The Repeatability of Axial Length Measurements Using a Scheimpflug-based System

Purpose: To assess the repeatability of Pentacam AXL as a Scheimpflug-based system or measuring axial length according to the age, sex, lens type, axial length value, and type of cataract. Methods: The present study was conducted using multistage cluster sampling in Tehran, Iran. Ocular biometry was performed, using the Pentacam AXL, by an experienced optometrist on all the participants. The axial length (AL) measurements were taken thrice, with a gap of 10 minutes. To evaluate the repeatability, the intraclass correlation coefficient (ICC) and the repeatability coefficient (RC) were calculated. To determine the significant difference in the repeatability index among study variables, the tolerance index (TI) was calculated. Results: In this report, 897 eyes of 677 individuals aged between 20 and 91 years (mean ± SD: 64.90 ± 13.62 years) were reported. The ICC of the axial length measurements was 0.981 for all cases. Based on the within-subject standard deviation, the RC was 0.401. The ICC was 0.976 and 0.985 in men and women, respectively. The TI showed better RC of measurements among females. The ICC decreased from 0.999 in participants under 40 years to 0.973 in individuals over 60 years of age. The TI showed a decrease in RC with advancing age. The RC was worse in eyes with nuclear cataracts; the RC was also worse in the first quartile of the signal-to-noise ratio (SNR) compared to the other SNR quartiles. Conclusion: The Scheimpflug-based system Pentacam AXL had high repeatability in measuring axial length. Some variables such as male gender, older age, and nuclear cataract were associated with reduced repeatability of the measurements. A higher SNR was associated with better repeatability of the axial length measurements

Agreements’ profile of Scheimpflug-based optical biometer with gold standard partial coherence interferometry

AIM: To determine the agreement of ocular biometric indices including axial length, keratometric readings, anterior chamber depth, and horizontal corneal diameter between the Pentacam AXL and IOL Master 500. METHODS: The study was a large cross-sectional population-based study (Tehran Geriatric Eye Study) conducted from Jan 2019 to Jan 2020. A total of 160 clusters were randomly selected proportional to size (each cluster contained 20 individuals) from 22 strata of Tehran city. All people aged 60y and above were invited to participate in the study. For all participants, preliminary ocular examinations were performed including the measurement of uncorrected and best-corrected visual acuity, objective and subjective refraction, anterior and posterior segment examinations. All participants underwent an ocular biometry using the Pentacam AXL and IOL Master 500. RESULTS: The 95% limits of agreement (LoA) between the two devices were -0.13 to 0.19, -0.15 to 0.17, and -0.13 to 0.19 in normal, pseudophakic, and cataractous eyes, respectively. With increasing the axial length, the difference between the two devices significantly increased in all three groups of normal, pseudophakic, and cataractous eyes (P<0.001). The 95% LoAs between the two devices regarding the mean keratometry shows that the best LoAs were seen in cataractous (-0.33 to 0.81) and followed by normal eyes (-0.36 to 0.86) and the pseudophakic eyes (-0.48 to 0.90) had the widest LoA. The 95% LoAs for horizontal corneal diameter measurements were -0.08 to 0.86, -0.03 to 0.83, and -0.07 to 0.87 in normal, pseudophakic, and cataractous eyes, respectively. The 95% LoAs of anterior chamber depth measurements between the two devices was -0.39 to 0.19 and -0.37 to 0.13 in normal eyes and cataractous, respectively. CONCLUSION: The Pentacam AXL has excellent agreement with the gold standard, IOL Master 500 in measuring axial length. In eyes with cataracts, the difference between the two devices is more scattered. With the increasing of axial length, the difference between the two devices increased, which should be considered when using Pentacam AXL

Response to Cardiac Resynchronization Therapy in Cardiomyopathy Patients with Right Bundle Branch Block

Background: The use of cardiac resynchronization therapy (CRT) in heart failure patients with right bundle branch block (RBBB) is under debate. We present early and late echocardiographic characteristics of a series of heart failure patients with RBBB who underwent CRT.  Methods: In this retrospective descriptive study, 18 patients with RBBB in the surface electrocardiogram underwent CRT between 2005 and 2015. All the patients had the New York Heart Association functional class III/IV, a left ventricular ejection fraction (LVEF) ≤35%, and a QRS duration ≥120 milliseconds. The median follow-up duration was 19 months. The echocardiographic response was based on a ≥5% increase in LVEF.  Results: Within 48 hours after CRT implantation, LVEF increased from 24.58%±7.08% before to 28.46±8.91% after CRT (P=0.005) and to 30.00±9.44% at follow-up (P=0.008). Among the 18 patients, 12 (66.7%) were responders within 48 hours after CRT. The following baseline echocardiographic parameters were higher in the responders than in those without an increased LVEF, although the difference did not reach statistical significance: septal-to-lateral wall delay (48.33±33.53 vs 43.33±38.82 ms), anteroseptal-to-posterior wall delay (41.7±1.75 vs 38.33±18.35 ms), and interventricular mechanical delay (48.50±21.13 vs 31.17±19.93 ms). The mean QRS duration was higher in the responders than in the non-responders (183.58±40.69 vs 169.00±27.36 ms). Death was reported in 3 out of the 18 patients (16.7%) at follow-up. The 3 deceased patients had a higher baseline interventricular mechanical delay than those who survived.  Conclusion: Our results indicated that patients with RBBB might benefit from CRT. Further, patients with higher intra and interventricular dyssynchrony and a wider QRS may show better responses

Analysis of Association between the Effects of Methylphenidate and DRD4 Gene Polymorphisms in Patients with Attention Deficit Hyperactivity Disorder

Background: Drug treatment is one of the most important treatments for attention deficit hyperactivity disorder (ADHD). The DRD4 gene is a transporter and receptor coding gene of dopamine and is one of the most important genes under investigation in the disorder and etiology of ADHD. In this study, the association between rs3758653 C/T and VNTR exon 3 repetition polymorphisms of the DRD4 gene and the effects of methylphenidate were investigated in patients with ADHD disorder consuming methylphenidate. Methods: The descriptive-analytical study was performed on 122 patients (5 - 18 years old) with ADHD who were treated with methylphenidate. DNA was extracted using salting out method. Subsequently, the rs3758653 polymorphism in the 5’UTR region of DRD4 gene was genotyped by PCR-RFLP method, and the VNTR fragment in exon III of DRD4 gene was investigated by electrophoresis gel on acrylamide gel method. After eight weeks from the start of drug treatment with methylphenidate, the intensity of symptoms was evaluated using the Conners scale. Finally, all data from questionnaires and information that were resulted from laboratory findings were analyzed using ANOVA and repeated measure analysis. Results: Of the 122 patients under study, 15 patients (12.3%) were responded to the drug treatment, and 107 patients (87.7%) were not responded. The significant differences were not revealed in genotype, and allele frequencies of between rs3758653 (C/T) and exon III 3’VNTR repeats polymorphisms of the DRD4 gene and responder and non-responder of ADHD groups to the drug treatment. Conclusions: The results showed that the reduction of ADHD symptoms with drug treatment is not related to DRD4 sub-types in patients with ADHD

Urban Diversity and Pedestrian Behavior : Refining the concept of land-use mix for walkability

While land-use mix has continuously been referred to for its importance for walkability, current researchdemands further investigation to refine the concept and develop the measurement for it so that it may bestcapture the way it influences walking behavior. This study combines two on-going research projects dealingwith issues in urban form, one on urban diversity and the other on walkability, both trying to develop theconceptualization and the measurement of these qualities. Regarding diversity, scales and categorizations astwo essential factors for evaluating diversity are examined in this study by the implementation of analysis atvarious configurational levels and on access to variety. From the research project on walkability, a qualitativeobservation study was conducted examining the subjective measurement of pedestrian density and itspatterns, the route choices made in the walking trips observed while tracking pedestrians, and the differenttypes of walking activities taking place in the study areas. By obtaining hard data on real behaviors of walkingin different situations, it provides a detailed description of the walking activities and their patterns in threeneighborhoods in Stockholm, Sweden, where the quantitative analysis regarding diversity was also conducted.Therefore, in this study the multi-level analyses searching for the proper and useful scale for measuringdiversity are compared with the descriptive data on walking behavior, in order to test their validity andapplicability in walkability research. The results show that areas with higher degree of diversity in the builtenvironment contribute to higher degree of diversity in walking behavior by providing variety in both thecomposition of pedestrians and the type of walking activities, which may ultimately enhance the walkability ofan area. The comparison of the quantitative analysis of the built environment with the description of thewalking activities show the potential of the analysis presented in this paper as a tool in measuring factorsrelated to walkability, and the process allows a better understanding of the walkability as a complex subject.Certain parts of the analyses especially show strength in being a more precise measurement and a betterrepresentation of the built environment attributes than the ones done in the earlier walkability studies.Although the analyses and discussions presented in this paper yet have limitations in fully exploring the issueof diversity and walkability of the urban form, they provide insight and knowledge for the development ofeach project.QC 2012042

Urban diversity and how to measure it : An operational definition of classes and scales

Diversity as an essential factor for liveability, economic growth, and attractiveness in cities was stressed already half a century ago by Jane Jacobs (1961, 1969). Its importance has only grown and today, diversity is stated as fundamental for current creative societies and their need for knowledge spillovers, and referred to by economists as “Jacobean externalities”. More specifically, in urban morphology and design, we can find various trends that have tried to achieve such aims under the banner of for example mixed-use. The problem is, firstly, that the definitions are not strict enough to categorize what we mean with diversity. Secondly, there are not proper analytical tools to measure diversity so that we can compare various areas. For measurements there are various challenges ahead. For instance, cities may seem diverse on one scale but widely homogeneous on another. Consequently, application of analysis on various scales and precise categorizations are essential for the development of new knowledge on urban diversity. This paper addresses these needs, firstly, by a conceptual discussion on diversity in contradiction to specialization and homogeneity in cities. Secondly, by setting up a framework for the measurement of diversity, both as an economic phenomena and how it can be supported by urban form. The overall framework for this project is a thorough discussion and testing of a redefinition of Jacobs’ four criteria for spatial diversity in cities, introduced in the Death and Life of Great American Cities. Preliminary studies suggest strong correlation between all these criteria, in their developed and analytically formalized definitions for ground floor activities in the inner city of Stockholm.QC 2011121

Algorithmic problems of handwriting recognition

Maģistra darbs “Rokraksta atpazīšanas algoritmiskie jautājumi” ir izstrādāts latviešu valodā, aizņem 132.lpp. ar pielikimi, satur 4.tabulas, 43.attēlus un vairākus algoritmus. Rokraksta atpazīšana ir viena no tēlu atpazīšanas problēmām, kuras mērķis ir ar roku rakstītu tekstu pārveidot par datoram saprotamu, interpretējamu formātu. Darbā autors mēģināja apzināt rokraksta atpazīšanas nozares stāvokli un to raksturot. Rokraksta atpazīšanas nozare ir ļoti nesakārota un ļoti plaša, kas apgrūtināja šī uzdevuma izpildi. Darbā tika apkopoti vairāk kā 120 literatūras avoti. Literatūra tika skatīta visos rokraksta atpazīšanas algoritmiskos jautājumos, ietverot rokraksta pirmsapstrādi, segmentēšanu, īpašību izgūšanu un klasifikāciju. Darbā tiek skatīti gan Online, gan Offline algoritmi. Katrs no šiem jautājumiem tiek skatīts atsevišķi, analizējot atbilstošā posmā nepieciešamos algoritmus. Darbā ir raksturota virkne algoritmu, kas ietver statistiskās metodes, neironu tīklus, Markova modeļus un citus iesaistītos tematus. Algoritmi piedāvāti gan vispārīgi, gan arī dots algoritmu pielietojuma piemērs. Visbeidzot tika izstrādāta valodā C# neliela pirmsapstrādē iesaistīto algoritmu bibliotēka, kā arī uzrakstīta vilkumu atpazīšanas programma, kas parāda Rubina algoritma, lineārā diskriminatora, neironu tīklu, DTW darbību, kā arī izmanto autora izdomāto vienkāršo algoritmu. Programma ir modulāra, to var viegli papildināt ar jauniem algoritmiem gan izmantojot esošās funkcijas, gan pievienojot jaunas. Atslēgvārdi: On-line, Off-line, rekurentie neironu tīkli, rokraksta atpazīšana, rokraksta segmentēšana, Rubina algoritms, spalvas ceļa atjaunošana, vilkumu atpazīšana, DTW, neironu tīkli, lineārais diskriminators, Markova modeļi, zonēšana, rokraksta pirmsapstrāde, rokraksta pēcapstrādeThe master's theses “Algorithmical problems of Handwriting recognition” has been developed in latvian language, includes 132 pages of writen text, 4 tables, 43 images and several algorithms. The handwriting recognition is one of the pattern recognition problems, the target of which is to transform handwritten text into format recognizable by a computing system. The author has tried to aggregate the state of the handwriting recognition sector and to describe it. The sector is very broad and uncategorized, which made this process difficult. More than 120 sources of literature were covered. The sources vary across broad handwriting recognition algorithmic areas, including hadnwriting preprocessing, segmentation, feature extraction and classification. The paper includes both Online and Offline algorithms. Each of these has been observed seperatly, analyzing the respective necessary algorithms. The paper describes series of algorithms like statistical methods, neural networks, Markov models and other topics. The algorithms have been presented both generally and with relevant examples. At last, a small algorithm library involved in handwiring preprocessing has been developed in C# language. Also, a stroke recongition programm was written, which revieles Rubine algorithm, neural network, DTW functionality and which also uses a simple algorithm created by the author. The programms is modular and can be easilly sumplimented by new algorithms using both existing functions as well as perspective. Keywords: On-line, Off-line, recurrent neural network, handwriting recognition, handwriting segmentation, Rubin algorithm, replication of pen stroke, gesture recognition, DTW, neural networks, linear discriminator, Markov models, zoning, handwriging preprocessing, handwriting postprocessin

Audio based depression detection using Convolutional Autoencoder

Depression is a serious and common psychological disorder that requires early diagnosis and treatment. In severe episodes the condition may result in suicidal thoughts. Recently, the need for building an effective audio-based Automatic Depression Detection (ADD) system has sparked the interest of the research community. To date, most of the reported approaches to recognize depression rely on hand-crafted feature extraction for audio data representation. They combine wide variety of audio-related features to improve the classification performance. However, combining many hand-crafted features including relevant and less-relevant can enlarge the feature space which can lead to high-dimensionality issues as not all the features would carry significant information regarding depression. Having high number of features can make the pattern recognition more difficult and increase the risk of overfitting. To overcome these limitations, an audio-based framework of depression detection which includes an adaptation of a deep learning (DL) technique is proposed to automatically extract the highly relevant and compact feature set. This proposed framework uses an end-to-end Convolutional Neural Network-based Autoencoder (CNN AE) technique to learn the highly relevant and discriminative features from raw sequential audio data, and hence to detect depressed people more accurately. In addition, to address the sample imbalance problem we use a cluster-based sampling technique which highly reduces the risk of bias towards the major class (non-depressed). To evaluate the performance and effectiveness of the proposed pipeline, we perform the experiments on Distress Analysis Interview Corpus-Wizard of Oz (DAIC-WOZ) dataset and compare them with the hand-crafted feature extraction methods and other outstanding studies in this domain. The results show that proposed method outperforms other well-known audio-based ADD models with at least 7% improvement in F-measure for classifying depression.</p