of this dissertation were to model surface resistance for alfalfa reference crop and to find an effective value of the surface resistance of alfalfa in the ASCE Standardized Reference ET equation. It has been found that using a single Kc curve for different climatic conditions can lead to significant error in estimating ETc. Hence it is important to find appropriate Kc for different crops for local climatic condition. Lysimeters are generally used to determine the values of Kc, as lysimetry is considered a reliable method of quantifying the ET losses from a control volume. This study found that using lysimeter ET data to obtain Kc can be problematic especially when the field is heterogeneous. In order to develop Kc for various crops, it is recommended to use some years of reliable data with uniform healthy and unstressed crop surface conditions both inside and outside the lysimeter. This study was focused on to develop a model for surface resistance (rs) of alfalfa in order to calculate alfalfa ETc in a one-step approach without the need for Kc values. Surface resistance was estimated by inverting the aerodynamic equation using ET measured from lysimeter and sensible heat flux (H) measured from large aperture scintillometer (LAS). This observed rs showed a very good correlation with leaf area index (LAI) and crop height (hc). The alfalfa rs was then modeled as a function of LAI and hc (which is referred to as rs(LAI) and rs(hc) respectively). Then these modeled rs s were incorporated into the Penman Monteith (PM) equation to estimate alfalfa hourly ET, which performed very well when compared with the measured hourly lysimeter ET. The conventional alfalfa rs, developed by Allen et al. (1989) was found to underestimate rs significantly especially when the crop height was short (less than 25 cm). It was found that ET_conventional_rs was not applicable to estimate alfalfa ET when the crop height was less than 25 cm. The modeled rs(LAI) and rs(hc) are constant throughout the day, but in reality, rs changes throughout the day. Hence hourly variable rs was also developed based on aerodynamic resistance (ra), canopy temperature (Tc) and vapor pressure deficit (VPD). It was found that PM equation incorporating the hourly variable rs improved the alfalfa ET estimation when compared with the conventional rs approach. ASCE-EWRI Standardized Reference ET for tall reference crop was found to underestimate measured ET by about 10 per cent. The equation assumes the value of rs for alfalfa as 30 s/m. When the value of rs was changed from 30 s/m to 10 s/m, the performance of the equation improved, resulting in no bias and root mean square error (RMSE) reduction from 0.08 mm/h (15.3%) to 0.06 mm/h (11.4%) in 2009 and from 0.09 mm/h (14.1%) to 0.06 mm/h (10.1%) in 2010
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