Search

In the Vase system, the most common training system for peach-growing countries for more than a century, light distribution to the canopy is uneven, and access to the canopy for pruning, thinning, and harvest labor is difficult. It is important to identify alternative systems to the Vase system considering the cultivar and growing environment to facilitate labor and enhance productivity and quality. In Türkiye, one of the important centers of peach growing worldwide, detailed research has yet to be published on the applicability of training systems alternative to the widely used Vase system. Therefore, this study aimed to evaluate the effect of different training systems (Vase, Catalan Vase, Quad-V, Tri-V) on growth, yield, fruit quality, and labor costs of peach cultivars (ExtremeVR 314, ExtremeVR 436, ExtremeVR 568). The experiment was conducted from 2017 to 2022. Although the distance between rows in all training systems is 5 m, the distance between trees on the row is determined as 4 m in Vase, 3 m in Catalan Vase, 2.5 m in Quad-V, and 2 m in Tri-V. In the experiment, vegetative development parameters, such as canopy volume, trunk sectional area, and the amount of winter pruning weights, differed according to the training system. In the final year, the Vase system, which produces the most pruning weight, generates 48.0% more pruning weight compared with the Tri-V system, which produces the least. Concerning yield per tree and hectare, trained to the Vase system yielded higher fruit per tree regardless of cultivar, while the Quad-V and Tri-V systems yielded more fruit per hectare. The training system and cultivar affected the fruit size; the largest fruits were obtained from the ExtremeVR 568 cultivar trained according to the Vase system. The most time needed for winter pruning was obtained from the Vase (79.4 min/tree) system, and the Tri-V (57.4 min/tree) and Quad-V (60.3 min/tree) systems required the least time. The Catalan Vase (31.1 min/tree) system required the least time for summer pruning. The most fruit harvest in an hour was obtained from the trees trained according to the Tri-V (164.5 kg/h) and Quad-V (132.02 kg/h) systems. These results suggest that Quad-V and Catalan Vase systems performed well and could be alternatives to the Vase system. [ABSTRACT FROM AUTHOR]

Rowing races require extreme physical and psychological effort from every athlete. This study aimed to determine the dynamics of the salivary cortisol and alpha-amylase, as well as blood lactate throughout the specific load represented by a 6 km rowing race, conducted on a rowing ergometer. The sample consisted of 11 junior and senior rowers from HVK Gusar in Split (n = 11) who actively competed at club and international levels. Variables consisted of three repeated oral samples of the hormone cortisol and the enzyme alpha-amylase determined in saliva and three repeated blood lactate samples. Potential differences in the levels of the studied variables at different time points were determined using a repeated-measures ANOVA test. The results showed different dynamics of hormonal (cortisol) and metabolic (alpha-amylase and lactates) variables. All variables experienced a significant post-race increase, while other changes were not significant. The results highlighted that high-intensity rowing causes an increase in the body's cortisol, alpha-amylase, and lactate levels. This should be implemented in rowing training to find the right balance between high and low-intensity rowing, enabling athletes' progression while reducing the risk of overtraining. [ABSTRACT FROM AUTHOR]

This longitudinal study aimed to analyze the effects of a team rowing-based training program on physical fitness and anthropometric parameters in female breast cancer survivors (n = 40; 56.78 ± 6.38 years). Participants were divided into two groups: one rowed in fixed seat rowing (FSR) boats (n = 20; 56.35 ± 4.89 years) and the other in sliding seat rowing (SSR) boats (n = 20; 57.20 ± 7.7 years). Both groups engaged in two 75-min sessions per week for 24 weeks. Significant improvements were observed in both groups in resting heart rate (FSR: −10.65 bpm; SSR: −8.45 bpm), heart rate at the beginning of the 6-min walk test (6 MWT) (FSR: −10.7 bpm; SSR: −11.25 bpm), and heart rate at the end of the test (FSR: −13.85 bpm; SSR: −20.35 bpm). Blood pressure improved significantly in both diastolic blood pressure (FSR: −12.35 mmHg; SSR: −19.25 mmHg) and systolic blood pressure (FSR: −13 mmHg; SSR: −16.95 mmHg). Additionally, both groups increased the distance covered in the 6 MWT (FSR: +63.05 m; SSR: +93.65 m). These results suggest that a rowing training program is a viable and safe activity for female breast cancer survivors, improving cardiac function, blood pressure, and cardiorespiratory capacity, particularly in sliding seat boats. [ABSTRACT FROM AUTHOR]

The main purpose of this study was to study the effects of a specific rowing ergometer training program on the athletic performance of young adolescents (N = 56; 11.73 ± 1.4 years old) compared to a workout based on general strength training. An eight-week training program was implemented, with four sessions per week and two hours per session. The sample was divided into two groups: a control group (CG) that performed circuit training with exercises aimed at building general strength and an experimental group (EG) who focused on specifically training on a rowing ergometer (rowing machine). The data obtained in a rowing meter test over the competition distance were analyzed to obtain the average power attained (W) at the beginning of the training, at the middle (4 weeks), at the end of the training (8 weeks) and one year after the experimentation. The results show that although both forms of training improve the average W obtained in both categories, the EG subjects (+29.94 W) obtained better averages in all phases of the study compared to the CG (+5.88 W). Furthermore, this increase was greater in male rowers (+34.06 W) than in female rowers (+24.54 W). These results reveal that a specific rower rowing ergometer training program has a more significant effect than a general strength program and these effects can even be observed a year after the intervention. [ABSTRACT FROM AUTHOR]

It is quite remarkable how solo bamboo drifting (originated from indigenous boating in southwestern China) has transformed into a captivating and innovative sport when compared to more conventional forms of competition. This study focuses on the competitive element of solo drifting on bamboo, which involves direct contact with the terrain. Instead, the focus is on studying a variety of oar-rowing strategies and understanding how successful athletes achieve victory in competitions. The primary objective of the research is to offer training advice that is supported by empirical evidence for the participants/athletes involved in the sport. The investigation involves five athletes who were selected for the case studies based on their performance in the 60-metre straight track event. In this context, the study tools used include literature analysis, observation, video playback, and statistical mathematics. The Dartfish sports technique video analysis system, a specialised app, enables you to scrutinise movements closely and compare them to your athletes to evaluate their pole-rowing techniques. The results suggest that the athletes' technique plays a vital role in determining the competitive outcomes in solo bamboo drifting. Factors such as their position on the bamboo, the angle at which the pole enters the water, the management of rowing power and speed, and the control of the bamboo's direction all contribute to the overall performance. By maintaining proper posture and employing effective pole-rowing techniques, you can greatly reduce water resistance and increase the speed of the bamboo's forward movement. Efficiently managing the force applied during rowing is crucial for maintaining the stability of the bamboo and maximising the overall effectiveness of the rowing process. Furthermore, the competitors' yawing phenomena during the competition have a negative impact on rowing efficiency, disrupting the rhythm and stability of the rowing motions. This study employs comparative analysis to investigate the pole-rowing tactics of three athletes, emphasising differences in their movement intricacies and effectiveness during the rowing cycle. The results of this study provide a solid basis for future training efforts. This paper provides a comprehensive set of training suggestions derived from the research findings. These recommendations involve incorporating cutting-edge technology for technical monitoring and analysis, improving physical training to optimise rowing efficiency, and honing direction control in different competition conditions. The purpose of these guidelines is to help athletes enhance their pole-rowing techniques and elevate their performance in competitions. This research not only provides theoretical justification for the technical training of solo bamboo drifting but also offers practical instructions for the scientific advancement and widespread adoption of the sport. [ABSTRACT FROM AUTHOR]

When data is scarce, software analytics can make many mistakes. For example, consider learning predictors for open source project health (e.g., the number of closed pull requests in 12 months time). The training data for this task may be very small (e.g., 5 years of data, collected every month means just 60 rows of training data). The models generated from such tiny datasets can make many prediction errors. Those errors can be tamed by a landscape analysis that selects better learner control parameters. Our niSNEAK tool (a) clusters the data to find the general landscape of the hyperparameters, then (b) explores a few representatives from each part of that landscape. niSNEAK is both faster and more effective than prior state-of-the-art hyperparameter optimization algorithms (e.g., FLASH, HYPEROPT, OPTUNA). The configurations found by niSNEAK have far less error than other methods. For example, for project health indicators such as C = number of commits, I = number of closed issues, and R = number of closed pull requests, niSNEAK 's 12-month prediction errors are {I=0%, R=33% C=47%}, whereas other methods have far larger errors of {I=61%,R=119% C=149%}. We conjecture that niSNEAK works so well since it finds the most informative regions of the hyperparameters, then jumps to those regions. Other methods (that do not reflect over the landscape) can waste time exploring less informative options. Based on the preceding, we recommend landscape analytics (e.g., niSNEAK) especially when learning from very small datasets. This article only explores the application of niSNEAK to project health. That said, we see nothing in principle that prevents the application of this technique to a wider range of problems. To assist other researchers in repeating, improving, or even refuting our results, all our scripts and data are available on GitHub at https://github.com/zxcv123456qwe/niSneak. [ABSTRACT FROM AUTHOR]

Accurately characterizing vineyard parameters is crucial for precise vineyard management and breeding purposes. Various macroscopic vineyard parameters are required to make informed management decisions, such as pesticide application, defoliation strategies, and determining optimal sugar content in each berry by assessing biomass. In this paper, we present a novel approach that utilizes point cloud data to detect trunk positions and extract macroscopic vineyard characteristics, including plant height, canopy width, and canopy volume. Our approach relies solely on geometric features and is compatible with different training systems and data collected using various 3D sensors. To evaluate the effectiveness and robustness of our proposed approach, we conducted extensive experiments on multiple grapevine rows trained in two different systems. Our method provides more comprehensive canopy characteristics than traditional manual measurements, which are not representative throughout the row. The experimental results demonstrate the accuracy and efficiency of our method in extracting vital macroscopic vineyard characteristics, providing valuable insights for yield monitoring, grape quality optimization, and strategic interventions to enhance vineyard productivity and sustainability. [ABSTRACT FROM AUTHOR]

IntroductionThe aim of the study was to investigate the influence of training status on cardiovascular function in young male recreational and competitive rowers.MethodsEjection duration in percentage to the heart rate period (ED%), subendocardial viability ratio (SEVR), augmentation index at 75 bpm (AIx75) and carotid to femoral pulse wave velocity (cf-PWV) of competitive rowers (CR) (age 17.6 ± 4.1 years), recreational rowers (RR) (age 16.7 ± 2.70 years) and athletes practicing other recreational sports (ORS) (age 15.3 ± 1.4 years) were assessed.ResultsED% was lower in CR compared to ORS (31.9 ± 3.9% vs. 38.4 ± 4.8%; p = 0.026) and cf-PWV was higher in CR compared to ORS (5.5 ± 1.0 m/s vs. 4.7 ± 0.5 m/s; p = 0.032). SEVR was higher in CR compared to RR and ORS (165.8 ± 33.7% vs. 127.4 ± 30.4% and 128.3 ± 27.8%; p = 0.022) and AIx75 was lower in CR compared to RR and ORS (−15.7 ± 8.6% vs. 1.2 ± 9.9% and 1.5 ± 9.1; p = 0.001).DiscussionHealthy, young competitive male rowers reported higher myocardial performance and better cardiovascular health than recreational athletes. Interpretations of cf-PWV in competitive rowers should be performed alongside other cardiovascular indicators.

Using panel data from 2009, 2011, and 2015, this study estimates the impact of rice production training conducted in Uganda on the adoption of improved cultivation practices and productivities of not only training participants but also non-participants. Spillover effects to non-participants in training villages are indicated by increased total rice production by 0.4 tons and expanded cultivation area by 0.26 hectare. Although training increases adoption rates for better cultivation practice, namely, transplanting in rows among training participants, both in the short and long term, there were no measurable improvements in non-participants' rice cultivation knowledge or in rice productivity. [ABSTRACT FROM AUTHOR]

The identification method of rice seedling rows based on machine vision is affected by environmental factors that decrease the accuracy and the robustness of the rice seedling row identification algorithm (e.g., ambient light transformation, similarity of weed and rice features, and lack of seedlings in rice rows). To solve the problem of the above environmental factors, a Gaussian Heatmap-based method is proposed for rice seedling row identification in this study. The proposed method is a CNN model that comprises the High-Resolution Convolution Module of the feature extraction model and the Gaussian Heatmap of the regression module of key points. The CNN model is guided using Gaussian Heatmap generated by the continuity of rice row growth and the distribution characteristics of rice in rice rows to learn the distribution characteristics of rice seedling rows in the training process, and the positions of the coordinates of the respective key point are accurately returned through the regression module. For the three rice scenarios (including normal scene, missing seedling scene and weed scene), the PCK and average pixel offset of the model were 94.33%, 91.48%, 94.36% and 3.09, 3.13 and 3.05 pixels, respectively, for the proposed method, and the forward inference speed of the model reached 22 FPS, which can meet the real-time requirements and accuracy of agricultural machinery in field management. [ABSTRACT FROM AUTHOR]

With the rapid advancement of artificial intelligence technology and the widespread use of sensing technology in education, human-computer interaction teaching has gradually developed in sports and education. Traditionally, teachers explain and demonstrate the fundamentals of movements first, then organize exercises, and students gradually consolidate technical movements through repetition. This process requires teachers to repeatedly explain, such that students can develop movement concepts, and to assist students in correcting their movements through practice. Eventually, students can master the dragon boat's paddling movements. Teachers frequently struggle to observe all of their students' movements and are therefore unable to correct them in a timely and effective manner. To address the aforementioned issues, this paper proposes a big data system for multidimensional stereo vision training in dragon boat paddling action. The stock price action recognition of dragon boat paddles and the movement of students' dragon boat paddles are realized through the multidimensional fusion of attention mechanism and spatiotemporal graph convolution. Make judgments to more effectively guide and train students' paddling movements. [ABSTRACT FROM AUTHOR]

Introduction: The aim of the study was to investigate the influence of training status on cardiovascular function in young male recreational and competitive rowers., Methods: Ejection duration in percentage to the heart rate period (ED%), subendocardial viability ratio (SEVR), augmentation index at 75 bpm (AIx75) and carotid to femoral pulse wave velocity (cf-PWV) of competitive rowers (CR) (age 17.6 ± 4.1 years), recreational rowers (RR) (age 16.7 ± 2.70 years) and athletes practicing other recreational sports (ORS) (age 15.3 ± 1.4 years) were assessed., Results: ED% was lower in CR compared to ORS (31.9 ± 3.9% vs. 38.4 ± 4.8%; p  = 0.026) and cf-PWV was higher in CR compared to ORS (5.5 ± 1.0 m/s vs. 4.7 ± 0.5 m/s; p  = 0.032). SEVR was higher in CR compared to RR and ORS (165.8 ± 33.7% vs. 127.4 ± 30.4% and 128.3 ± 27.8%; p  = 0.022) and AIx75 was lower in CR compared to RR and ORS (-15.7 ± 8.6% vs. 1.2 ± 9.9% and 1.5 ± 9.1; p  = 0.001)., Discussion: Healthy, young competitive male rowers reported higher myocardial performance and better cardiovascular health than recreational athletes. Interpretations of cf-PWV in competitive rowers should be performed alongside other cardiovascular indicators., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (© 2023 Falcioni, Gallotta, Baldari, Cardinali, Campanella, Ferrari, Guidetti and Meucci.)