Actual Pictures Research Articles

A multiscale computational framework for the development of spines in molluscan shells.

From mathematical models of growth to computer simulations of pigmentation, the study of shell formation has given rise to an abundant number of models, working at various scales. Yet, attempts to combine those models have remained sparse, due to the challenge of combining categorically different approaches. In this paper, we propose a framework to streamline the process of combining the molecular and tissue scales of shell formation. We choose these levels as a proxy to link the genotype level, which is better described by molecular models, and the phenotype level, which is better described by tissue-level mechanics. We also show how to connect observations on shell populations to the approach, resulting in collections of molecular parameters that may be associated with different populations of real shell specimens. The approach is as follows: we use a Quality-Diversity algorithm, a type of black-box optimization algorithm, to explore the range of concentration profiles emerging as solutions of a molecular model, and that define growth patterns for the mechanical model. At the same time, the mechanical model is simulated over a wide range of growth patterns, resulting in a variety of spine shapes. While time-consuming, these steps only need to be performed once and then function as look-up tables. Actual pictures of shell spines can then be matched against the list of existing spine shapes, yielding a potential growth pattern which, in turn, gives us matching molecular parameters. The framework is modular, such that models can be easily swapped without changing the overall working of the method. As a demonstration of the approach, we solve specific molecular and mechanical models, adapted from available theoretical studies on molluscan shells, and apply the multiscale framework to evaluate the characteristics of spines from three distinct populations of Turbo sazae.

ESL Vocabulary Teaching Strategies Used by Primary School Teachers in Sarawak

The core component in any language is its vocabulary and vocabulary instruction lays the framework for pupils to retrieve words successfully in listening, speaking, reading, and writing. The application of various techniques will encourage a more comprehensive and well-rounded method for teaching vocabulary. The goal of this study is to investigate the strategies employed by ESL teachers to teach vocabulary in primary schools through quantitative research design. The questionnaire was adapted from a study by AI Ameri (2013), where 16 items were selected, refined and used in this study to gather data from 30 primary school teachers teaching English in Sarawak. The data collected were analysed descriptively and the findings indicated that teachers use a variety of different techniques in the classroom rather than concentrating solely on one. Based on the results, the top three strategies used by teacher to teach vocabulary to their pupils are through group discussions or presentations, using actual objects or pictures and teaching pupils to infer a word's meaning from context. Hence, this study gave the researcher some understanding of the vocabulary teaching strategies utilised by teachers particularly in primary schools in Sarawak.

The creation of an online grocery store for experimental purposes: A pilot study

More households shop for groceries online than ever in the United States. Thus, changes in online grocery store environments can affect the nutritional quality of food choices on a large scale. In response, we built a simulated online grocery store for experimental purposes. This paper describes the development of an online grocery store that displays actual products, brands, sizes, prices, pictures, and ingredient lists sold in current online grocery stores in the United States. We ran a pilot study to evaluate this research tool by calculating adherence and accounting for participants’ experiences. We assessed the impact of game elements (point scoring and a scoreboard) and different budgets on the nutritional quality of the food bundle in the final shopping baskets of participants (n = 654). Participants in the treatment group saw the nutritional quality rating system illustrated for each food item as 1 to 5 “crowns.” Ordinary least square regressions compared the nutritional quality of the final shopping baskets between experimental groups. Participants who saw the game elements selected food bundles with 2.53 (CI 95% [0.72; 4.33], p = 0.006) more crowns in their final basket. Receiving a high budget ($50) increased the number of crowns by 2.78 (CI 95% [0.66;4.90], p = 0.010) compared to a low budget ($30). We found no significant interaction between the game intervention and budget level. Participants noted that the store was intuitive to navigate, had a high-quality interface, and easily found the products they often buy. The game elements encouraged shoppers to make healthier food choices. Our simulated grocery store can help researchers gain insight into online consumer behavior by testing interventions.

Medals, Rings, and Olympic Dreams: A Review Essay of Antonio Sotomayor and Cesar R. Torres, eds., Olimpismo

Medals, Rings, and Olympic Dreams: A Review Essay of Antonio Sotomayor and Cesar R. Torres, eds., <i>Olimpismo</i>

GabROP: Gabor Wavelets-Based CAD for Retinopathy of Prematurity Diagnosis via Convolutional Neural Networks.

One of the most serious and dangerous ocular problems in premature infants is retinopathy of prematurity (ROP), a proliferative vascular disease. Ophthalmologists can use automatic computer-assisted diagnostic (CAD) tools to help them make a safe, accurate, and low-cost diagnosis of ROP. All previous CAD tools for ROP diagnosis use the original fundus images. Unfortunately, learning the discriminative representation from ROP-related fundus images is difficult. Textural analysis techniques, such as Gabor wavelets (GW), can demonstrate significant texture information that can help artificial intelligence (AI) based models to improve diagnostic accuracy. In this paper, an effective and automated CAD tool, namely GabROP, based on GW and multiple deep learning (DL) models is proposed. Initially, GabROP analyzes fundus images using GW and generates several sets of GW images. Next, these sets of images are used to train three convolutional neural networks (CNNs) models independently. Additionally, the actual fundus pictures are used to build these networks. Using the discrete wavelet transform (DWT), texture features retrieved from every CNN trained with various sets of GW images are combined to create a textural-spectral-temporal demonstration. Afterward, for each CNN, these features are concatenated with spatial deep features obtained from the original fundus images. Finally, the previous concatenated features of all three CNN are incorporated using the discrete cosine transform (DCT) to lessen the size of features caused by the fusion process. The outcomes of GabROP show that it is accurate and efficient for ophthalmologists. Additionally, the effectiveness of GabROP is compared to recently developed ROP diagnostic techniques. Due to GabROP's superior performance compared to competing tools, ophthalmologists may be able to identify ROP more reliably and precisely, which could result in a reduction in diagnostic effort and examination time.

Realistic Rendering Algorithm for Bubble Generation and Motion in Water

A simplified bubble model and its solver optimization method are proposed to solve the problem of poor realistic simulation and complex solutions for bubble-motion behavior in water. Firstly, the internal velocity of the bubble was avoided, and the bubble model was established by only considering the net flux of the inlet and outlet bubbles, which reduced the computational complexity. The bubble constraint was then introduced into the motion equation of water, and the mixed Euler–Lagrangian method was used to solve it. FLIP particles tracked the bubble position, velocity, and deformation, and the mesh updated the vector field. At the same time, the viscosity term was simplified. Finally, it was combined with implicit incompressible SPH particles to achieve the purpose of volume correction. The experimental results show that the method in this paper can present a simulation effect of bubbles in water with rich detail and a realistic sense, whether compared with actual pictures or with existing methods.

Management of Children with Autism Spectrum Disorder using Picture Exchange Communication System - A Pilot Study

Aim: The aim of the study was to empirically assess the efficacy of Picture Exchange Communication System (PECS) in 5 children with autism spectrum disorder (ASD). This study was also intended to report parental feedback on using PECS with their children.Method: Purposive convenient sampling was used for this quasi-experimental study. Five nonverbal children who were diagnosed with mild to moderate autism spectrum disorder with a median age of 4.1 years were selected for the study. All the five participants who exhibited limited or no functional communication skills were recruited for the study. Exclusion criteria included presence of any syndrome or any significant medical conditions such as seizures. The pre-assessment and the post assessments after 24 sessions of PECS training were done using selected communicative function domains. Post therapy parental feedback was obtained concerning five categories which are communication intent, attention, behavioural issues, vocalization and ease of communication. Also frequency of initiation as observed in home settings was obtained by interview method.Results: Current study shows that all the children were able to use PECS spontaneously and independently without any physical prompts. Children were able to generalize PECS at home with ease and were able to initiate communication on their own using the pictures. The mothers of the children reported that they observed a drastic subsidence in children’s challenging behaviours and also improvement in their attention span. The findings from our study showed that PECS training is effective in improving the socio-communication skills in children with ASD who had restricted communication. On analysing the report, mothers stated that they were able to easily incorporate PECS at home with their child as it implements the use of actual pictures for communicative exchange. As PECS training paves the way for expression of the child’s needs, there was also a significant reduction in the children’s behavioural problems such as tantrums and other self-injurious behaviours.Conclusion: From this study, it can be concluded that PECS training is effective in improving various communicative temptations in socio-communication skills in children with ASD who have restricted communication. It was also noted that obtaining parental feedback periodically would help in generalization and it encourages the parents’ involvement in the child’s learning process.

Deepfake Video Detection Based on EfficientNet-V2 Network

As technology advances and society evolves, deep learning is becoming easier to operate. Many unscrupulous people are using deep learning technology to create fake pictures and fake videos that seriously endanger the stability of the country and society. Examples include faking politicians to make inappropriate statements, using face-swapping technology to spread false information, and creating fake videos to obtain money. In view of this social problem, based on the original fake face detection system, this paper proposes using a new network of EfficientNet-V2 to distinguish the authenticity of pictures and videos. Moreover, our method was used to deal with two current mainstream large-scale fake face datasets, and EfficientNet-V2 highlighted the superior performance of the new network by comparing the existing detection network with the actual training and testing results. Finally, based on improving the accuracy of the detection system in distinguishing real and fake faces, the actual pictures and videos are detected, and an excellent visualization effect is achieved.

Research on Defect Detection of Electric Energy Metering Box Based on YOLOv5

The manual inspection for the damage state of the electric energy metering box consumes a lot of time, the workload is large, and the data storage is difficult. In order to solve these problems, this paper proposes an automatic detection method for the damage state of the electric energy metering box based on the YOLOv5 algorithm. The actual metering box pictures taken by the operation and maintenance inspectors are used as the training set, LabelImage is used to annotate the data set, and YOLOv5s model is used to train the data set. The experimental results show that the method proposed in this paper can accurately mark the position of the metering box lid and accurately predict its damage state. The average accuracy reaches 98%, which can meet the requirements for the detection accuracy of the power metering box damage state in the operation and maintenance inspection work.

Student Attitude Towards the Application of Conceptual Metaphors to Teaching English Idioms

Contrary to the traditional view of idioms, cognitive linguists have demonstrated that the nature of idioms is not arbitrary and rote memorization is not the only way to learn them. The discovery of conceptual metaphor (CM) and its application to teaching idiomatic language in EFL has opened up a new path to more systematic and perceptive learning. However, the learners’ attitudes towards the employment of conceptual metaphors have yet to be thoroughly explored. To address this issue, the current study aimed to investigate the attitudes of 106 Vietnamese university students towards the CM-inspired instruction after a five-week treatment. Two research instruments were employed in this study: an attitudinal questionnaire and a semi-structured interview. The results of the study reveal that the CM-inspired instruction received positive feedback from the students, though the instruction itself exposed some shortcomings that need to be dealt with. To overcome its shortcomings, actual pictures and activities for structural elaboration are proposed to be used concurrently with the CM-inspired instruction.

BrazilClim: The overcoming of limitations of pre‐existing bioclimate data

AbstractSpecies distribution modelling has become instrumental in assessing the influence of environmental conditions on the occurrence or abundance of taxa. The set of environmental layers used for this purpose is a crucial aspect, for which different climate‐based (bioclimatic) datasets have been recently developed. These bioclimatic variables result from combinations of precipitation and temperatures surfaces. Here, we explored both the performance and possibility of improving some of the currently available bioclimatic databases, through an evaluation of the precipitation and temperatures surfaces used to generate them. For this purpose, we used a combination of statistic and graphic approaches. We focused on Brazil, not only due to its natural megadiversity, but also due to its continental size and orographic heterogeneity: an excellent ground for refining methods replicable elsewhere. We found a better match between the climatic data measured on‐field and Tropical Rainfall Measuring Mission (TRMM 3B43 v7) in the case of precipitation, and the surfaces provided by the National Oceanic and Atmospheric Administration (NOAA) in the case of temperatures, sources uncommonly used for species niche modelling. We gauge‐calibrated the best performing surfaces using machine‐learning algorithms and generated corrected surfaces that allowed us to create BrazilClim: a database of bioclimatic variables, based on improved primary surfaces, which will result in more assertive predicted distributions and more actual pictures of the species' ecological requirements for megadiverse Brazil, an approach replicable elsewhere. All primary and bioclimatic surfaces generated for this study may be freely downloaded.

Research on Splicing Technology of Large Format Three Dimensional Printing

With the development and maturity of 3D printing technology, there are new requirements for printing accuracy, clarity, and frame size. This article mainly focuses on large-format printing technology, using projection splicing technology to realize large-format digital light processing projection splicing 3D printing technology. Aiming at the problem of projection distortion, the article implements multiple digital light processing projection distortion correction; Aiming at the problem of image stitching, the article uses secondary Alpha edge fusion to realize image stitching, and gives an experimental environment to compare the results. According to the above steps, combined with actual pictures, a good splicing effect is achieved.

Traffic signal light detection and recognition based on canny operator

In this paper, five classical edge detection operators are compared, and then a traffic signal light detection and recognition scheme that can be used for intelligent connected vehicles is implemented. Firstly, the image to be processed is obtained by detecting the traffic signal light through the vision sensor. The image is preprocessed: the color space of the image is converted from RGB space to HSV space. Through the grayscale, histogram equalization, image binarization processing, using the morphological closure operation, the five operators are compared in noise sensitivity, positioning accuracy and signal-to-noise ratio, the Canny edge detection operator is selected for image edge detection, and the target recognition area is obtained. Finally, using the histogram drawn, the number of red, green and yellow pixel points in the histogram can be clearly counted, and the color with the largest number of pixel points can be identified as the color of the identified traffic signal light, and the identification of the traffic signal light can be completed. The actual pictures are simulated on the MATLAB, which verifies the feasibility of the proposed method of traffic signal light recognition method based on Canny operator in this paper, which can correctly identify the color of the traffic signal light.

Correlates of the willingness to consume insects: a meta-analysis

Although insects are a sustainable meat alternative, the willingness to consume (WTC) them remains generally low. We synthesised the effects of WTC correlates reported in 37 studies and also investigated the moderating effects of certain study characteristics. Across a large number of studies, affect-based factors, such as ‘food neophobia’, ‘disgust’ and ‘the expected unpleasant taste of insects’, were consistently strongly correlated with WTC (r̄=-0.33-0.55). Information-based factors, such as ‘the perceived sustainability of insects as food’ and ‘the perceived nutritiousness of insects as food’, also impacted WTC (r̄=0.32-0.55). However, the number of contributing studies in this regard was low. Curiosity appears to be relevant to WTC because ‘food sensation and innovation seeking’ (r̄=0.29) positively impacted WTC. ‘Age, education and gender’ were relatively unrelated to WTC (r̄=-0.14-0.00) across a large number of studies. Combatting affective barriers through gradual and/or early exposure – i.e. increasing the ‘familiarity with the concept of eating insects’ (r̄=0.10) and allowing consumers’ experiences with ‘insect consumption’ (r̄=0.35) to develop over time – will help foster entomophagy acceptance in the long run. In comparison, information-based interventions may have limited effectivity, but they can be implemented in the short term. As meta-regressions have shown, future researchers must consider whether the presentation of the edible insects has moderating effects, e.g. presenting specific as compared to non-specific products (β=-0.47) or actual products (β=-0.56) and pictures of such products (β=-0.55) as compared to mere verbal descriptions. Classical psychological entomophagy factors have been explored comprehensively, and research should also adopt a more market-oriented focus.

“Neural differences in expert guitarists during over-learned non-standard visuomotor mapping of abstract versus concrete information”

Using visual information to perform actions is a fundamental aspect of human behavior. Musicians commonly translate visual information into action using both concrete and abstract visual information. We exposed expert guitarists to four types of familiar visual depictions of action instruction including musical notation (very abstract), tablature (abstract), chord diagrams (more concrete), and actual pictures of guitars chords being formed (very concrete). These were shown during fMRI scanning as the guitarists formed the appropriate chords (as visually depicted) on a magnet safe guitar fret board with strings, or where they simply viewed the visual stimuli without an action. Whole brain contrasts revealed that the right precuneus was more active for abstract instruction while an occipito-insular circuit was more active for concrete instruction. The current findings highlight that the degree of over-learned visual abstraction is an important factor modulating visual-motor processing.

Exploring the Challenges of Tertiary Students in Non-Laboratory Courses After the First Year of Emergency Remote Teaching

&lt;p style="text-align: justify;"&gt;Shortly after the Coronavirus disease (COVID-19) pandemic began, studies on the challenges faced by tertiary students during Emergency Remote Teaching (ERT) became available. However, the data sets were harvested early, as many countries began implementing ERT in response to the pandemic in March 2020. Many recent studies have failed to distinguish between the challenges faced by students enrolled in the laboratory and non-laboratory courses. There is still a dearth of literature on the difficulties encountered by students enrolled in non-laboratory courses following the first year of ERT implementation. The purpose of this paper was to examine the various challenges faced by tertiary students enrolled in non-laboratory courses following the conclusion of the first year of ERT implementation. Contextualized in two state-owned higher education institutions in northern Luzon, this study employed a fundamental qualitative approach, with focus group discussions (FGDs) serving as the primary data collection technique. Five major themes emerged from the FGDs with 42 purposively selected tertiary students. These themes presented in the spider web illustration include (1) student-focused challenges, (2) instructional material-related challenges, (3) instructor-emanating challenges, (4) technology-related challenges, and (5) student support-related challenges. This article concludes that these issues must be dealt with immediately to facilitate the implementation of ERT in non-laboratory courses. These difficulties may also be dimensions of concerns about distance education, particularly in non-urban areas of the Philippines. The themes also provide some actual pictures of the student challenges in the initial year of ERT in college. This paper highlighted some implications for pedagogy and educational management, as well as future research directions.&lt;/p&gt;

Diffusion phenomenon of lunar soil particles under a plume in a vacuum environment by numerical simulation

During the landing of lunar probes on the surface of the Moon, lunar soil particles are lifted and diffused under the action of a plume. This study used three methods to numerically investigate the diffusion of lunar soil particles under a plume in a vacuum environment. First, an analytical solution of Fick's second law is used to obtain the motion results of lunar soil particles under the influence of diffusion in a steady state. Then, Fick's second law of finite-difference solution is used to obtain the motion results under the influence of diffusion. Finally, the discrete solution method of the mass- and energy-conservation equations is used to determine how the particles are affected by the plume in a transient state, including effects such as drag and lift, gravity, and temperature. The results show that lunar soil particles with small diameters diffuse more easily. After considering diffusion, the diffusion speeds of the 10- and 40-μm lunar soil particles are 3.6–4.5 times the speeds of those without diffusion; the spatial distribution range is increased by 1.4–4.5 times. The maximum lifting angle is increased by 1.0°–1.6°. However, lunar soil particles with diameters of 70 and 100 μm are not considerably affected by diffusion. At the same time, the introduction of the energy-loss coefficient showed that the impact of energy loss on the diffusion effect is substantial and that greater energy losses result in more diffusion-weakening trends. Compared with energy loss without considering the energy loss, diffusion speed is reduced by 10.2%–50.6%, occupied space is decreased by 18.3%–48.5%, and lifting angle is decreased by 18.8%–21.8%.Among the three methods, the mass- and energy-conservation method can fully consider the effects of particles and other factors. After considering the diffusion effect, the spatial distribution of lunar soil particles coheres better with the actual landing pictures, confirming that the impact of lunar soil particle diffusion on spatial distribution cannot be ignored.

Atlas of Ultrasound-Guided Procedures in Interventional Pain Management, 2nd ed

The first edition of this book was published in 2011, and I was lucky enough to have it on my shelf to compare it with the present one that is reviewed. Since 2011, an update was to keep up with the huge volume of new techniques and information about ultrasound-guided techniques for pain and regional anesthesia. This is a single-editor book with several well-known authors contributing who cover the wide range of subjects reviewed in the text. The volume is nicely presented with a color hard cover, and the pages are of good-quality paper, although not as bright as in the First Edition that made the ultrasound pictures look better. The book is organized in 7 parts, covering imaging in interventional pain and basics of ultrasound, spine sonoanatomy and ultrasound-guided spine injections, ultrasound-guided abdominal and pelvic blocks, ultrasound-guided peripheral blocks and catheters, diagnostic and musculoskeletal ultrasound, diagnostic neurosonology, and advanced and new applications of ultrasound. In total, there are 36 chapters, a few more than in the First Edition, spread over 334 pages. Nineteen out of the 36 chapters unfortunately are carbon copies of the old ones from the first edition and 8 years having passed between publication times. In most of the areas, there are many new references and a much larger paradigm that were left unexplained to the reader. Among these “old chapters,” however, the reader may find real jewels requiring no changes or perhaps minimal updates like spine sonoanatomy by Dr Bernard Moriggl, basics of ultrasound: pitfalls and limitations by Drs Vincent Chan and Anahi Perlas, and essential knobology for ultrasound-guided regional and interventional pain management by Drs Alan J. R. Macfarlane, Cyrus C. H. Tse, and Richard Brull. Some of the newly written chapters are outstanding like the one on ultrasound-guided upper extremity blocks by Jason McVicar, Sheila Riazi, and Anahi Perlas with excellent text and beautiful and well-explained figures, ultrasound-guided superficial trigeminal nerve blocks by David A. Spinner and Jonathan S. Kirschner, ultrasound-guided greater occipital nerve block by Bernhard Moriggl and Manfred Greher, ultrasound of peripheral nerves by Swati Deshmukh and Jonathan Samet, and, finally, occipital neuralgia: sonoanatomy and sonopathology of the occipital nerves by the editor Samer N. Narouze. Pictures and drawings explaining procedures are well presented with nice colors, but in some cases, it is intriguing and disappointing not to find actual pictures with the needle in the tissue despite the fact that the authors are experienced in these techniques and must have a good collection of nice images from their work in the last 8 years. Both for the newcomer in the field of ultrasound-guided pain management as well as for the seasoned practitioner, this second edition is an outstanding text from a leader in the field. Some chapters, as explained by the editor in the prologue, include excellent step-by step descriptions of the techniques. We hope the next edition will come with some missed procedures like trans quadratus lumborum block, erector spinae block, sympathetic blocks at the lumbar region, pectoralis nerve, and serratus plane blocks. Juan Francisco Asenjo, MD, FRCPCDepartment of AnesthesiaThe Montreal General HospitalMcGill University Health CentreMontreal, Quebec, Canada[email protected] Julia Jackson, BScDepartment of AnesthesiaThe Montreal General HospitalMcGill UniversityMontreal, Quebec, Canada

Contour recognition of roadheader cutting head based on shape matching

In this paper, a shape matching algorithm is presented to perform the cutting head recognition for roadheaders based on a binocular vision system installed on the machine. The shape descriptor is a simplified intersection angle of tangent lines which is firstly proposed on the basis of contour points’ spatial positions. It exhibits significant self-contained property and features describing capacity for both partial and whole shapes. To achieve the best match, the MVM algorithm was improved with skipping and multiple matching penalties to complete the multiple mapping and to skip existing outliers in sequences. More precisely, these advantages make the proposed algorithm less sensible to the local variations caused by varied views. Experimental results demonstrated that the proposed method outperforms existing ones with stronger robustness and higher accuracy. In actual pictures tests, the cutting head recognition rate reached 100% with spatial positioning errors under 2.2 cm, which met the requirements for accurate location in real time.

Simulation of tree growth for three almond cultivars with contrasting architecture with the L-ALMOND model

The L-PEACH and L-ALMOND models use L-systems to simulate the architectural development and carbohydrate dynamics (assimilation, transport, distribution, storage and remobilization) of growing peach and almond trees, respectively. The models were able to successfully simulate tree growth and development and produce realistic estimates of tree size, structure and productivity over several years after planting, but always only for a specific cultivar. We here show how L-ALMOND can be adapted to simulate the architectural growth of three cultivars (‘Nonpareil’, ‘Aldrich’, and ‘Winters’) differing in tree architecture after three steps for each cultivar: i) inclusion of specific shoot architectures for six types of shoots (watersprouts, long, medium-long, medium, medium-short, and small shoots). Branching patterns and flowering occurrence for each type of shoot were previously assessed by developing hidden semi-Markov statistical models based on field research. Spur morphology was the same. Very different patterns emerged of sylleptic shoot production from lateral meristems on watersprouts, long, and medium-long shoots. ‘Aldrich’ and ‘Winters’ produced many more sylleptic shoots than ‘Nonpareil’. No sylleptic shoot growth appeared from medium, medium-short, and small shoots in any cultivar; ii) definition of the type of shoot derived from a sylleptic shoot. In ‘Aldrich’ and ‘Winters’ most sylleptic shoots were spurs and short shoots, respectively, while in ‘Nonpareil’ their length varied widely (spurs, small, medium-short, and medium shoots); and iii) adjustment of a parameter to modify shoot bending to simulate differences in growth habit observed in the field. ‘Aldrich’ was more erect than ‘Winters’ and ‘Nonpareil’. After modifications, L-ALMOND 3-dimensional tree simulations were similar to actual pictures of field trees, demonstrating how different shoot architectures result in different tree architectures over time, and especially the role that sylleptic shoot production plays in determining final tree architecture in almond.