PubMed İndeksli Yayınlar Koleksiyonu
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Article Citation - WoS: 77Citation - Scopus: 82Feedback network controls photoreceptor output at the layer of first visual synapses in Drosophila(Rockefeller Univ Press, 2006) Lei Zheng; Gonzalo García De Polavieja; Verena Wolfram; Musa Hakan Asyali; Roger C. Hardie; Mikko A. Juusola; Wolfram, V; Polavieja, GG; Juusola, M; Zheng, L; Asyali, MH; De Polavieja, Gonzalo G.; Hardie, RCAt the layer of first visual synapses information from photoreceptors is processed and transmitted towards the brain. In fly compound eye output from photoreceptors (R1-R6) that share the same visual field is pooled and transmitted via histaminergic synapses to two classes of interneuron large monopolar cells (LMCs) and amacrine cells (ACs). The interneurons also feed back to photoreceptor terminals via numerous ligand-gated synapses yet the significance of these connections has remained a mystery. We investigated the role of feedback synapses by comparing intracellular responses of photoreceptors and LMCs in wild-type Drosophila and in synaptic mutants to light and current pulses and to naturalistic light stimuli. The recordings were further subjected to rigorous statistical and information-theoretical analysis. We show that the feedback synapses form a negative feedback loop that controls the speed and amplitude of photoreceptor responses and hence the quality of the transmitted signals. These results highlight the benefits of feedback synapses for neural information processing and suggest that similar coding strategies could be used in other nervous systems. © The Rockefeller University Press. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - Scopus: 71Comparison of AR and Welch methods in epileptic seizure detection(2006) Ahmet Alkan; Mahmut Kemal Kıymık; Alkan, Ahmet; Kiymik, M. KemalBrain is one of the most critical organs of the body. Synchronous neuronal discharges generate rhythmic potential fluctuations which can be recorded from the scalp through electroencephalography. The electroencephalogram (EEG) can be roughly defined as the mean electrical activity measured at different sites of the head. EEG patterns correlated with normal functions and diseases of the central nervous system. In this study EEG signals were analyzed by using autoregressive (parametric) and Welch (non-parametric) spectral estimation methods. The parameters of autoregressive (AR) method were estimated by using Yule-Walker covariance and modified covariance methods. EEG spectra were then used to compare the applied estimation methods in terms of their frequency resolution and the effects in determination of spectral components. The variations in the shape of the EEG power spectra were examined in order to epileptic seizures detection. Performance of the proposed methods was evaluated by means of power spectral densities (PSDs). Graphical results comparing the performance of the proposed methods with that of Welch technique were given. The results demonstrate consistently superior performance of the covariance methods over Yule-Walker AR and Welch methods. © 2006 Springer Science+Business Media Inc. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 30Citation - Scopus: 35Determining a continuous marker for sleep depth(Pergamon-Elsevier Science Ltd, 2007) Musa Hakan Asyali; Richard Barnett Berry; Michael C.K. Khoo; Ayşe Asyali Altinok; Khoo, Michael C.K.; Asyali, Musa H.; Berry, Richard B.; Altinok, AyseDetection and quantification of sleep arousals is an important issue as the frequent arousals are known to reduce the quality of sleep and cause daytime sleepiness. In typical sleep staging electroencephalograph (EEG) is the core signal and based on the visual inspection of the frequency content of EEG non-rapid eye movement sleep is staged into four somewhat rough categories. In this study we aimed at developing a continuous marker based on a more rigorous spectral analysis of EEG to measure or quantify the depth of sleep. In order to develop such a marker we obtained the time-frequency map of two EEG channels around sleep arousals and identified the frequency bands that show the most change during arousals. We then evaluated classification performance of the potential signals for representing the depth of sleep using receiver operating characteristic analysis. Our comparisons based on the area under the curve values revealed that the sum of absolute powers in alpha and beta bands is a good continuous marker to represent the depth of sleep. Higher values of this marker indicate low-quality sleep and vice versa. We believe that use of this marker will lead to a better quantification of sleep quality. © 2007. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 9Citation - Scopus: 13Gene expression profile class prediction using linear Bayesian classifiers(PERGAMON-ELSEVIER SCIENCE LTD, 2007) Musa H. Asyali; Asyali, Musa H.Due to recent advances in DNA microarray technology using gene expression profiles diagnostic category of tissue samples can be predicted with high accuracy. In this study we discuss shortcomings of some existing gene expression profile classification methods and propose a new approach based on linear Bayesian classifiers. In our approach we first construct gene-level linear classifiers to identify genes that provide high class-prediction accuracies i.e. low error rates. After this screening phase starting with the gene that offers the lowest error rate we construct a multi-dimensional linear classifier by incorporating next best-per-forming genes until the prediction error becomes minimum or 0 if possible. When we compared classification performance of our approach against prediction analysis of microarrays (PAM) and support vector machines (SVM) based approaches we found that our method outperforms PAM and produces comparable results with SVM. In addition we observed that the gene selection scheme of PAM could be misleading. Albeit SVM achieves relatively higher prediction performance it has two major disadvantages: Complexity and lack of insight about important genes. Our intuitive approach offers competing performance and also an efficient means for finding important genes. (c) 2007 Elsevier Ltd. All rights reserved.Article Citation - WoS: 26Citation - Scopus: 30Negotiators' profit predicted by cognitive reappraisal suppression of emotions misrepresentation of information and tolerance of ambiguity(SAGE Publications Inc, 2008) Gülçimen Yurtsever; Yurtsever, GolcimenThis study examined the relationship between negative emotions and variables that affect negotiators' profit. Based on a simulated negotiation this study induced emotions by providing negative feedback on how negotiating partners perceived and evaluated each other's behavior. Then relationships were examined between negative emotions and emotional regulation strategies misrepresentation of information tolerance of ambiguity and negotiators' profit. A total of 228 undergraduate students enrolled in an economics course in the Faculty of Law and the Faculty of Management at a university in Ankara participated. There were 130 students in the experimental group and 98 students in the control group, 102 were men and 126 were women ages 17 to 35 years (M = 22.6 yr. SD = 2.3). A simulated negotiation process was used. Regression coefficients suggested positive relation between Emotional Reaction and the use of a Suppression strategy and Misrepresentation of Information. Negative coefficients were obtained from scores between Emotional Reaction and Cognitive Reappraisal and Tolerance of Ambiguity. The regression also suggested there were negative regression coefficients linking Misrepresentation of Information and Suppression strategies to Negotiators' Profit. Positive regression coefficients linked Tolerance of Ambiguity to Negotiators' Profit. Mediating variables explained 55% of variance in Negotiators' Profit, the majority (43%) was explained by Cognitive Reappraisal. © Perceptual and Motor Skills 2008. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 45Citation - Scopus: 50Classification of EEG recordings by using fast independent component analysis and artificial neural network(Springer, 2008) Yücel Koçyig̃it; Ahmet Alkan; Halil Erol; Alkan, Ahmet; Kocyigit, Yucel; Erol, HalilSince there is no definite decisive factor evaluated by the experts visual analysis of EEG signals in time domain may be inadequate. Routine clinical diagnosis requests to analysis of EEG signals. Therefore a number of automation and computer techniques have been used for this aim. In this study we aim at designing a MLPNN classifier based on the Fast ICA that accurately identifies whether the associated subject is normal or epileptic. By analyzing a data set consisting of 100 normal and 100 epileptic EEG time series we have found that the MLPNN classifier based on the Fast ICA achieved and sensitivity rate of 98% and specificity rate of 90.5%. The results demonstrate that the testing performance of the neural network diagnostic system is found to be satisfactory and we think that this system can be used in clinical studies. Since the time series analysis of EEG signals is unsatisfactory and requires specialist clinicians to evaluate this application brings objectivity to the evaluation of EEG signals. © 2007 Springer Science+Business Media LLC. © 2008 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 5Citation - Scopus: 7Detection of hidden hostile/terrorist groups in harsh territories by using animals as mobile biological sensors(MDPI, 2008) Yasar Guneri Sahin; Tuncay Ercan; Ercan, Tuncay; Sahin, Yasar GuneriTerrorism is the greatest threat to national security and cannot be defeated by conventional military force alone. In critical areas such as Iraq Afghanistan and Turkey regular forces cannot reach these hostile/terrorist groups the instigators of terrorism. These groups have a clear understanding of the relative ineffectiveness of counter-guerrilla operations and rely on guerrilla warfare to avoid major combat as their primary means of continuing the conflict with the governmental structures. In Internal Security Operations detection of terrorist and hostile groups in their hiding places such as caves lairs etc. can only be achieved by professionally trained people such as Special Forces or intelligence units with the necessary experience and tools suitable for collecting accurate information in these often harsh rugged and mountainous countries. To assist these forces commercial micro-sensors with wireless interfaces could be utilized to study and monitor a variety of phenomena and environments from a certain distance for military purposes. In order to locate hidden terrorist groups and enable more effective use of conventional military resources this paper proposes an active remote sensing model implanted into animals capable of living in these environments. By using these mobile sensor devices improving communications for data transfer from the source and developing better ways to monitor and detect threats terrorist ability to carry out attacks can be severely disrupted.Article Citation - WoS: 32Citation - Scopus: 35Hypoglycemic effect of Lentinus strigosus (Schwein.) Fr. crude exopolysaccharide in streptozotocin-induced diabetic rats(Mary Ann Liebert, Inc, 2008) Mustafa Yamaç; Güngör Kanbak; Melih Zeytinoǧlu; Gökhan Bayramoǧlu; Hakan Şenturk; Mustafa Uyanoǧlu; Senturk, Hakan; Uyanoglu, Mustafa; Kanbak, Gungor; Yamac, Mustafa; Bayramoglu, Gokhan; Zeytinoglu, MelihThis study reports the hypoglycemic effects of the crude exopolysaccharide (EPS) produced from submerged mycelial culture of Lentinus strigosus (Schwein.) Fr. (Family Polyporaceae) in streptozotocin (STZ)-induced diabetic rats. In a dose-dependent study diabetic rats were treated with EPS at doses of 50-150 mg/kg of body weight for 7 days. Serum glucose and plasma insulin levels were measured in normal STZ-induced diabetic and EPS-treated diabetic rats. Following oral administration of EPS dosages for 7 days the serum glucose levels in the STZ-induced diabetic rats were reduced up to 21.1% at the dose of 150 mg/kg of body weight. The results revealed that orally administered L. strigosus EPS at the dose of 150 mg/kg exhibited a considerable hypoglycemic effect in STZ-induced diabetic rats. Plasma insulin levels of STZ-induced diabetic rats decreased as compared to control group rats (P < .05). Although insulin levels slightly increased in the EPS-treated groups the increase was not statistically significant. The hypoglycemic potential of the EPS was further supported by histological observations of pancreatic islets of Langerhans. © 2008 Mary Ann Liebert Inc. © 2009 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 135Citation - Scopus: 162Exploiting Data Topology in Visualization and Clustering Self-Organizing Maps(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2009) Kadim Tasdemir; Erzsebet Merenyi; Tasdemir, Kadim; Merenyi, ErzsebetThe self-organizing map (SOM) is a powerful method for visualization cluster extraction and data mining. It has been used successfully for data of high dimensionality and complexity where traditional methods may often be insufficient. In order to analyze data structure and capture cluster boundaries from the SOM one common approach is to represent the SOM's knowledge by visualization methods. Different aspects of the information learned by the SOM are presented by existing methods but data topology which is present in the SOM's knowledge is greatly underutilized. We show in this paper that data topology can be integrated into the visualization of the SOM and thereby provide a more elaborate view of the cluster structure than existing schemes. We achieve this by introducing a weighted Delaunay triangulation (a connectivity matrix) and draping it over the SOM. This new visualization CONNvis also shows both forward and backward topology violations along with the severity of forward ones which indicate the quality of the SOM learning and the data complexity. CONNvis greatly assists in detailed identification of cluster boundaries. We demonstrate the capabilities on synthetic data sets and on a real 8-D remote sensing spectral image.Article Citation - WoS: 23Citation - Scopus: 24Graph Based Representations of Density Distribution and Distances for Self-Organizing Maps(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010) Kadim Tasdemir; Tasdemir, KadimThe self-organizing map (SOM) is a powerful method for manifold learning because of producing a 2-D spatially ordered quantization of a higher dimensional data space on a rigid lattice and adaptively determining optimal approximation of the (unknown) density distribution of the data. However a postprocessing visualization scheme is often required to capture the data manifold. A recent visualization scheme CONNvis which is shown effective for clustering uses a topology representing graph that shows detailed local data distribution within receptive fields. This brief proposes that this graph representation can be adapted to show local distances. The proposed graphs of local density and local distances provide tools to analyze the correlation between these two information and to merge them in various ways to achieve an advanced visualization. The brief also gives comparisons for several synthetic data sets.Article BUYER SELLER NEGOTIATIONS: A COMPARISON OF DOMESTIC AND INTERNATIONAL CONDITIONS IN A PILOT STUDY WITH INTERNATIONAL BUSINESS STUDENTS(SAGE PUBLICATIONS INC, 2010) Guelcimen Yurtsever; Gizem Kurt; Gungor Hacioglu; Hacioglu, Gungor; Yurtsever, Guelcimen; Kurt, GizemThis study examined the differences and similarities between domestic and international negotiations using Kelley's Negotiation Game to measure the profit achieved. There were 58 participants in the international negotiation sample 29 Turkish and 29 European students. There were 62 Turkish students in the domestic negotiations. All participants studied business or related topics at a university in Izmir. Student t tests indicated statistically significant differences in scores on misrepresentation of information interpersonal attraction peer evaluation of misrepresentation information and satisfaction between domestic and international negotiations.Article Citation - WoS: 13Hemophagocytic lymphohistiocytosis associated with H1N1 virus infection and visceral leishmaniasis in a 4.5-month-old infant(SOC BRASILEIRA MEDICINA TROPICAL, 2012) Yilmaz Ay; Basak Yildiz; Hale Tuhan; Deniz Yilmaz Karapinar; Fadil Vardar; Tuhan, Hale; Ay, Yilmaz; Yildiz, Basak; Vardar, Fadil; Karapinar, Deniz YilmazWe present a case of a 4.5-month-old boy from Turkey with hemophagocytic lymphohistiocytosis (HLH) associated with H1N1 virus and Leishmania spp. coinfection. Because visceral leishmaniasis can mimic hematologic disorders like HLH it is important to rule out this clinical condition before starting immunosuppressive therapy. In our case treatment with liposomal amphotericin B resulted in a dramatic resolution of clinical and laboratory abnormalities.Article Citation - WoS: 58Citation - Scopus: 78Young people's topography of musical functions: Personal- social and cultural experiences with music across genders and six societies(JOHN WILEY & SONS LTD, 2012) Diana Boer; Ronald Fischer; Hasan Gurkan Tekman; Amina Abubakar; Jane Njenga; Markus Zenger; Abubakar, Amina; Tekman, Hasan Gürkan; Fischer, Ronald; Boer, Diana; Njenga, Jane; Zenger, MarkusHow can we understand the uses of music in daily life? Music is a universal phenomenon but with significant interindividual and cultural variability. Listeners' gender and cultural background may influence how and why music is used in daily life. This paper reports the first investigation of a holistic framework and a new measure of music functions (RESPECT-music) across genders and six diverse cultural samples (students from Germany Kenya Mexico New Zealand Philippines and Turkey). Two dimensions underlie the mental representation of music functions. First music can be used for contemplation or affective functions. Second music can serve intrapersonal social and sociocultural functions. Results reveal that gender differences occur for affective functions indicating that female listeners use music more for affective functions i.e. emotional expression dancing and cultural identity. Country differences are moderate for social functions (values social bonding dancing) and strongest for sociocultural function (cultural identity family bonding political attitudes). Cultural values such as individualism-collectivism and secularism-traditionalism can help explain cross-cultural differences in the uses of music. Listeners from more collectivistic cultures use music more frequently for expressing values and cultural identity. Listeners from more secular and individualistic cultures like to dance more. Listeners from more traditional cultures use music more for expressing values and cultural identity and they bond more frequently with their families over music. The two dimensions of musical functions seem systematically underpinned by listeners' gender and cultural background. We discuss the uses of music as behavioral expressions of affective and contemplative as well as personal social and sociocultural aspects in terms of affect proneness and cultural values.Article Citation - WoS: 5Citation - Scopus: 4Computer based classification of MR scans in first time applicant Alzheimer patients(Bentham Science Publ Ltd, 2012) Fatma Eksi Polat; Selçuk Orhan Demirel; Ömer Kitiş; Fatma Şimşek; Damla İşman Haznedaroǧlu; Kerry Lee Coburn; Emre Kumral; Ali Saffet Gönül; Simsek, Fatma; Kitis, Omer; Demirel, Selcuk Orhan; Gonul, Ali Saffet; Haznedaroglu, Damla Isman; Coburn, Kerry; Polat, FatmaIn this study we aimed to classify MR images for recognizing Alzheimer Disease (AD) in a group of patients who were recently diagnosed by clinical history and neuropsychiatric exams by using non-biased machine-learning techniques. T1 weighted MRI scans of 31 patients with probable AD and 31 age- and gender-matched cognitively normal elderly were analyzed with voxel-based morphometry and classified by support vector machine (SVM) a machine learning technique. SVM could differentiate patients from controls with accuracy of 74 % (sensitivity: 70 % and specificity: 77 %) when the whole brain was included the analyses. The classification accuracy was increased to 79 % (sensitivity: 65 % and specificity: 93 %) when the analyses restricted to hippocampus. Our results showed that SVM is a promising tool for diagnosis of AD but needed to be improved. © 2012 Bentham Science Publishers. © 2013 Elsevier B.V. All rights reserved., MEDLINE® is the source for the MeSH terms of this document.Article Citation - WoS: 5Citation - Scopus: 5Modeling the Effect of Mood on Dimensional Attention During Categorization(AMER PSYCHOLOGICAL ASSOC, 2013) Matthew T. Zivot; Andrew L. Cohen; Aycan Kapucu; Cohen, Andrew L.; Kapucu, Aycan; Zivot, Matthew T.Classification is a flexible process that can be affected by mood. The goal of this paper is to evaluate the idea that mood may modulate categorization behavior through an attentional weighting mechanism in which mood changes the attention afforded to different stimulus dimensions. In two experiments participants learn and are tested on categories while in a calm or sad mood. In Experiment 1 sad participants are faster to learn one- and two-dimensional category structures but show no advantage on a three-dimensional category structure. In Experiment 2 the generalized context model of categorization is used to measure dimensional weighting. The results suggest that sad participants have a narrower focus of attention but that the narrowing tends to be on diagnostic dimensions.Article Citation - WoS: 29Citation - Scopus: 39Depression anxiety and sexual satisfaction in breast cancer patients and their partners-Izmir oncology group study(Asian Pacific Organization for Cancer Prevention kyyoo@plaza.snu.ac.kr,, 2014) Ahmet T. Alacacioǧlu; Eda Ulger; Umut Ut Varol; Ibrahim Yildiz; Tarik Salman; Vedat Bayoglu; Ahmet Dirican; Lütfiye Demir; Murat Akyol; Yaşar Yildiz; Bayoglu, Vedat; Yildiz, Ibrahim; Ulger, Eda; Salman, Tarik; Varol, Umut; Alacacioglu, Ahmet; Tarhan, Mustafa OktayBackground: We aimed to investigate anxiety depression and sexual satisfaction levels and the effects of depression and anxiety upon the sexual satisfaction of Turkish breast cancer patients and their partners. Materials and Methods: Data were collected from one hundred breast cancer patients and their partners using three forms: one covering information about socio-demographic characteristics of the patients the Hospital Anxiety and Depression Scale (HADs) and the Golombok-Rust Inventory of Sexual Satisfaction (GRISS). Results: The frequencies avoidance and touch subscores were statistically significantly high in the patients. Among those with high anxiety scores the frequency communication satisfaction touch and anorgasmic subscale scores of GRISS were found to be significantly high. Among the partners whose anxiety scores were high only the premature ejaculation subscale was statistically significant. It was determined that for partners with higher depression scores the communication satisfaction avoidance premature ejaculation and erectile dysfunction subscores of GRISS were statistically higher compared to partners with lower depression scores. Conclusions: Patients' quality of life may be increased by taking precautions to reduce their and their partners' psychosocial and psychosexual concerns. © 2015 Elsevier B.V. All rights reserved.Article Citation - WoS: 40Citation - Scopus: 42Memory bias for negative emotional words in recognition memory is driven by effects of category membership(ROUTLEDGE JOURNALS TAYLOR & FRANCIS LTD, 2014) Corey N. White; Aycan Kapucu; Davide Bruno; Caren M. Rotello; Roger Ratcliff; White, Corey N.; Ratcliff, Roger; Kapucu, Aycan; Bruno, Davide; Rotello, Caren M.Recognition memory studies often find that emotional items are more likely than neutral items to be labelled as studied. Previous work suggests this bias is driven by increased memory strength/familiarity for emotional items. We explored strength and bias interpretations of this effect with the conjecture that emotional stimuli might seem more familiar because they share features with studied items from the same category. Categorical effects were manipulated in a recognition task by presenting lists with a small medium or large proportion of emotional words. The liberal memory bias for emotional words was only observed when a medium or large proportion of categorised words were presented in the lists. Similar though weaker effects were observed with categorised words that were not emotional (animal names). These results suggest that liberal memory bias for emotional items may be largely driven by effects of category membership.Article Citation - WoS: 68Citation - Scopus: 79How accurately do drivers evaluate their own driving behavior? An on-road observational study(Pergamon-Elsevier Science Ltd, 2014) Sonia Amado; Elvan Arıkan İyilikci; Gülin Kaça; Mehmet Koyuncu; Belgüzar Nilay Turkan; Kaca, Gulin; Koyuncu, Mehmet; Arikan, Elvan; Amado, Sonia; Turkan, B. NilaySelf-assessment of driving skills became a noteworthy research subject in traffic psychology since by knowing one's strenghts and weaknesses drivers can take an efficient compensatory action to moderate risk and to ensure safety in hazardous environments. The current study aims to investigate drivers' self-conception of their own driving skills and behavior in relation to expert evaluations of their actual driving by using naturalistic and systematic observation method during actual on-road driving session and to assess the different aspects of driving via comprehensive scales sensitive to different specific aspects of driving. 19-63 years old male participants (N = 158) attended an on-road driving session lasting approximately 80 min (45 km). During the driving session drivers' errors and violations were recorded by an expert observer. At the end of the driving session observers completed the driver evaluation questionnaire while drivers completed the driving self-evaluation questionnaire and Driver Behavior Questionnaire (DBQ). Low to moderate correlations between driver and observer evaluations of driving skills and behavior mainly on errors and violations of speed and traffic lights was found. Furthermore the robust finding that drivers evaluate their driving performance as better than the expert was replicated. Over-positive appraisal was higher among drivers with higher error/violation score and with the ones that were evaluated by the expert as "unsafe". We suggest that the traffic environment might be regulated by increasing feedback indicators of errors and violations which in turn might increase the insight into driving performance. Improving self-awareness by training and feedback sessions might play a key role for reducing the probability of risk in their driving activity.© 2013 Elsevier Ltd. All rights reserved. © 2013 Elsevier B.V. All rights reserved.Article Citation - WoS: 15Citation - Scopus: 14Analysis of the learning curve for robotic hysterectomy for benign gynaecological disease(John Wiley and Sons Ltd, 2014) Fatih Şendaǧ; Burak Zeybek; Ali Osman Akdemir; Banu Ozgurel; Kemal Öztekin; Akdemir, Ali; Ozgurel, Banu; Oztekin, Kemal; Zeybek, Burak; Sendag, FatihBackground: The objective was to evaluate the learning curve for performing a robotic hysterectomy to treat benign gynaecological disease. Methods: Thirty-six patients underwent robotic hysterectomy for benign indications. A systematic chart review of consecutive cases was conducted. The collected data included age BMI operating time set-up time docking time uterine weight blood loss intraoperative complications postoperative complications conversions to laparotomy and length of hospital stay. Results: The mean operating set-up and docking times were 169±54.5 52.9±12.4 and 7.8±7.6min respectively. The learning curve analysis revealed a decrease in both docking and operating times with both curves plateauing after case 9. Conclusions: The learning curve analysis revealed a decrease in docking time and operating time after case 9 suggesting that there might be a fast learning curve for experienced laparoscopic surgeons to master robotic hysterectomy and that the docking process does not have a significant negative influence on the overall operating time. © 2022 Elsevier B.V. All rights reserved.Article Citation - WoS: 54Citation - Scopus: 65Cultural Bases for Self-Evaluation: Seeing Oneself Positively in Different Cultural Contexts(SAGE Publications Inc. claims@sagepub.com, 2014) Maja Becker; Vivian L. Vignoles; Ellinor Owe; Matthew J. Easterbrook; Rupert James Brown; Peter Bevington Smith; Michael Harris Bond; Camillo Regalia; Claudia Manzi; Maria Brambilla; Easterbrook, Matthew J.; Vignoles, Vivian L.; Koller, Silvia H.; Brown, Rupert; Owe, Ellinor; Smith, Peter B.; Becker, MajaSeveral theories propose that self-esteem or positive self-regard results from fulfilling the value priorities of one's surrounding culture. Yet surprisingly little evidence exists for this assertion and theories differ about whether individuals must personally endorse the value priorities involved. We compared the influence of four bases for self-evaluation (controlling one's life doing one's duty benefitting others achieving social status) among 4852 adolescents across 20 cultural samples using an implicit within-person measurement technique to avoid cultural response biases. Cross-sectional and longitudinal analyses showed that participants generally derived feelings of self-esteem from all four bases but especially from those that were most consistent with the value priorities of others in their cultural context. Multilevel analyses confirmed that the bases of positive self-regard are sustained collectively: They are predictably moderated by culturally normative values but show little systematic variation with personally endorsed values. © 2014 by the Society for Personality and Social Psychology Inc. © 2019 Elsevier B.V. All rights reserved.
