Elaborate Information Research Articles

Modeling of the Rainfall and R-Factor for Tocantins State, Brazil

ABSTRACT The state of Tocantins is inserted in the new Brazilian agricultural frontier and has shown enormous potential for expansion of the agricultural lands. However, there is a lack of more elaborate scientific information for better planning and guide agricultural activities, especially regarding the soil and water conservation. Tocantins has a relevant rainfall spatial variability and, consequently, rainfall erosivity. Thus, this work aimed to develop models to estimate the mean monthly and annual rainfall and means rainfall erosivity factor (R-factor) [...]

A Dual Convolution Network Using Dark Channel Prior for Image Smoke Classification

Through a comparative analysis, we confirm that the value of the dark channel pixels of the smoke image is higher than the non-smoke image. It means that the dark channel of the smoke image has more elaborate information of the smoke, which is of great benefit to our detailed feature extraction of smoke. On this background, we propose a dual convolution network using dark channel prior for image smoke classification (DarkC-DCN) for the image smoke classification. In DarkC-DCN, basing on the AlexNet, and through continuous structural improvement and optimization, we improve a detailed CNN to extract the detailed features of dark channel images. Similarly, to extract the general features in the image, we further design another residual network based on the AlexNet, which is the main framework of the entire network. To ascertain the robustness of the network, the two channels are trained separately for various inputs. In addition, we perform feature fusion before the common fully connected layer. In the experiment, we also add some non-smoke data similar to smoke in the public smoke data set for data expansion. The experimental results indicate that the model has a good performance in general. The accuracy value reaches 98.56%.

A Novel Network Scheduling Approach Based on Genetic Algorithm for Autonomous Underwater Vehicle Control

Autonomous Underwater Vehicle (AUV) is one type of important equipments for conducting ocean exploration missions. The AUV control system typically employs a common communication network to connect various function nodes such as Doppler meter, compass/inertial navigation unit, sonar, water depth sensor, main propulsion, and rudder motor. Each of these function nodes has its own information transmission requirements that need to be served by the limited bandwidth of the common communication network. In order to obtain a good control performance, an elaborate information transmission schedule in the communication network should be planned in such a way that all information transmission requirements in the AUV control system can be satisfied with as less network-induced delay and data packet dropout as possible. This paper proposes a novel network scheduling approach based on the Genetic Algorithm (GA) and the time-triggered architecture for meeting information transmission requirements in the Controller Area Network (CAN) of the AUV control system. The proposed network scheduling approach divides the whole transmission period into a serial of time slices with equal lengths, and defines a large cycle consisting of multiple time slices. For the periodical information transmission, the transmission schedule in one large cycle is determined by solving one nonlinear integer optimization problem with the Genetic Algorithm. This GA-based network scheduling approach maximizes the available bandwidth of each single time slice in all the periodic time slices of the whole schedule period, and aims to achieve a balanced information transmission in the CAN network. Meanwhile, the available bandwidth in each time slice of the whole schedule period is then allocated for the event-triggered information transmission. In this way, the proposed network scheduling approach satisfies the transmission requirements of both periodical and event-triggered information in the AUV. Finally, simulation experiments demonstrate the performance of the proposed GA-based network scheduling approach, and verify its performance improvement on an AUV heading motion control using TrueTime toolbox.

Stepped morphology on vicinal 3C- and 4H-SiC (0001) faces: A kinetic Monte Carlo study

Stepped morphologies on vicinal 3C- and 4H-SiC (0001) surfaces with the miscut toward [11¯00] or [112¯0] directions have been studied with a three-dimensional kinetic Monte Carlo model. In the model, a three-dimensional lattice mesh was established based on the crystal lattice of 3C-and 4H-SiC to fix the positions of atoms and interatomic bonding. Periodic boundary conditions were applied in the lateral direction while helicoidal boundary conditions were used in the direction of crystal growth. Events, such as adatoms attachment, detachment and interlayer transport at the step edges, and adatoms adsorption and diffusion on the terraces were considered in the model. Effects of Ehrlich–Schwoebel barriers at downward step edges and incorporation barriers at upwards step edges were also considered. Moreover, the atoms of silicon and carbon were treated as the minimal diffusing species independently to achieve more elaborate information for the behavior of atoms in the crystal surface. The simulation results showed that multiple-height steps were formed on the vicinal 4H-SiC (0001) surfaces, whereas single bilayer-height stepped morphologies were observed on the vicinal 3C-SiC (0001) surfaces. Furthermore, zigzag shaped edges were observed for both of 3C- and 4H-SiC (0001) surfaces with the miscut toward [112¯0] direction. At last, the formation mechanism of the stepped morphology was also analyzed.

Context retrieval and description benefits for recognition of unfamiliar faces.

Describing unfamiliar faces during or immediately after their presentation in a study phase can produce better recognition memory performance compared with a view-only control condition. We treated descriptions as elaborative information that is part of the study context and investigated how context retrieval influences recognition memory. Following general dual-process theories, we hypothesized that recollection would be used to recall descriptions and that description recall would influence recognition decisions, including the level of recognition confidence. In four experiments description conditions produced higher hit rates and higher levels of recognition confidence than control conditions. Participants recalled descriptive content on some trials, and this context retrieval was linked to an increase in the recognition confidence level. Repeating study faces in description conditions increased recognition scores, recognition confidence level, and context retrieval. Estimates of recollection from Yonelinas' (1994) dual-process signal detection ROCs were, on average, very close to the measures of context recall. Description conditions also produced higher estimates of familiarity. Finally, we found evidence that participants engaged in description activity in some ostensibly view-only trials. An emphasis on the information participants use in making their recognition decisions can advance understanding on description effects when descriptions are part of the study trial context. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Elaborate Refresh: A Fine Granularity Retention Management for Deep Submicron DRAMs

As the DRAM cell size continues to shrink, the proportion of leaky cells is increasing. As a result, the prior approaches, called retention aware refresh, which skip unnecessary refresh operations for non-leaky cells, are unable to skip as many refresh operations as before. The large granularity of the DRAM refresh mechanism makes this problem more serious. Specifically, even when there are only a small number of leaky cells in a particular retention group, that group is classified as a leaky group. Because of that, many non-leaky cells that also belong to that group are refreshed at an unnecessarily frequent rate. Since the granularity of the retention group is larger, this inefficiency becomes huge. To solve this problem, we propose a novel retention aware refresh approach called Elaborate Refresh, to reduce the granularity of the retention group further. The key idea of the Elaborate Refresh is to store leaky row addresses per each chip, and refresh different leaky row in each chip simultaneously. By doing so, Elaborate Refresh reduces the overhead of the leaky group refresh 16 times. In addition, Elaborate Refresh stores retention information in the DRAM chip, thus saving the refresh energy, even in the self-refresh mode when the memory controller cannot control the DRAM.

Crop Diversification in Rangpur Region

For the planning of future research and development elaborate information and a reliable database on existing cropping patterns, cropping intensity and crop diversity of a particular area are of prime importance for guiding policy makers, researchers, extensionists and development workers. A massive group work was accomplished over all 35 upazilas of Rangpur region during 2016 using pre-tested semistructured questionnaire with a view to document the existing cropping patterns, cropping intensity and crop diversity in the area. Boro−Fallow−T. Aman occupied the largest portion (53%) of net cropped area (NCA) with its distribution in all upazilas. The second largest area, 5% of NCA, was covered by Maize−Fallow−T. Aman which was spread out over 23 upazilas. Under the current investigation 134 cropping patterns were identified. The highest number of cropping patterns was identified 31 in Badarganj of Rangpur and the lowest was 10 in Razibpur of Kurigram district. The highest value of CDI was observed 0.991 in Razibpur upazila followed by 0.989 in Chilmari of Kurigram. The range of cropping intensity values was recorded 190-255%. The maximum value was for Gangachara upazila of Rangpur and minimum for Gaibandha sadar upazila. The overall CDI of Rangpur region was calculated 0.871 and the average cropping intensity at regional level was 219%.Bangladesh Rice j. 2017, 21(2): 255-271

Computed tomography cavernosography combined with volume rendering to observe venous leakage in young patients with erectile dysfunction.

To observe the venous leakage of penile veins through cavernosometry and cavernosography, using CT combined with three-dimensional volume rendering. 186 consecutive erectile dysfunction patients (20-40 years old) with suspected venous leakage diagnosed by clinicians were enrolled. All patients underwent intracavernous injection of vasoactive agents combined with Doppler ultrasound to identify venous leakage. Taking intracavernous injection combined with Doppler ultrasound as the "gold-standard", 47/186 (25.3%) patients had negative venous leakage, and 139/186 (74.7%) patients had positive venous leakage. CT cavernosography showed that 22/139 (15.8%) cases were isolated deep dorsal vein or crural vein leakage, and 117/139 (84.2%) cases were complex venous leakage. Three types of deep dorsal vein were seen: single-branch 42/139 (30.2.%), double-branch 45/139 (32.4%), and complex 31/139 (22.3%). Three types of prostatic venous plexus were seen: single-branch 26/139 (18.7%), multiple-branch 36/139 (25.9%), and plexus 39/139 (28.1%). A total of 166 crural veins were revealed in 129 patients. Crural veins had three origins: medial dorsal side (112/166, 67.5%), lateral ventral side (30/166, 18.1%) and the curs tip (24/166, 14.4%). To achieve the expected success rate of ligation surgery or endovascular embolization, candidates for the procedures should be carefully selected through CT cavernosography, which can provide elaborate images and information about the venous leakage. A modified evaluation method was used in this study to monitor the intracavernous pressure during examination. New classifications of the deep dorsal vein, prostatic venous plexus and crural vein are described in this study.

Türkiye‘de Orman, Park ve Fidanlıklarda Görülen Phytophthora Kök Çürüklüğü Hastalıkları ve Korunma Önlemleri

Phytophthora spp., Oomycetes sınıfında yer alan, tek ve çok yıllık bitkilerde kök, kök boğazı ve yaprak yanıklığı oluşturarak ani ölümlere yol açan önemli bir hastalık grubudur. Orman ağaçlarında ilk Phytophthora çalışması, Türkiye ormanlarının en yaygın ağacı olan meşelerde yapılmış ve ülkenin birçok bölgesinde, Phytophthora türlerinin bitkilerde kurumalar ve geriye ölüm belirtileri oluşturduğu, bu hastalıklara P. cinnamomi, P. citricola, P. cryptogea, P. gonapodyides, P. quercina, Phytophthora sp. 1 ve Phytophthora sp. 2‘ in neden olduğu, en yaygın türün ise P. quercina olduğu belirlenmiştir. Phytophthora türlerinin yaygın olarak görüldüğü ikinci orman ağacı kestanedir ve ülkemizin hemen hemen her yöresinde Phytophthora kök çürüklüklerine rastlanmıştır. Kestanede dört türün hastalık yaptığı, bunlardan P. cambivora‘nın daha çok iç bölgelerde bulunduğu, P. cinnamomi‘ nin ise ılıman yerlerde sahil bölgelerde bulunduğu, P. plurivora ve P. cryptogea‘ nın daha az oranda bulunduğu belirlenmiştir. Bu türlerden P. cambivora ve P. cryptogea, karaçamlarda da saptanmıştır. Diğer orman ağaçlarından Dişbudaklarda P. lacustris, Şimşirlerde P. plurivora, P. occultans; Atkestanelerinde P. citrophthora ve P. cactorum; Kokarağaçta P. nicotianae tespit edilmiştir. Ülkemizde incelenen birçok orman ve süs bitkisi üreten fidanlıklarda da Phytophthora hastalıkları belirlenmiştir. Değişik fidanlıklarda; P. cinnamomi, P. cryptogea, P. cactorum, P. citricola, P. megasperma ve P. syringae türlerinin hastalık oluşturduğu belirlenmiştir. Bu derlemede bu bulgular ile ilgili detaylı bilgi sunulmuştur.

Considerations for the Development of Mobile Phone Apps to Support Diabetes Self-Management: Systematic Review.

BackgroundThere is increased research interest in the use of mobile phone apps to support diabetes management. However, there are divergent views on what constitute the minimum standards for inclusion in the development of mobile phone apps. Mobile phone apps require an evidence-based approach to development which will consequently impact on their effectiveness. Therefore, comprehensive information on developmental considerations could help designers and researchers to develop innovative and effective patient-centered self-management mobile phone apps for diabetes patients.ObjectiveThis systematic review examined the developmental considerations adopted in trials that engaged mobile phone applications for diabetes self-management.MethodsA comprehensive search strategy was implemented across 5 electronic databases; Medline, Scopus, Social Science Citation Index, the Cochrane Central Register of Controlled Trials and Cumulative Index of Nursing and Allied Health Literature (CINALHL) and supplemented by reference list from identified studies. Study quality was evaluated using the Joanna Briggs Critical appraisal checklist for trials. Information on developmental factors (health behavioral theory, functionality, pilot testing, user and clinical expert involvements, data privacy and app security) were assessed across experimental studies using a template developed for the review.ResultsA total of 11 studies (10 randomized controlled trials and 1 quasi-experimental trial) that fitted the inclusion criteria were identified. All the included studies had the functionality of self-monitoring of blood glucose. However, only some of them included functions for data analytics (7/11, 63.6%), education (6/11, 54.5%) and reminder (6/11, 54.5%). There were 5/11(45.5%) studies with significantly improved glycosylated hemoglobin in the intervention groups where educational functionality was present in the apps used in the 5 trials. Only 1 (1/11, 9.1%) study considered health behavioral theory and user involvement, while 2 (2/11, 18.1%) other studies reported the involvement of clinical experts in the development of their apps. There were 4 (4/11, 36.4%) studies which referred to data security and privacy considerations during their app development while 7 (7/12, 63.6%) studies provided information on pilot testing of apps before use in the full trial. Overall, none of the studies provided information on all developmental factors assessed in the review.ConclusionsThere is a lack of elaborate and detailed information in the literature regarding the factors considered in the development of apps used as interventions for diabetes self-management. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of practical and user-friendly self-management apps that can enhance the quality of life for diabetes patients.

A novel rail defect detection method based on undecimated lifting wavelet packet transform and Shannon entropy-improved adaptive line enhancer

Acoustic emission (AE) technology is sensitive to subliminal rail defects, however strong wheel-rail contact rolling noise under high-speed condition has gravely impeded detecting of rail defects using traditional denoising methods. In this context, the paper develops an adaptive detection method for rail cracks, which combines multiresolution analysis with an improved adaptive line enhancer (ALE). To obtain elaborate multiresolution information of transient crack signals with low computational cost, lifting scheme-based undecimated wavelet packet transform is adopted. In order to feature the impulsive property of crack signals, a Shannon entropy-improved ALE is proposed as a signal enhancing approach, where Shannon entropy is introduced to improve the cost function. Then a rail defect detection plan based on the proposed method for high-speed condition is put forward. From theoretical analysis and experimental verification, it is demonstrated that the proposed method has superior performance in enhancing the rail defect AE signal and reducing the strong background noise, offering an effective multiresolution approach for rail defect detection under high-speed and strong-noise condition.

The structural effects of affective and cognitive elaboration in formation of customer–brand relationship

ABSTRACTCustomer–brand relationships exist in many tourism categories; however, these relationships are rarely specified in the integrated resort category. Because an integrated resort consists of various types of travel services, customers form their attitudes based on their pleasure and sensory experiences as well as their cognitively oriented travel activities. This research suggests a model depicting both affective and cognitive elaboration processes that lead to building customer–brand relationship. The findings revealed that customers’ affective (e.g. affective brand experience) and cognitive (e.g. intellectual brand experience) elaborations are elicited concurrently in the formation of brand relationship quality and behavior intention toward an integrated resort brand. The novelty of this study is to provide the understanding of (1) an integrated model of cognitive and affective elaboration of brand experience processing; and (2) a mechanism of brand experience, brand relationship quality, and behavioral outcome in the integrated resort industry.

An integrated clinical and genomic information system for cancer precision medicine

BackgroundIncreasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient’s genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly.ResultsHere, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data.ConclusionsOur CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.

Cross-level impact of team goal orientation and individual goal orientation on individual creativity

AbstractThis study explored how individual and team-level goal orientation influence individual creativity in a work setting. By creating a cross-level theoretical framework, we tested 562 members of 81 teams currently working in various companies in China. The study analyzed the relationships between individual goal orientation, team goal orientation, and individual creativity from cross-level perspective linked by motivated information processing theory. Applying multilevel research method and hierarchical-level modeling, we found that team learning goal orientation and individual learning goal orientation influence individual creativity through different information activities at their own levels. Moreover, team learning goal orientation has a positive and team performance-avoidance goal orientation has a negative effect on individual creativity through team information exchange, while individual learning goal orientation poses a positive effect on individual creativity through individual information elaboration. In conclusion, it was indicated that team members tend to elaborate more work-related information when teams are more learning-orientated. Conversely, team members do not tend to elaborate information when their team has higher performance-avoidance goal orientation.

Transient Simulation Research on Automobile Aerodynamic Lift Based on LBM Method

In order to improve the limitation of steady-state automobile aerodynamic lift characteristics in finite volume method, the Lattice Boltzmann Method (LBM) was conducted on transient simulation of automobile aerodynamic lift. This proposed method utilized adaptive wake refinement feature to obtain a series of regular fluid particles for macroscopic fluid and combined large eddy simulation (LES) with wale-viscosity model to study the transient characteristics of automobile aerodynamic lift. In this numerical investigation, using the international standard automobile MIRA model, the temporal and spatial characteristics of rear velocity field and vorticity field were analyzed, whose results had agreement with the wind tunnel test data. It was showed that the elaborate information of flow field around the car-body and the aerodynamic lift could be more accurately described. A pair of asymmetric non-periodical and inward twisting rear vortexes in the car rear flow field was found, while it squeezed and dragged each other in different eddy scales. This result also indicated the aerodynamic lift to oscillate in a certain amplitude scope, markedly different from the simulated result of steady state automobile aerodynamic lift, which is more close to real driving conditions. DOI: http://dx.doi.org/10.5755/j01.mech.23.6.19847

Determination of free steroidal compounds in vegetable oils by comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry

A method based on comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC × GC-TOF/MS) was developed to analyze steroidal compounds in vegetable oils, which could provide better separation and higher sensitivity than conventional one dimensional gas chromatography, and allowed determination of 31 sterols and triterpene alcohols in one injection. Furthermore, the approach also permitted separation and detection of small amounts of other compounds (may be steroidal compounds whose molecular structures have not been confirmed), which were obscured in the lower-resolution single-column technique. With the help of the GC × GC system, a more elaborate and complete information regarding the distributions and concentrations of free phytosterols and triterpene alcohols in safflower seed oil, soybean oil, rapeseed oil, sunflower seed oil and peanut oil were obtained. The proposed method could potentially open a new opportunity for the more in-depth knowledge of the steroidal compounds of vegetable oils.

Digital Learning As Enhanced Learning Processing? Cognitive Evidence for New insight of Smart Learning.

Large use of technology improved quality of life across aging and favoring the development of digital skills. Digital skills can be considered an enhancing to human cognitive activities. New research trend is about the impact of the technology in the elaboration information processing of the children. We wanted to analyze the influence of technology in early age evaluating the impact on cognition. We investigated the performance of a sample composed of n. 191 children in school age distributed in two groups as users: high digital users and low digital users. We measured the verbal and visuoperceptual cognitive performance of children by n. 8 standardized psychological tests and ad hoc self-report questionnaire. Results have evidenced the influence of digital exposition on cognitive development: the cognitive performance is looked enhanced and better developed: high digital users performed better in naming, semantic, visual memory and logical reasoning tasks. Our finding confirms the data present in literature and suggests the strong impact of the technology using not only in the social, educational and quality of life of the people, but also it outlines the functionality and the effect of the digital exposition in early age; increased cognitive abilities of the children tailor digital skilled generation with enhanced cognitive processing toward to smart learning.

Profiling teachers based on their professional attitudes towards teaching responsible research and innovation

In order to facilitate policy-driven reforms in science education, it is important to understand how teaching innovations diffuse among teachers and how that adoption process can be catalysed. Little is known about the set of attitudes that makes teachers early or late adopters. In this study, the Concerns-Based Adoption Model (C-BAM) was employed as a framework for analysing teachers’ interests, concerns, worries and enthusiasm. We argue that the questionnaire typically used with C-BAM suffers from a ceiling effect and has unbalanced variables. An improved version of the questionnaire was developed and implemented in the project IRRESISTIBLE with 180 science teachers in ten countries at all school levels. The case of educational innovation in this project was Responsible Research and Innovation (RRI), a concept offered by the EU for science education to orient towards socially and ethically sensitive and inclusive processes of science and technology. Using cluster analysis we found four concern profile types: the Carefree, the Pragmatic, the Uncertain and the Worried. With their relatively high positive interests, the Carefree and the Pragmatic profile types are most likely to be early adopters. The high number of Uncertain teachers calls for better conceptualization of RRI in the school context. Furthermore, teacher professional development and additional resources are needed if this innovation is to be diffused widely across European schools. The improved questionnaire provided elaborate information on teachers’ concerns and interests, and could help in understanding and facilitating other top-down educational reforms as well.

“I like the sound of that!” Wine descriptions influence consumers' expectations, liking, emotions and willingness to pay for Australian white wines

This study investigated how information, typically presented on wine back-labels or wine company websites, influences consumers' expected liking, informed liking, wine-evoked emotions and willingness to pay for Australian white wines. Regular white wine consumers (n=126) evaluated the same set of three commercially available white wines (mono-varietal Chardonnay, Riesling, Sauvignon Blanc) under three information levels. Session 1, blind tasting (no information provided) and Session 2, informed tasting (held at least 1week later) with both basic (sensory description of the wines) and elaborate (sensory plus high wine quality and favourable winery information) descriptions followed by liking, wine-evoked emotions (measured with the Australian Wine Evoked Emotions Lexicon (AWEEL)) and willingness to pay evaluations. Before tasting the wine in session 2, consumers also rated expected liking.Results showed that information level had a significant effect on all investigated variables. The elaborate information level evoked higher expectations before tasting the wines, plus resulted in higher liking ratings, elicitation of more intense positive (e.g. contented, happy and warm-hearted) and less intense negative emotions (e.g. embarrassed and unfulfilled), and a substantial increase in willingness to pay after tasting the wines compared to the blind condition, with the basic condition ranging in-between. These results were consistent across the three wine samples.Furthermore, if the liking rating after tasting the wines matched the expected liking or exceeded the expectations by 1 point on a 9-point hedonic scale, participants felt the most intense positive emotions and the least intense negative emotions. Whereas, if the expectations were not met or the actual liking exceeded the expectations by >2 points, participants felt less intense positive and more intense negative emotions. This highlights not only the importance of well written and accurate wine descriptions, but also that information can influence consumers' wine drinking experience and behaviour.

Differentiation of subsequent memory effects between retrieval practice and elaborative study

Retrieval practice enhances memory retention more than re-studying. The underlying mechanisms of this retrieval practice effect have remained widely unclear. According to the elaborative retrieval hypothesis, activation of elaborative information occurs to a larger extent during testing than re-studying. In contrast, the episodic context account has suggested that recollecting prior episodic information (especially the temporal context) contributes to memory retention. To adjudicate the distinction between these two accounts, the present study used the classical retrieval practice effect paradigm to compare retrieval practice and elaborative study. In an initial behavioral experiment, retrieval practice produced greater retention than elaboration and re-studying in a one-week delayed test. In a subsequent event-related potential (ERP) experiment, retrieval practice resulted in reliably superior accuracy in the delayed test compared to elaborative study. In the ERPs, a frontally distributed subsequent memory effect (SME), starting at 300ms, occurred in the elaborative study condition, but not in the retrieval practice condition. A parietal SME emerged in the retrieval practice condition from 500 to 700ms, but was absent in the elaborative study condition. After 700ms, a late SME was present in the retrieval practice condition, but not in the elaborative study condition. Moreover, SMEs lasted longer in retrieval practice than in elaboration. The frontal SME in the elaborative study condition might be related to semantic processing or working memory-based elaboration, whereas the parietal and widespread SME in the retrieval practice condition might be associated with episodic recollection processes. These findings contradict the elaborative retrieval theory, and suggest that contextual recollection rather than activation of semantic information contributes to the retrieval practice effect, supporting the episodic context account.