A Positive Answer to a Question of K. Borsuk on the Capacity of Polyhedra with Finite by Cyclic Fundamental Group

Karol Borsuk in 1968 asked: Is it true that every finite polyhedron dominates only finitely many different shapes? Danuta Kolodziejczyk showed that generally an answer to the Borsuk question is negative and also presented a positive answer by proving that every polyhedron with finite fundamental group dominates only finitely many different homotopy types (hence shapes). In this paper, we show that polyhedra with finite by cyclic fundamental group dominate only finitely many homotopy types. As a consequence, we give a partial positive answer to this question of Kolodziejczyk: Does every polyhedron with abelian fundamental group dominate only finitely many different homotopy types? In fact, we that every polyhedron with abelian fundamental group of rank 1 dominates only finitely many different homotopy types. Finally, we prove that every polyhedron dominates only finitely many homotopy types of simply connected CW-complexes.Comment: 9 page

SurgMAE: Masked Autoencoders for Long Surgical Video Analysis

There has been a growing interest in using deep learning models for processing long surgical videos, in order to automatically detect clinical/operational activities and extract metrics that can enable workflow efficiency tools and applications. However, training such models require vast amounts of labeled data which is costly and not scalable. Recently, self-supervised learning has been explored in computer vision community to reduce the burden of the annotation cost. Masked autoencoders (MAE) got the attention in self-supervised paradigm for Vision Transformers (ViTs) by predicting the randomly masked regions given the visible patches of an image or a video clip, and have shown superior performance on benchmark datasets. However, the application of MAE in surgical data remains unexplored. In this paper, we first investigate whether MAE can learn transferrable representations in surgical video domain. We propose SurgMAE, which is a novel architecture with a masking strategy based on sampling high spatio-temporal tokens for MAE. We provide an empirical study of SurgMAE on two large scale long surgical video datasets, and find that our method outperforms several baselines in low data regime. We conduct extensive ablation studies to show the efficacy of our approach and also demonstrate it's superior performance on UCF-101 to prove it's generalizability in non-surgical datasets as well

Depression and Anxiety in Iranian Mothers of Children with Epilepsy

How to Cite this Article: Soltanifar A, Ashrafzadeh F, Mohareri F, Mokhber N. Depression and Anxiety in Iranian Mothers ofChildren with Epilepsy. Iranian Journal of Child Neurology 2012;6(1):29-34. ObjectiveEpilepsy is a common neurological disorder in children. Parents with epileptic children have many psychosocial care needs. So the main goal of this study was to evaluate depression and anxiety in Iranian mothers with epileptic children.Materials & MethodsWe identified 30 mothers of children with epilepsy and 30 mothers of children without epilepsy with children aged between 8 and 12 years who met the study criteria. In all children with epilepsy, the mothers were the main caregivers and all these children lived in two-parent families. Children in the control group were in the same age. Ninety-eight percent of children in the control group lived in two-parent families with the mother as the main caregiver. All mothers fulfilled the Beck Depression Inventory (BDI) and Spielberger State-Trait Anxiety Inventory.ResultsAccording to these data, BDI scores were significantly higher in the mothers of epileptic children (mean of Beck score=16.5) compared to the control group (mean of Beck score=9.8). The total, Spielberger State-Trait Anxiety Inventory scores for mothers of children with epilepsy were 100.3, 51.7 and 48.6. However, these scores in the control group were 86.9, 45.1 and 41.8. These differences were statistically significant.In a second analysis, using the demographic data, we did not find any statistically significant relation between anxiety or depression and the mothers’ job, children’s medication and other demographic variables.ConclusionNeurologists and psychiatrists need to develop better programs for adequate management of psychiatric disorders in mothers with epileptic children. References 1. Cowan LD. The epidemiology of the epilepsies inchildren. Ment Retard Dev Disabil Res Rev 2002;8:171-81.2. Schiariti V, Farrell K, Hoube JS, Lisonkova S. Periodprevalence of epilepsy in children in BC: a population-basedstudy. Can J Neurol Sci 2009 Jan;36(1):36-41.3. Otero S. Psychopathology and psychological adjustmentin children and adolescents with epilepsy. World J Pediatr2009 Feb;5(1):12-7.4. Rodenburg HR, Stams GJJM, Meijer AM, Aldenkamp AP,Dekovic´ M. Psychopathology in children with epilepsy:a metaanalysis. J Pediatr Psychol 2005 Sep;30(6):453-68.Epub 2005 Mar 3.5. Rodenburg R, Meijer AM, Dekovic M, AldenkampAP. Family factors and psychopathology in childrenwith epilepsy: a literature review. Epilepsy Behav 2005Jun;6(4):488-503.6. Lovejoy M, Graczyk PA, O_Hare E, Neuman G. Maternaldepression and parenting behavior: a meta-analytic reviewClin Psychol Rev 2000;20:561-92.7. Shore CP, Buelow JM, Austin JK, Johnson CS.Continuing psychosocial care needs in children with newonsetepilepsy and their parents. J Neurosci Nurs 2009Oct;41(5):244-50.8. Pianta RC, Lothman DJ. Predicting behavior problemsin children with epilepsy: child factors, disease factors,family stress, and child-mother interaction. Child Dev1994 Oct;65(5):1415-28.9. Dunn DW, Austin JK, Huster GA. Symptoms ofdepression in adolescents with epilepsy. J Am Acad ChildAdolesc Psychiatr 1999;38:1133-8.10. Shore CP, Austin JK, Huster GA, Dunn DW. Identifyingrisk factors for maternal depression in families ofadolescents with epilepsy. J Specialists Pediatr Nurs2002;7:71-80.11. Yongli, Cheng-Ye ji, Jiong Qin, Zhi-Xiang Zhang.Parental anxiety and quality of Life of epileptic children.Biomed Environ Sci 2008 Jun;21(3):228-32.12. Williams J, Steel C, Sharp GB, DelosReyes E, PhillipsT, Bates S, et al. Parental anxiety and quality of life inchildren with epilepsy. Epilepsy Behav 2003;4:483-6.13. Lv R, Wu L, Jin L, Lu Q, Wang M, Qu Y, Liu H. Depression,anxiety and quality of life in parents of children withepilepsy. Acta Neurol Scand 2009 Nov;120(5):335-41.14. Baki O, Erdogan A, Kantarci O, Akisik G, KayaalpL, Yalcinkaya C. Anxiety and depression in childrenwith epilepsy and their mothers. Epilepsy Behav 2004Dec;5(6):958-64.15. Yam WK, Ronen GM, Cherk SW, Rosenbaum P, ChanKY, Streiner DL, et al. Health-related quality of lifeof children with epilepsy in Hong Kong: how does itcompare with that of youth with epilepsy in Canada?Epilepsy Behav 2008 Apr;12(3):419-26.16. Ghassemzadeh H, Mojtabai R, Karamghadiri N,Ebrahimkhani N. Psychometric properties of a Persianlanguageversion of the Beck Depression Inventory Second edition: BDI-II-PERSIAN. Depress Anxiety2005;21(4):185-92.17. Hojat M, Shapurian R, Mehryar AH. Psychometricproperties of a Persian version of the short form of theBeck Depression Inventory for Iranian college students.Psychol Rep 1986 Aug;59(1):331-8.18. Kalkhoran MA, Karimollahi M. Religiousness andpreoperative anxiety: a correlational study. Ann GenPsychiatry 2007;6:17.19. Mu PF, Kuo HC, Chang KP. Boundary ambiguity, copingpatterns and depression in mothers caring for children withepilepsy in Taiwan. Int J Nurs Stud 2005 Mar;42(3):273-82.20. Lv R, Wu L, Jin L, Lu Q, Wang M, Qu Y, et al. Depression,anxiety and quality of life in parents of children withepilepsy. Acta Neurol Scand 2009 Nov;120(5):335-41.21. (Wood LJ, Sherman E, Hamiwka LD, Blackman M,Wirrell E. Depression, anxiety, and quality of life insiblings of children with intractable epilepsy. EpilepsyBehav 2008 Jul;13(1):144-8.22. Tosun A, Gokcen S, Ozbaran B, Serdaroglu G, Polat M,Tekgul H, et al. The effect of depression on academicachievement in children with epilepsy. Epilepsy Behav2008 Oct;13(3):494-8.23. Rodenburg R, Meijer AM, Dekovic M, Aldenkamp AP. Family factors and psychopathology in childrenwith epilepsy: a literature review. Epilepsy Behav 2005Jun;6(4):488-503.24. Wirrell EC, Wood L, Hamiwka LD, Sherman EM. Parenting stress in mothers of children with intractableepilepsy. Epilepsy Behav 2008 Jul;13(1):169-73

Evaluating of psychiatric behavior in obese children and adolescents

Abstract IntroductionObesity is a medical condition  that it may have a harmful effect on health, leading to increased illness and reduced life expectancy. This study is aimed to evaluate the relationship of psychiatry disorders in overweight and obese children and adolescents.MethodsIn this was case-control study, one hundred and sixty child and Adolescent were recruited. The sampling method of this study was non-probability and biased. Study instruments were SDQ, CDI, STAI, Peds QL. All questionnaires were self-administrating that was completed by subjects or their parents. Differences between groups were examined using t-test and chi-square tests as appropriate. ResultsThe results our study showed no significant different in scores of anxiety between two groups. But showed significant different in scores of depression, quality of life, and strength and difficult between two groups.  Also there was no significant difference in gender effect on anxiety and Depression. However, in Quality of life test showed that emotional symptoms were more in girl than boys. In contrast, the conduct problems were more in boys than girls. Anxiety and Depression was more in adolescents than childrenConcussion Our study showed obesity has a negative effect on the anxiety, depression, and self-esteem of children and adolescents. It can be suggested that obesity might be a more important risk factor for depression, anxiety, and other psychiatry disorders. This study also emphasizes the importance of prevention of obesity

Tracking and Mapping in Medical Computer Vision: A Review

As computer vision algorithms are becoming more capable, their applications in clinical systems will become more pervasive. These applications include diagnostics such as colonoscopy and bronchoscopy, guiding biopsies and minimally invasive interventions and surgery, automating instrument motion and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing and applying algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision. We begin with describing our review process, which results in a final list of 515 papers that we cover. We then give a high-level summary of the state of the art and provide relevant background for those who need tracking and mapping for their clinical applications. We then review datasets provided in the field and the clinical needs therein. Then, we delve in depth into the algorithmic side, and summarize recent developments, which should be especially useful for algorithm designers and to those looking to understand the capability of off-the-shelf methods. We focus on algorithms for deformable environments while also reviewing the essential building blocks in rigid tracking and mapping since there is a large amount of crossover in methods. Finally, we discuss the current state of the tracking and mapping methods along with needs for future algorithms, needs for quantification, and the viability of clinical applications in the field. We conclude that new methods need to be designed or combined to support clinical applications in deformable environments, and more focus needs to be put into collecting datasets for training and evaluation.Comment: 31 pages, 17 figure

A survey on computational intelligence approaches for predictive modeling in prostate cancer

Predictive modeling in medicine involves the development of computational models which are capable of analysing large amounts of data in order to predict healthcare outcomes for individual patients. Computational intelligence approaches are suitable when the data to be modelled are too complex forconventional statistical techniques to process quickly and eciently. These advanced approaches are based on mathematical models that have been especially developed for dealing with the uncertainty and imprecision which is typically found in clinical and biological datasets. This paper provides a survey of recent work on computational intelligence approaches that have been applied to prostate cancer predictive modeling, and considers the challenges which need to be addressed. In particular, the paper considers a broad definition of computational intelligence which includes evolutionary algorithms (also known asmetaheuristic optimisation, nature inspired optimisation algorithms), Artificial Neural Networks, Deep Learning, Fuzzy based approaches, and hybrids of these,as well as Bayesian based approaches, and Markov models. Metaheuristic optimisation approaches, such as the Ant Colony Optimisation, Particle Swarm Optimisation, and Artificial Immune Network have been utilised for optimising the performance of prostate cancer predictive models, and the suitability of these approaches are discussed