scholarly journals Cycling Biomechanics and Its Relationship to Performance

2020 ◽  
Vol 10 (12) ◽  
pp. 4112 ◽  
Author(s):  
Nicolas A. Turpin ◽  
Bruno Watier

State-of-the-art biomechanical laboratories provide a range of tools that allow precise measurements of kinematic, kinetic, motor and physiologic characteristics. Force sensors, motion capture devices and electromyographic recording measure the forces exerted at the pedal, saddle, and handlebar and the joint torques created by muscle activity. These techniques make it possible to obtain a detailed biomechanical analysis of cycling movements. However, despite the reasonable accuracy of such measures, cycling performance remains difficult to fully explain. There is an increasing demand by professionals and amateurs for various biomechanical assessment services. Most of the difficulties in understanding the link between biomechanics and performance arise because of the constraints imposed by the bicycle, human physiology and musculo-skeletal system. Recent studies have also pointed out the importance of evaluating not only output parameters, such as power output, but also intrinsic factors, such as the cyclist coordination. In this narrative review, we present various techniques allowing the assessment of a cyclist at a biomechanical level, together with elements of interpretation, and we show that it is not easy to determine whether a certain technique is optimal or not.

Author(s):  
Inzamam Mashood Nasir ◽  
Muhammad Rashid ◽  
Jamal Hussain Shah ◽  
Muhammad Sharif ◽  
Muhammad Yahiya Haider Awan ◽  
...  

Background: Breast cancer is considered as the most perilous sickness among females worldwide and the ratio of new cases is expanding yearly. Many researchers have proposed efficient algorithms to diagnose breast cancer at early stages, which have increased the efficiency and performance by utilizing the learned features of gold standard histopathological images. Objective: Most of these systems have either used traditional handcrafted features or deep features which had a lot of noise and redundancy, which ultimately decrease the performance of the system. Methods: A hybrid approach is proposed by fusing and optimizing the properties of handcrafted and deep features to classify the breast cancer images. HOG and LBP features are serially fused with pretrained models VGG19 and InceptionV3. PCR and ICR are used to evaluate the classification performance of proposed method. Results: The method concentrates on histopathological images to classify the breast cancer. The performance is compared with state-of-the-art techniques, where an overall patient-level accuracy of 97.2% and image-level accuracy of 96.7% is recorded. Conclusion: The proposed hybrid method achieves the best performance as compared to previous methods and it can be used for the intelligent healthcare systems and early breast cancer detection.


2019 ◽  
Vol 13 (2) ◽  
pp. 14-31
Author(s):  
Mamdouh Alenezi ◽  
Muhammad Usama ◽  
Khaled Almustafa ◽  
Waheed Iqbal ◽  
Muhammad Ali Raza ◽  
...  

NoSQL-based databases are attractive to store and manage big data mainly due to high scalability and data modeling flexibility. However, security in NoSQL-based databases is weak which raises concerns for users. Specifically, security of data at rest is a high concern for the users deployed their NoSQL-based solutions on the cloud because unauthorized access to the servers will expose the data easily. There have been some efforts to enable encryption for data at rest for NoSQL databases. However, existing solutions do not support secure query processing, and data communication over the Internet and performance of the proposed solutions are also not good. In this article, the authors address NoSQL data at rest security concern by introducing a system which is capable to dynamically encrypt/decrypt data, support secure query processing, and seamlessly integrate with any NoSQL- based database. The proposed solution is based on a combination of chaotic encryption and Order Preserving Encryption (OPE). The experimental evaluation showed excellent results when integrated the solution with MongoDB and compared with the state-of-the-art existing work.


Foods ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 316
Author(s):  
Marco Montemurro ◽  
Erica Pontonio ◽  
Rossana Coda ◽  
Carlo Giuseppe Rizzello

Due to the increasing demand for milk alternatives, related to both health and ethical needs, plant-based yogurt-like products have been widely explored in recent years. With the main goal to obtain snacks similar to the conventional yogurt in terms of textural and sensory properties and ability to host viable lactic acid bacteria for a long-time storage, several plant-derived ingredients (e.g., cereals, pseudocereals, legumes, and fruits) as well as technological solutions (e.g., enzymatic and thermal treatments) have been investigated. The central role of fermentation in yogurt-like production led to specific selections of lactic acid bacteria strains to be used as starters to guarantee optimal textural (e.g., through the synthesis of exo-polysaccharydes), nutritional (high protein digestibility and low content of anti-nutritional compounds), and functional (synthesis of bioactive compounds) features of the products. This review provides an overview of the novel insights on fermented yogurt-like products. The state-of-the-art on the use of unconventional ingredients, traditional and innovative biotechnological processes, and the effects of fermentation on the textural, nutritional, functional, and sensory features, and the shelf life are described. The supplementation of prebiotics and probiotics and the related health effects are also reviewed.


Plants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1027
Author(s):  
Xizi Wang ◽  
Fulai Liu

Wheat is one of the most important staple foods in temperate regions and is in increasing demand in urbanizing and industrializing countries such as China. Enhancing yield potential to meet the population explosion around the world and maintaining grain quality in wheat plants under climate change are crucial for food security and human nutrition. Global warming resulting from greenhouse effect has led to more frequent occurrence of extreme climatic events. Elevated atmospheric CO2 concentration (eCO2) along with rising temperature has a huge impact on ecosystems, agriculture and human health. There are numerous studies investigating the eCO2 and heatwaves effects on wheat growth and productivity, and the mechanisms behind. This review outlines the state-of-the-art knowledge regarding the effects of eCO2 and heat stress, individually and combined, on grain yield and grain quality in wheat crop. Strategies to enhance the resilience of wheat to future warmer and CO2-enriched environment are discussed.


2015 ◽  
Vol 738-739 ◽  
pp. 1105-1110 ◽  
Author(s):  
Yuan Qing Qin ◽  
Ying Jie Cheng ◽  
Chun Jie Zhou

This paper mainly surveys the state-of-the-art on real-time communicaton in industrial wireless local networks(WLANs), and also identifys the suitable approaches to deal with the real-time requirements in future. Firstly, this paper summarizes the features of industrial WLANs and the challenges it encounters. Then according to the real-time problems of industrial WLAN, the fundamental mechanism of each recent representative resolution is analyzed in detail. Meanwhile, the characteristics and performance of these resolutions are adequately compared. Finally, this paper concludes the current of the research and discusses the future development of industrial WLANs.


Author(s):  
Xabier Muriel ◽  
Pedro L. Valenzuela ◽  
Manuel Mateo-March ◽  
Jesús G. Pallarés ◽  
Alejandro Lucia ◽  
...  

Purpose: To compare the physical demands and performance indicators of male professional cyclists of 2 different categories (Union Cycliste Internationale WorldTour [WT] and ProTeam [PT]) during a cycling grand tour. Methods: A WT team (n = 8, 31.4 [5.4] y) and a PT team (n = 7, 26.9 [3.3] y) that completed “La Vuelta 2020” volunteered to participate. Participants’ power output (PO) was registered, and measures of physical demand and physiological performance (kilojoules spent, training stress score, time spent at different PO bands/zones, and mean maximal PO [MMP] for different exertion durations) were computed. Results: WT achieved a higher final individual position than PT (31 [interquartile range = 33] vs 71 [59], P = .004). WT cyclists showed higher mean PO and kilojoule values than their PT peers and spent more time at high-intensity PO values (>5.25 W·kg−1) and zones (91%–120% of individualized functional threshold power) (Ps < .05). Although no differences were found for MMP values in the overall analysis (P > .05), subanalyses revealed that the between-groups gap increased through the race, with WT cyclists reaching higher MMP values for ≥5-minute efforts in the second and third weeks (Ps < .05). Conclusions: Despite the multifactorial nature of cycling performance, WT cyclists spend more time at high intensities and show higher kilojoules and mean PO than their PT referents during a grand tour. Although the highest MMP values attained during the whole race might not differentiate between WT and PT cyclists, the former achieve higher MMP values as the race progresses.


Author(s):  
Rosa Romano

The Smart Skin Envelope research analyses the recent revolution that has taken place in the sector of planning and production of smart skin components, made up of dynamic layers. The aim is to identify the technological, functional, qualitative and performance parameters that guide the decisions of the actors in the innovation process. It explores the factors that drive them to develop solutions and proposals designed to transform the envelope of the building from a static to a dynamic element, featuring interoperable components that can interact with the input from the outdoor and indoor environments, in relation to which the smart skin acts as a system of boundary and delimitation. The proposed research programme explores in particular the sector of Smart Envelopes, setting as its priority objective the identification and definition of the energy performance, both through analysis of the state of the art and through the development of a facade component that is dynamic in terms of the adaptive variability of its performance.


2020 ◽  
Author(s):  
Andrey De Aguiar Salvi ◽  
Rodrigo Coelho Barros

Recent research on Convolutional Neural Networks focuses on how to create models with a reduced number of parameters and a smaller storage size while keeping the model’s ability to perform its task, allowing the use of the best CNN for automating tasks in limited devices, with reduced processing power, memory, or energy consumption constraints. There are many different approaches in the literature: removing parameters, reduction of the floating-point precision, creating smaller models that mimic larger models, neural architecture search (NAS), etc. With all those possibilities, it is challenging to say which approach provides a better trade-off between model reduction and performance, due to the difference between the approaches, their respective models, the benchmark datasets, or variations in training details. Therefore, this article contributes to the literature by comparing three state-of-the-art model compression approaches to reduce a well-known convolutional approach for object detection, namely YOLOv3. Our experimental analysis shows that it is possible to create a reduced version of YOLOv3 with 90% fewer parameters and still outperform the original model by pruning parameters. We also create models that require only 0.43% of the original model’s inference effort.


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