Physical Output Research Articles

Embedding 21st century employability into assessment and feedback practice through a student-staff partnership.

In-course assessments are an essential part of any coursework because they represent both a physical output of the skills and knowledge acquired at university, but also have the role of supporting student transitions into prospective careers. Therefore, assessments could be used as a conduit to encourage student awareness of the skills needed for the workplace and verify their attainment of these skills, particularly at foundation levels within a degree. Within a second-year Microbiology and Immunology course, students struggled to engage with standalone timetabled careers-related sessions, yet they showed enthusiasm when employability was embedded into assessments. A staff–student partnership project explored these issues, with the overall aim of understanding how to effectively embed employability skills into assessment and feedback and support students positioning themselves for the future. Through a focus group, this project investigated the reasons for low student engagement with timetabled employability sessions and used student views to develop digital initiatives and 21st-century competencies that could be applied more widely within assessment and feedback practice. These initiatives were then implemented as pre-session self-directed activities, with the objective of helping students to link course feedback with employment skills and future career planning, followed by a newly developed in-class reflective feedback session that allowed students time to consider what skills they have developed and make links with future careers. Project evaluation was conducted using a quantitative survey of the students involved.

Physical and technical demands of offence, defence, and contested phases of play in Australian Football

BackgroundThis study compared the physical demands and effect of field location for different phases of play (offence, defence and contested), and examined the physical and technical demands of successful and unsuccessful phases of play during Australian Football matches.MethodsGlobal positioning system (GPS) and technical performance data were collected from 32 male Australian Football players in one club over 19 games in the 2019 season. The GPS data was aligned with phases of play acquired using Champion Data. Linear mixed models were used to detect differences between phases of play and field location which were further contextualized using Cohen’s d effect size.ResultsPhysical demands were greatest (p < 0.001) in defensive phases for backs (ES 0.61 to 1.42), and offensive phases for midfielders (ES 0.65 to 0.96) and forwards (ES 0.84 to 1.94). Additionally, distance and high-speed running were lowest in contested phases irrespective of playing position. Distance and high-speed running were greatest in larger field locations (e.g., full ground). No pattern was evident for accelerations or decelerations. Successful offensive plays demonstrated greater physical and technical outputs for midfielders and forwards, whereas the opposite was found for backs. Physical output was largely greater in unsuccessful defensive plays for all positions; however, the rate of tackles and marks was greater during successful defence.ConclusionThese findings enable a greater understanding of the demands of Australian Football matches, and can be utilized to inform both representative training design, and the evaluation of player performance.

Neural network training using ℓ1-regularization and bi-fidelity data

With the capability of accurately representing a functional relationship between the inputs of a physical system's model and output quantities of interest, neural networks have become popular for surrogate modeling in scientific applications. However, as these networks are over-parameterized, their training often requires a large amount of data. To prevent overfitting and improve generalization error, regularization based on, e.g., ℓ1- and ℓ2-norms of the parameters is applied. Similarly, multiple connections of the network may be pruned to increase sparsity in the network parameters. In this paper, we explore the effects of sparsity promoting ℓ1-regularization on training neural networks when only a small training dataset from a high-fidelity model is available. As opposed to standard ℓ1-regularization that is known to be inadequate, we consider two variants of ℓ1-regularization informed by the parameters of an identical network trained using data from lower-fidelity models of the problem at hand. These bi-fidelity strategies are generalizations of transfer learning of neural networks that uses the parameters learned from a large low-fidelity dataset to efficiently train networks for a small high-fidelity dataset. We also compare the bi-fidelity strategies with two ℓ1-regularization methods that only use the high-fidelity dataset but with similar computational cost for generating the training datasets. Three numerical examples for propagating uncertainty through physical systems are used to show that the proposed bi-fidelity ℓ1-regularization strategies produce errors that are one order of magnitude smaller than those of networks trained only using datasets from the high-fidelity models.

Effect of Manufacturing Inaccuracies on the Wake Past Asymmetric Airfoil by PIV

The effect of manufacturing geometry deviations on the flow past a NACA 64(3)-618 asymmetric airfoil is studied. This airfoil is 3D printed according to the coordinates from a public database. An optical high-precision 3D scanner, GOM Atos, measures the difference from the idealized model. Based on this difference, another model is prepared with a physical output closer to the ideal model. The velocity in the near wake (0–0.4 chord) is measured by using the Particle Image Velocimetry (PIV) technique. This work compares the wakes past three airfoil realizations, which differ in their similarity to the original design (none of the realizations is identical to the original design). The chord-based Reynolds number ranges from 1.6×104 to 1.6×105. The ensemble average velocity is used for the determination of the wake width and for the rough estimation of the drag coefficient. The lift coefficient is measured directly by using force balance. We discuss the origin of turbulent kinetic energy in terms of anisotropy (at least in 2D) and the length-scales of fluctuations across the wake. The spatial power spectral density is shown. The autocorrelation function of the cross-stream velocity detects the regime of the von Karmán vortex street at lower velocities.

Influence of Tactical Formation on Average and Peak Demands of Elite Soccer Match-Play

Global Positioning Systems (GPS) have provided practitioners with information on the activity profiles of team-sport players. There is no available literature identifying the average or peak physical demands of elite soccer in the USA. This investigation aims to quantify the activity profiles and most demanding passages of elite soccer competition within different positions, periods, and tactical formations. Activity profiles were captured from 449 whole-period, and 661 peak-period data from 24 field players across a 31-game Major League Soccer season. Total distance covered (metres), average speed (m·min-1), and number of acceleration and deceleration (m·s-2) efforts were used to comprise whole-period profiles. Peak values for speed (m·min-1) were obtained by using a moving-average approach for durations lasting 1, 2, 3, 5, and 10 minutes. Across all positions the 4-2-3-1, 3-4-3, and 4-3-3 formations showed a decrease in average speed between the first and second halves. The 4-3-1-2 yielded greatest whole-period accelerations and decelerations for full backs, and overall distance covered and average speed for strikers. Most peak intensities were observed in the first half of match-play, with attacking midfielders and strikers demonstrating their greatest activity during the first half of a 4-3-1-2 formation. Altering tactical formations results in different physical outputs for all positional groups. Depending on the formation implemented, positional groups resulted in differences, with physical outputs, between halves during match-play.

Positive Influence of Regulated Human Capital Accumulation on Economic Growth: A Theoretical Model

Human capital, as an important factor of production, directly promotes economic growth. On the other hand, it indirectly promotes economic growth by stimulating the accumulation of physical capital and improving the level of technological innovation. Therefore, human capital is the fundamental reason for economic growth. The key to make human capital play a long-term role is to correctly set the human capital accumulation equation. Different from the existing articles that set human capital accumulation equation from the perspective of human capital investment and physical capital investment, this paper focuses on the marginal output of physical capital. Based on the marginal output of physical capital, this paper makes human capital accumulation subject to a regulation that can completely offset the diminishing effect of physical capital marginal output and keep it at a reasonable level. This way of human capital accumulation is called “regulated” accumulation. The derivation of theoretical model proves that the regulated human capital accumulation, which is based on constant marginal output of physical capital, enables the growth rate of output to be constant and positive. Therefore, this paper finds the source of long-term economic growth from aspect of human capital. As the embodiment of a country’s comprehensive strength and core competitiveness, human capital has important strategic significance and great potential in China’s sustainable economic development. Regulated human capital accumulation can provide a new driving force for China’s economic growth and promote long-term development.

Pandemic Restrictions Are Over: An Overview of Changes in the Main Economic Indicators of Enterprises. Part 1. Production, Prices, Employment, Financial Position of Enterprises and Profitability

The article outlines the dynamics of production, prices, wages, employment and various indicators characterizing the financial state of enterprises during the pandemic period. It is shown that production and employment decreased during the COVID period not as considerably as it had been expected, and the indicators characterizing prices increased very significantly. Inflation processes speeded up during this period more actively than the indicators of physical output and employment decreased. Being at very low values by the beginning of the COVID period, the financial position of the surveyed enterprises significantly improved by its end and returned to the highs of the pre-pandemic period, and in terms of profitability and the share of companies who consider the probability of their bankruptcy in the coming year or two unrealistic reached record highs for the entire observation period.

Пандемийные ограничения позади: обзор изменений основных показателей хозяйственной деятельности предприятий. Часть 1. Производство, цены, занятость, финансовое положение компаний и рентабельность производства

The article outlines the dynamics of output, prices, wages, employment and various indicators characterizing the financial situation of enterprises during the pandemic period. It is shown that output and employment decreased during the covid period not as considerably as it was expected, and the indicators characterizing prices increased very significantly. Inflation processes unfolded during this period more actively than the indicators of physical output and employment decreased. Being at very low values by the beginning of the covid period, the financial situation of the surveyed enterprises significantly improved by its end and returned to the highs of the pre-pandemic period, and in terms of profitability and the share of companies who consider the probability of their bankruptcy in the coming year or two unrealistic, reached record highs for the entire observation period.

An overview of Structured Biosensors for Metal Ions Determination

The determination of metal ions is important for nutritional and toxicological assessment. Atomic spectrometric techniques are highly efficient for the determination of these species, but the high costs of acquisition and maintenance hinder the application of these techniques. Inexpensive alternatives for metallic element determination are based on dedicated biosensors. These devices mimic biological systems and convert biochemical processes into physical outputs and can be used for the sensitive and selective determination of chemical species such as cations. In this work, an overview of the proposed biosensors for metal ions determination was carried out considering the last 15 years of publications. Statistical data on the applications, response mechanisms, instrumentation designs, applications of nanomaterials, and multielement analysis are herein discussed.

Mental imagery training programs for developing sport-specific motor skills: a systematic review and meta-analysis

ABSTRACT Background Physical practice is the cornerstone of acquiring and developing movement skills in physical education and sport. However, research has suggested that psychological tools, such as mental imagery (MI), could effectively supplement a learner's physical practice schedule. MI is the mental simulation of a movement or situation in the absence of an overt physical output. Previous reviews have established the efficacy of MI for improving motor skills in sport. Further investigation, however, will help strengthen previous findings by focusing exclusively on studies that apply MI programs for the development of sport-specific motor skills. Purpose The purpose of this paper is to examine the overall effectiveness of MI programs for developing sport-specific motor skills and investigate program principles that may moderate the efficacy of MI programs, such as practice type, skill level, skill complexity, performance measures, duration, practice setting, and session frequency. By examining key program variables for MI, this review seeks to provide practical recommendations for physical educators and sports coaches on how they might effectively design and deliver a MI program to develop sport-specific motor skills. Method The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. To provide practical recommendations for physical educators and sports coaches for effective MI programs, the following moderator variables were examined using subgroup analysis: (1) skill complexity, (2) skill level, (3) program duration, (4) session frequency, (5) MI practice type, and (6) practice context. The PEDro scale was used to assess study quality. The presence of publication bias was evaluated using the Trim and Fill method to calculate an adjusted and unbiased overall effect. Results The systematic review included 36 studies (n = 1449). A random-effects meta-analysis of standardised mean differences yielded an initial 135 individual effect sizes. A composite approach accounted for statistical dependence between effects and yielded 58 individual effects for further analysis. Analysis indicated that MI has a significant effect on performance (g = 0.476). Further analysis revealed significant effects on performance outcomes for MI combined with physical practice and MI alone (g = 0.579 and 0.298, respectively). Subgroup analyses revealed these beneficial effects be moderated by skill complexity, elements of skill performance, and MI delivery type. Conclusions and recommendations These results presented in our meta-analysis highlight the overall benefit of MI practice for developing sport-specific motor skills. However, there is a paucity of research on the effects of MI on complex skills and in physical education and sport coaching contexts. Although most studies presented in this review were conducted in controlled research settings, there are clear parallels between the skills practiced in these studies and those implemented in physical education and sport coaching. The efficacy of MI alone presents a potentially beneficial tool when physical practice is not possible or when physical training needs reduction (e.g. in-season sports competition). Therefore, it is encouraged that physical educators and sports coaches collaborate with sport psychology practitioners to investigate the efficacy of the several MI program variables presented in this review.

Localizing category-related information in speech with multi-scale analyses.

Measurements of the physical outputs of speech—vocal tract geometry and acoustic energy—are high-dimensional, but linguistic theories posit a low-dimensional set of categories such as phonemes and phrase types. How can it be determined when and where in high-dimensional articulatory and acoustic signals there is information related to theoretical categories? For a variety of reasons, it is problematic to directly quantify mutual information between hypothesized categories and signals. To address this issue, a multi-scale analysis method is proposed for localizing category-related information in an ensemble of speech signals using machine learning algorithms. By analyzing how classification accuracy on unseen data varies as the temporal extent of training input is systematically restricted, inferences can be drawn regarding the temporal distribution of category-related information. The method can also be used to investigate redundancy between subsets of signal dimensions. Two types of theoretical categories are examined in this paper: phonemic/gestural categories and syntactic relative clause categories. Moreover, two different machine learning algorithms were examined: linear discriminant analysis and neural networks with long short-term memory units. Both algorithms detected category-related information earlier and later in signals than would be expected given standard theoretical assumptions about when linguistic categories should influence speech. The neural network algorithm was able to identify category-related information to a greater extent than the discriminant analyses.

From the post-industrial prophecy to the de-industrial nightmare: Stagnation, the manufacturing fetish and the limits of capitalist wealth

The post-2008 era saw a return of the manufacturing fetish, the idea that manufacturing constitutes the flywheel of growth without which no nation can thrive. Across the Global North and South, voices are calling to reverse deindustrialization and revive manufacturing. While today deindustrialization is met with anxiety, in the 1930s economists predicted deindustrialization but interpreted it as a liberating process leading to a post-industrial age based on material abundance and widespread economic security. Far from delivering this vision, deindustrialization actually produces a precarious economic order driven by labour precarity, economic stagnation and lost development opportunities for the Global South. What can be termed the Baumolian and Kaldorian frameworks, attribute this precarious reality to services’ inability to replace manufacturing as a growth engine given their technologically stagnant nature. However, this article argues that, by focusing on the technical aspects of service economies, such views overlook the social limits of the capitalist economy and its historically specific conception of wealth, value. As capitalism matures, productivity becomes an increasingly inadequate form of augmenting social wealth as it results in great increases in physical output but counterintuitively undermines the expansion of value. Capitalism is underpinned by a secular movement towards declining dynamism, as it increasingly struggles to maintain its former economic vigour. Stagnation and heightened labour precarity are not merely the product of tertiarization but symptoms of capitalism’s declining trajectory.

Monitoring Postmatch Fatigue During a Competitive Season in Elite Youth Soccer Players.

Countermovement jump (CMJ) and perceived wellness measures are useful for monitoring fatigue. Fatigue indicators should simultaneously show sensitivity to previous load and demonstrate influence on subsequent physical output; however, these factors have not been examined. To explore the efficacy of CMJ and wellness measures to both detect postmatch fatigue and predict subsequent physical match output in elite youth soccer players. Cross-sectional study. Sixteen soccer players (18 ± 1 years) from 36 English Football League Youth Alliance League fixtures. Physical match outputs (total distance, high-speed running, very high-speed running, and accelerations and decelerations [AD]) were recorded using a 10-Hz global positioning system and 200-Hz accelerometer device during competitive match play. The CMJ height and perceived wellness were assessed weekly and daily, respectively, as indirect indicators of fatigue. Four subunits of wellness (perceived soreness, energy, general stress, and sleep) were measured using customized psychometric questionnaires. Simple linear regression showed that match AD predicted energy (R2 = 0.08, P = .001), stress (R2 = 0.09, P < .001), and total wellness (R2 = 0.06, P = .002) at 2 days postmatch. The CMJ (R2 = 0.05, P = .002), stress (R2 = 0.08, P < .001), sleep (R2 = 0.03, P = .034), and total wellness (R2 = 0.05, P = .006) measures at 5 days prematch predicted AD during the subsequent match. The CMJ and wellness measures may be useful for detecting postmatch fatigue. Wellness scores, but not CMJ, at 5 days prematch influenced subsequent match output and therefore may be used to plan and periodize training for the upcoming microcycle.

Improving readability by modifying graphic QR code microstructure

White modules of quick response codes (QR codes) are degraded by dot gain, especially when printed at smaller sizes, which results in more false blacks than false whites in error analysis, and also severely affects decoding ability. To reduce the false blacks generated from printing and to improve code readability, modifying the microstructure of graphic QR codes by reducing the size of the information dots is proposed. Experimental results show that the resultant QR code reduces the number of false blacks and thus the error rate. This method applies to the physical output of both conventional and graphic QR codes.

The Interaction between Health Capital Stock and Economic Growth

The health of citizens affects their labor ability. The labor ability of the whole society determines the labor output, and the physical output will bring economic growth, that is, the health of citizens will indirectly affect the economic growth of the whole society. This paper uses the data of public health investment, per capita GDP and fixed capital stock of ten developing and developed countries from 1980 to 2016 to explore the different degrees of interaction between health capital stock and economic growth between developing and developed countries, as well as the possible causal relationship between health capital and economic growth. After unit root test and cointegration test to test the stationarity of the data and ensure that there is no pseudo regression, OLS regression is carried out on the data. The regression results confirm or partially confirm three hypotheses: the promotion degree of health capital to the economic growth of developed and developing countries is significantly different, and the promotion degree of health capital to developing countries is higher; In the long run, the promoting effect of health capital on economic growth is weakened; There is a causal relationship between health capital and economic growth.

Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high-resolution visible channel: implementation and examples

Abstract. The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

Forecasting the production of gross output in agricultural sector of the Ryazan oblast

Gross agricultural output is a generalised physical output indicator in an industry that includes hundreds of different types of products, as well as the result of the interaction of production factors. This study provides a comparative analysis of methods based on "Gradient boosting of regression trees" in the Python programming language to identify the optimal values of the model parameters with the subsequent construction of a predictive model based on indicators that affect the production of gross agricultural output. The purpose of this study is to build a regression model for predicting gross agricultural output at actual prices for 2020. To achieve this goal, the methods of regression analysis, forecasting, gradient boosting, etc., were used. The gradient boosting of regression trees was solved for the conditions of the Ryazan Oblast. 4 models were created, 2 of which were based on the preliminary data processing. As a result of the construction of all models, the optimal values of the parameters were found and the results of the correctness on the model on the test set were obtained. It was found that the gradient boosting of regression trees gives adequate regression models for predicting the target variable, in particular, the indicator of gross agricultural output. The investigated indicator is a complex result of the interaction of many factors that are common for agricultural production. Thus, the gradient boosting of trees is most suitable for forecasting complex open systems. Such a method can be used to forecast the production of gross agricultural output not only of individual regions but also of the state as a whole. Based on the "test_score" model, which showed the correctness of 99% (0.994) on the test set, the gross agricultural output in all categories of farms in 2020 amounted to RUB 19187.84 million.

Bangkok’s Bumpy Road to Sustainable Urban Mobility: Governance Challenges in the Promotion of Cycle-friendliness

Many cities promote cycling as an environmentally friendly and healthier mode of urban transport. The challenge often is bigger than anticipated, as it involves inducing behavioural change among different groups of actors and reaching agreement about the reallocation of scarce resources. Recent experiences in Bangkok are illustrative. Here, multi-year efforts by the Bangkok Metropolitan Administration (BMA) to promote cycling have yielded only partial success. Recreational cycling has increased, but utility cycling much less so. A gap remains between what the BMA delivers in terms of pro-cycling policies and what Bangkokians need in order to become utility cyclists. This paper investigates the characteristics of this gap and the factors that produce it. It finds that safety concerns in particular keep Bangkokians from cycling, and that organizational inefficiencies and failure to commit key actors, a narrow focus on physical output, wavering political leadership, and a failure to benefit from the knowledge available among members of the public, are key factors preventing the BMA from delivering more effective solutions. The paper concludes by deriving key lessons from the Bangkok experience.

The influence of possession status on the physical output of male international hockey players

The aims of this investigation were to describe the physical output of hockey relative to possession status, and to identify differences in physical output during each possession category with respect of match result. Ten international matches were analysed utilizing Sportscode to identify in and not in possession instances. 24 players (age 26 ± 4) wore a 10 Hz GPS device to track physical output. Linear Mixed Models and post hoc pairwise comparisons were utilised to compare the physical output in each possession category within each position and relative to match result. Significant main effects were found for possession status on several physical output metrics (p ≤ 0.05). For all positions except forwards, not in possession instances were more physically demanding than in possession instances for metrics such as relative total distance, explosive distance, and high-speed running (&gt;5.5 m.s−1). No significant difference was identified between possession category physical output aligned with match result (p &gt; 0.05). This study shows for the first time that not in possession instances were more physically demanding than in possession instances for defenders, outside backs and midfielders. For not in possession instances, relative total distance and high-speed running was, on average, 13% and 41% higher compared to in possession instances. Furthermore, there was no statistical difference in physical output for any position during each possession category relative to the match result.

Smart Health System to Detect Dementia Disorders Using Virtual Reality.

Smart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic surgery, diagnosis of some difficult diseases, and virtual reality pain distraction for severe burn patients. Smart VR health technology acts as a decision support system in the diseases diagnostic test of patients as they perform real world tasks in virtual reality (e.g., navigation). In this study, a non-invasive, cognitive computerized test based on 3D virtual environments for detecting the main symptoms of dementia (memory loss, visuospatial defects, and spatial navigation) is proposed. In a recent study, the system was tested on 115 real patients of which thirty had a dementia, sixty-five were cognitively healthy, and twenty had a mild cognitive impairment (MCI). The performance of the VR system was compared with Mini-Cog test, where the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. It was observed that visuospatial and memory recall scores in both clinical diagnosis and VR system of dementia patients were less than those of MCI patients, and the scores of MCI patients were less than those of the control group. Furthermore, there is a perfect agreement between the standard methods in functional evaluation and navigational ability in our system where P-value in weighted Kappa statistic= 100% and between Mini-Cog-clinical diagnosis vs. VR scores where P-value in weighted Kappa statistic= 93%.