Pyramidal Approach Research Articles

The Training Intensity Distribution of Marathon Runners Across Performance Levels.

The training characteristics and training intensity distribution (TID) of elite athletes have been extensively studied, but a comprehensive analysis of the TID across runners from different performance levels is lacking. Training sessions from the 16weeks preceding 151,813 marathons completed by 119,452 runners were analysed. The TID was quantified using a three-zone approach (Z1, Z2 and Z3), where critical speed defined the boundary between Z2 and Z3, and the transition between Z1 and Z2 was assumed to occur at 82.3% of critical speed. Training characteristics and TID were reported based on marathon finish time. Training volume across all runners was 45.1 ± 26.4km·week-1, but the fastest runners within the dataset (marathon time 120-150min) accumulated > three times more volume than slower runners. The amount of training time completed in Z2 and Z3 running remained relatively stable across performance levels, but the proportion of Z1 was higher in progressively faster groups. The most common TID approach was pyramidal, adopted by > 80% of runners with the fastest marathon times. There were strong, negative correlations (p < 0.01, R2 ≥ 0.90) between marathon time and markers of training volume, and the proportion of training volume completed in Z1. However, the proportions of training completed in Z2 and Z3 were correlated (p < 0.01, R2 ≥ 0.85) with slower marathon times. The fastest runners in this dataset featured large training volumes, achieved primarily by increasing training volume in Z1. Marathon runners adopted a pyramidal TID approach, and the prevalence of pyramidal TID increased in the fastest runners.

FP-GCN: Frequency Pyramid Graph Convolutional Network for Enhancing Pathological Gait Classification.

Gait, a manifestation of one's walking pattern, intricately reflects the harmonious interplay of various bodily systems, offering valuable insights into an individual's health status. However, the current study has shortcomings in the extraction of temporal and spatial dependencies in joint motion, resulting in inefficiencies in pathological gait classification. In this paper, we propose a Frequency Pyramid Graph Convolutional Network (FP-GCN), advocating to complement temporal analysis and further enhance spatial feature extraction. specifically, a spectral decomposition component is adopted to extract gait data with different time frames, which can enhance the detection of rhythmic patterns and velocity variations in human gait and allow a detailed analysis of the temporal features. Furthermore, a novel pyramidal feature extraction approach is developed to analyze the inter-sensor dependencies, which can integrate features from different pathways, enhancing both temporal and spatial feature extraction. Our experimentation on diverse datasets demonstrates the effectiveness of our approach. Notably, FP-GCN achieves an impressive accuracy of 98.78% on public datasets and 96.54% on proprietary data, surpassing existing methodologies and underscoring its potential for advancing pathological gait classification. In summary, our innovative FP-GCN contributes to advancing feature extraction and pathological gait recognition, which may offer potential advancements in healthcare provisions, especially in regions with limited access to medical resources and in home-care environments. This work lays the foundation for further exploration and underscores the importance of remote health monitoring, diagnosis, and personalized interventions.

Motion correction of 3D dynamic contrast-enhanced ultrasound imaging without anatomical B-Mode images: Pilot evaluation in eight patients.

Dynamic contrast-enhanced ultrasound (DCE-US) is highly susceptible to motion artifacts arising from patient movement, respiration, and operator handling and experience. Motion artifacts can be especially problematic in the context of perfusion quantification. In conventional 2D DCE-US, motion correction (MC) algorithms take advantage of accompanying side-by-side anatomical B-Mode images that contain time-stable features. However, current commercial models of 3D DCE-US do not provide side-by-side B-Mode images, which makes MC challenging. This work introduces a novel MC algorithm for 3D DCE-US and assesses its efficacy when handling clinical data sets. In brief, the algorithm uses a pyramidal approach whereby short temporal windows consisting of three consecutive frames are created to perform local registrations, which are then registered to a master reference derived from a weighted average of all frames. We applied the algorithm to imaging studies from eight patients with metastatic lesions in the liver and assessed improvements in original versus motion corrected 3D DCE-US cine using: (i) frame-to-frame volumetric overlap of segmented lesions, (ii) normalized correlation coefficient (NCC) between frames (similarity analysis), and (iii) sum of squared errors (SSE), root-mean-squared error (RMSE), and r-squared (R2) quality-of-fit from fitted time-intensity curves (TIC) extracted from a segmented lesion. We noted improvements in frame-to-frame lesion overlap across all patients, from 68%±13% without correction to 83%±3% with MC (p=0.023). Frame-to-frame similarity as assessed by NCC also improved on two different sets of time points from 0.694±0.057 (original cine) to 0.862±0.049 (corresponding MC cine) and 0.723±0.066 to 0.886±0.036 (p ≤ 0.001 for both). TIC analysis displayed a significant decrease in RMSE (p=0.018) and a significant increase in R2 goodness-of-fit (p=0.029) for the patient cohort. Overall, results suggest decreases in 3D DCE-US motion after applying the proposed algorithm.

A Review of Community Awareness for Colorectal Cancer Screening and Prevention in North and Central Asian Countries.

Colorectal cancer (CRC) incidence and mortality rates are increasing in low- and middle-income countries (LMIC), including North and Central Asian countries (NCAC). Screening and risk factor reduction can aid in the prevention of colorectal cancer, but communities lack awareness of these screening programs. The review assessed community awareness about CRC screening and prevention in NCAC to facilitate cancer control policies. Study type and methods: For this scoping review, we searched PubMed/Medline, Embase, and the Cochrane Library for articles on community awareness about CRC screening and prevention in NCAC according to inclusion and exclusion criteria. Eight of 677 articles from five of the 15 NCAC countries met the criteria. Most of the studies utilized a survey design. The results indicated low awareness of the availability of CRC screening and poor knowledge of CRC symptoms. Knowledge of CRC screening modalities was also inadequate. Some countries also lack CRC screening programs. Community unawareness is a significant barrier to screening program utilization and sustenance. Community health awareness programs (CHAP) are needed to improve the uptake of CRC screening in NCAC. The NCAC should include CHAP as an integral component of the CRC control plan. Long-term cancer control in LMICcould be adapted using the step-ladder pyramidal approach.

Training Periodization, Methods, Intensity Distribution, and Volume in Highly Trained and Elite Distance Runners: A Systematic Review.

This review aimed to determine (1)performance and training characteristics such as training intensity distribution (TID), volume, periodization, and methods in highly trained/elite distance runners and (2)differences in training volume and TID between event distances in highly trained/elite distance runners. A systematic review of the literature was carried out using the PubMed/MEDLINE, Scopus, and Web of Science databases. Ten articles met the inclusion criteria. Highly trained/elite distance runners typically follow a pyramidal TID approach, characterized by a decreasing training volume from zone 1 (at or below speed at first ventilatory/lactate threshold [LT]) to zone 2 (between speeds associated with either both ventilatory thresholds or 2 and 4 mmol·L-1 LTs [vLT1 and vLT2, respectively]) and zone 3 (speed above vVT2/vLT2). Continuous-tempo runs or interval training sessions at vLT2 in zone 2 (ie,medium and long aerobic intervals) and those in zone 3 (ie,anaerobic or short-interval training) were both used at least once per week each in elite runners, and they were used to increase the number of either vLT2 or z3 sessions to adopt either a pyramidal or a polarized approach, respectively. More pyramidal- and polarized-oriented approaches were used by marathoners and 1500-m runners, respectively. Highly trained and elite middle- and long-distance runners are encouraged to adopt a traditional periodization pattern with a hard day-easy day basis, consisting in a shift from a pyramidal TID used during the preparatory and precompetitive periods toward a polarized TID during the competitive period.

A new signal processing-based islanding detection method using pyramidal algorithm with undecimated wavelet transform for distributed generators of hydrogen energy

Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match.

A Study of the Guidelines for the Planning and Design of Circular Buildings

Circular building is one of the key turning points in the movement of the construction industry towards sustainable development. It is a “circulation” and “human” idea aimed at balancing the construction and design of the residential environment with the responsibility and values of environmental resources and ecology. This study was focused on the formulation of planning and design guidelines that comply with the current circular building centred economy. Input from industry operatives was collected using semi-structural interviews and a pyramidal approach was employed using logical reasoning to set up planning and design objectives as well as specifications in 4 dimensions covering 12 items. The results provide substantial references for the promotion of current environmental codes compliant with circular building. They can also be used to shape up resource circulation in the construction industry, and help to meet the many needs of sustainable development in the planning and design of circular buildings.

A Study of the Guidelines for the Planning and Design of Circular Buildings

Circular building is one of the key turning points in the movement of the construction industry towards sustainable development. It is a “circulation” and “human” idea aimed at balancing the construction and design of the residential environment with the responsibility and values of environmental resources and ecology. This study was focused on the formulation of planning and design guidelines that comply with the current circular building centred economy. Input from industry operatives was collected using semi-structural interviews and a pyramidal approach was employed using logical reasoning to set up planning and design objectives as well as specifications in 4 dimensions covering 12 items. The results provide substantial references for the promotion of current environmental codes compliant with circular building. They can also be used to shape up resource circulation in the construction industry, and help to meet the many needs of sustainable development in the planning and design of circular buildings.

A Methodology for Flexible Implementation of Collaborative Robots in Smart Manufacturing Systems

Small-scale production is relying more and more on personalization and flexibility as an innovation key for success in response to market needs such as diversification of consumer preferences and/or greater regulatory pressure. This can be possible thanks to assembly lines dynamically adaptable to new production requirements, easily reconfigurable and reprogrammable to any change in the production line. In such new automated production lines, where traditional automation is not applicable, human and robot collaboration can be established, giving birth to a kind of industrial craftsmanship. The idea at the base of this work is to take advantage of collaborative robotics by using the robots as other generic industrial tools. To overcome the need of complex programming, identified in the literature as one of the main issues preventing cobot diffusion into industrial environments, the paper proposes an approach for simplifying the programming process while still maintaining high flexibility through a pyramidal parametrized approach exploiting cobot collaborative features. An Interactive Refinement Programming procedure is described and validated through a real test case performed as a pilot in the Building Automation department of ABB in Vittuone (Milan, Italy). The key novel ingredients in this approach are a first translation phase, carried out by engineers of production processes who convert the sequence of assembly operations into a preliminary code built as a sequence of robot operations, followed by an on-line correction carried out by non-expert users who can interact with the machine to define the input parameters to make the robotic code runnable. The users in this second step do not need any competence in programming robotic code. Moreover, from an economic point of view, a standardized way of assessing the convenience of the robotic investment is proposed. Both economic and technical results highlight improvements in comparison to the traditional automation approach, demonstrating the possibility to open new further opportunities for collaborative robots when small/medium batch sizes are involved.

Simulation and experimental testing of a bolted carbon-aluminium hybrid wingbox assembly under thermal loads

On the last decades, the aeronatical industry has increased the use of Carbon Fibre Reinforced Polymer matrix composites (CFRP), and at the same time, has kept the use of conventional metals. This has led to the presence of hybrid assemblies in the wingbox, fuselage, etc. Due to their high stiffness and strength, as well as the ease to dissasemble and repair, these assemblies are usually bolted. During its usage, an aircraft is subjected to large thermal jumps (the temperature difference between a landed aircraft and a flying one can reach 140 &ordm;C). Because of the presence of hybrid bolted joints, the materials of the joint undergo different thermal expansion/contraction, which cause significant thermal stresses altering the mechanical behaviour of the joint. Framed in the aeronautical Clean Sky 2 project &lsquo;INNOHYBOX&rsquo;, this work studies the behaviour of hybrid bolted joints subjected to thermal loads, both numerically and experimentally, following a pyramidal approach. At the coupon level, a hybrid carbon-aluminium single-lap shear specimen with one bolt was used to comprehend and characterise its behaviour under thermal loads. At the substructural level, a subcomponent representative of a wingbox was tested under thermal conditions. Finally, a full wingbox was tested. Furthermore, a computationally efficient finite element model was developed to simulate the complex behaviour of these type of joints without comprimsing the computational cost. The numerical predictions correlate favourably against the experimental data.

Analysis of competitiveness and economic profit of the confectionary sector in Kazakhstan and its comparison with Czech Republic data

Measuring competitiveness in post-communist countries in Central Asia is challenging. Many well-known metrics fail to warn bankruptcy risks sufficiently early or at all. This study uses metrics of the Altman z-score, Taffler z-score, IN99, IN01, IN05, and creditworthiness models to assess bankruptcy likelihood and financial performance of local and foreign confectionery companies operating in Kazakhstan during 2007-2018. These companies are Roshen, KDV Yaskino, Konti, Rakhat, and Bayan Sulu. The IN bankruptcy and creditworthiness models are considered in this study because they are found to be more appropriate for post-communist countries. Compared to the well known Altman or Taffler z-score models, they better suit the events and corporate situations peculiar to these countries. The benchmarking INFA system, involving a pyramidal approach developed for Czech companies, provides the economic-value-added (EVA) and component indicators to analyze competitiveness. This study also compares the performance of Kazakhstan companies with Nestlé Czechia and the Czech food industry. The objective is to analyze company competitiveness, bankruptcy probability, and ability to create value. Results show the effectiveness of INFA in analyzing competitiveness and the applicability of IN models to companies from Kazakhstan, Russia, Ukraine, and the Czech Republic.

Combined loadings after medium velocity impact on large CFRP laminated plates: Discrete ply model simulations

To decrease development costs of aeronautical composite structures, industrials and academic researchers are turning to “virtual testing” methods. To help achieve this objective, a new methodology has been developed at the Institut Clément Ader. It is based on a complex loading test rig for technological specimens (more representative than the usual level of coupons) and the Discrete Ply Model (DPM), a model allowing the main damage occurring in composite structures to be simulated. This research focuses on the combined loading of CFRP plates after impact. In a previous work, plates were experimentally impacted and loaded after the impact in the VERTEX test rig and a methodology to transfer boundary conditions to the numerical model was validated using a simple model without damage. In the work presented here, the DPM was used to simulate both the impact and the complex loading after impact tests. Numerical results and experimental results showed satisfactory correlation. The research undertaken demonstrates that the impact damage has very little influence when the tests are performed at larger scales than coupons. It is therefore paramount to use a pyramidal approach to design and test composite structures, in order to avoid oversizing.

A Review of the Components, Outcomes, and Cultural Responsiveness of the Pyramidal Parent Training Literature

Parental involvement is a cornerstone of success in supporting children with behavioral differences. However, having professionals provide intensive training to all parents in need of assistance is unattainable in many areas. The pyramidal parent training approach, where parents train other parents after first being trained by experts, supports generalization, collaboration, and makes training accessible in places where professional services are not available. A literature review was conducted to determine the scope of research on pyramidal parent training for families with children with ASD or another developmental disability. Eight relevant articles and one thesis were found. This research synthesized their training components, settings, foci, participants, designs, outcomes, social validity, and cultural responsiveness. Despite the many differences between the studies, two distinct forms of pyramidal parent training were identified: (1) Parent Training within a Family and (2) Parent Training among Families. The results show that regardless of the model, parent participants increased their skill acquisition to a similar degree whether trained by a professional or another parent. However, limited data were presented on the changes in the children’s behaviors and shortcomings were found in the areas of outcomes, generalization, maintenance, and cultural responsiveness.

A cross-country review on energy efficiency drivers

Energy efficiency remains as the main mitigation factor to slow down the growth of energy consumption and related CO2 emissions, undoubtedly the major responsible for climate change. Gaining insights into the driving forces that make efficiency change is a keystone to define energy policies and examine pathways to sustainable development. To this aim, this paper proposes a pyramidal approach for the analysis and decomposition of energy intensity, the main global efficiency indicator, using the LMDI method. First, the effects related to supply and demand sides of the energy system are separated in Primary Energy Factor and final energy intensity, respectively. Then, supply side is further decomposed to progressively reveal structural effects associated to transformation processes and fuel types. The approach is applied to the most emitting and consuming nations (China, United States, European Union, India, Russia, Japan) to provide a meaningful cross-country analysis over the period 1995–2017. Results show that energy intensity gains have been mainly driven by widespread demand side efficiency improvements from 25% to 61%. Regarding the supply side, unfavourable structural changes due to electrification, up to 12% in China, have only been offset by transformation efficiency gains about 6% in developed countries. Consequently, emerging economies have worsened their energy sector efficiency as they thrive. Changes in fuel mixes have generally contributed to energy intensity reductions (up to 4%) mainly due to shifts from coal and nuclear power towards gas and renewables plants. The proposed methodology could help stakeholders to effectively analyse the energy system and to develop policies to reduce its environmental impact.

A Neural Network for Image Anomaly Detection with Deep Pyramidal Representations and Dynamic Routing.

Image anomaly detection is an application-driven problem where the aim is to identify novel samples, which differ significantly from the normal ones. We here propose Pyramidal Image Anomaly DEtector (PIADE), a deep reconstruction-based pyramidal approach, in which image features are extracted at different scale levels to better catch the peculiarities that could help to discriminate between normal and anomalous data. The features are dynamically routed to a reconstruction layer and anomalies can be identified by comparing the input image with its reconstruction. Unlike similar approaches, the comparison is done by using structural similarity and perceptual loss rather than trivial pixel-by-pixel comparison. The proposed method performed at par or better than the state-of-the-art methods when tested on publicly available datasets such as CIFAR10, COIL-100 and MVTec.

Efficient semantic segmentation with pyramidal fusion

Emergence of large datasets and resilience of convolutional models have enabled successful training of very large semantic segmentation models. However, high capacity implies high computational complexity and therefore hinders real-time operation. We therefore study compact architectures which aim at high accuracy in spite of modest capacity. We propose a novel semantic segmentation approach based on shared pyramidal representation and fusion of heterogeneous features along the upsampling path. The proposed pyramidal fusion approach is especially effective for dense inference in images with large scale variance due to strong regularization effects induced by feature sharing across the resolution pyramid. Interpretation of the decision process suggests that our approach succeeds by acting as a large ensemble of relatively simple models, as well as due to large receptive range and strong gradient flow towards early layers. Our best model achieves 76.4% mIoU on Cityscapes test and runs in real time on low-power embedded devices.

Pre‐service teacher‐delivered behavioral skills training: A pyramidal training approach

This study evaluated the effectiveness of using a university‐based pyramidal approach (i.e., train the trainer) to teach four pre‐service teachers to train another person. These pre‐service teachers were taught to use behavioral skills training (BST) techniques to train other professionals to use an evidence‐based practice. Transfer to a generalization trainee was probed and three participants maintenance of BST fidelity was probed one year later, after the participants had begun teaching. Results indicate that the participants quickly acquired and maintained a high degree of fidelity with BST. Implications for research and practice are discussed.

Practitioner Implementation of Communication Intervention With Students With Complex Communication Needs.

This study evaluated the effects of a pyramidal training approach that used an expert trainer who taught teachers how to train their paraeducators. Three special education teachers were taught to train four paraeducators to provide students with intellectual and developmental disabilities opportunities to initiate (OTI). A multiple baseline design across participants was used to evaluate the rate and fidelity that paraeducators provided OTI and least to most prompting strategies with students. Rates increased from 0 to an average of .58 per minute. Fidelity of implementation increased from 0% to an average of 94.5%. Maintenance data were recorded for three paraeducators. Schools should consider using this cost- and time-effective training model with staff.

A Fast and Robust Segmentation of Magnetic Resonance Brain Images Using a Combination of the Pyramidal Approach and Level Set Method

A Fast and Robust Segmentation of Magnetic Resonance Brain Images Using a Combination of the Pyramidal Approach and Level Set Method

A Review of the Pyramidal Training Approach for Practitioners Working With Individuals With Disabilities.

Pyramidal training has been used for many years to expedite training for those who work with individuals with disabilities and utilizes an expert who provides training to a practitioner who then trains another practitioner to implement practices with clients. Fourteen articles were analyzed to investigate the viability of this training approach for practitioners of all types who support individuals with disabilities. Research does support the effectiveness of pyramidal training within the parameters with which it has been evaluated in this review. All Tier 1 participants made improvement; 83% of Tier 2 participants and 43% of individuals with disabilities showed improvement. Future researchers are encouraged to analyze not only the fidelity of the implementation of these practices but also the changes among the individuals with disabilities. To that end, progress monitoring is necessary to determine whether the implementation was the cause for the meaningful gains for the population being served.