Many studies have shown that experts possess better perceptual-cognitive skills than novices (e.g., in anticipation, decision making, pattern recall), but it remains unclear whether a relationship exists between performance on those tests of perceptual-cognitive skill and actual on-field performance. In this study, we assessed the in situ performance of skilled soccer players and related the outcomes to measures of anticipation, decision making, and pattern recall. In addition, we examined gaze behaviour when performing the perceptual-cognitive tests to better understand whether the underlying processes were related when those perceptual-cognitive tasks were performed. The results revealed that on-field performance could not be predicted on the basis of performance on the perceptual-cognitive tests. Moreover, there were no strong correlations between the level of performance on the different tests. The analysis of gaze behaviour revealed differences in search rate, fixation duration, fixation order, gaze entropy, and percentage viewing time when performing the test of pattern recall, suggesting that it is driven by different processes to those used for anticipation and decision making. Altogether, the results suggest that the perceptual-cognitive tests may not be as strong determinants of actual performance as may have previously been assumed.
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In this presented study, we measured in situ the uplink duty cycles of a smartphone for 5G NR and 4G LTE for a total of six use cases covering voice, video, and data applications. The duty cycles were assessed at ten positions near a 4G and 5G base-station site in Belgium. For Twitch, VoLTE, and WhatsApp, the duty cycles ranged between 4% and 22% in time, both for 4G and 5G. For 5G NR, these duty cycles resulted in a higher UL-allotted time due to time division duplexing at the 3.7 GHz frequency band. Ping showed median duty cycles of 2% for 5G NR and 50% for 4G LTE. FTP upload and iPerf resulted in duty cycles close to 100%.
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In this work, in situ measurements of the radio frequency electromagnetic field exposure have been conducted for an indoor massive MIMO 5G base station operating at 26–28 GHz. Measurements were performed at six different positions (at distances between 9.94 and 14.32 m from the base station), of which four were in line-of-sight and two were in non-line-of-sight. A comparison was performed between the measurements conducted with an omnidirectional probe and with a horn antenna, for scenarios with and without a user equipment used to actively create an antenna traffic beam from the base station towards the measurement location. A maximum exposure of 171.9 mW/m2 was measured at a distance of 9.94 m from the base station. This is below 2% of the ICNIRP reference level. Moreover, the feasibility to measure the power per resource element of the Synchronization Signal Block - which can be used to extrapolate the maximum exposure level - with a conventional spectrum analyzer was shown by comparison with a network decoder.
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Floating urbanization is a promising solution to reduce the vulnerability of cities against climate change, population growth or land scarcity. Although this type of construction introduces changes to aquatic systems, there is a lack of research studies addressing potential impacts. Water quality data collected under/near floating structures were compared with the corresponding parameters measured at the same depth at open water locations by (i) performing scans with underwater drones equipped with in situ sensors and video cameras and (ii) fixing two sets of continuous measuring in situ sensors for a period of several days/months at both positions. A total of 18 locations with different types of floating structures were considered in this study. Results show small differences in the measured parameters, such as lower dissolved oxygen concentrations or higher temperature measured underneath the floating structures. The magnitudes of these differences seem to be linked with the characteristics and type of water system. Given the wide variety and types of water bodies considered in this study, results suggest that water quality is not critically affected by the presence of the floating houses. Underwater images of biofouling and filter feeders illustrate the lively ecosystems that can emerge shortly after the construction of floating buildings.
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The purpose of this study is to analyze the relationship between sustainable performance and risk management, whereby sustainability (innovation), interdisciplinarity and leadership give new insights into the traditional perspectives on performance and risk management in the field of accounting and finance.
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Big data analytics received much attention in the last decade and is viewed as one of the next most important strategic resources for organizations. Yet, the role of employees' data literacy seems to be neglected in current literature. The aim of this study is twofold: (1) it develops data literacy as an organization competency by identifying its dimensions and measurement, and (2) it examines the relationship between data literacy and governmental performance (internal and external). Using data from a survey of 120 Dutch governmental agencies, the proposed model was tested using PLS-SEM. The results empirically support the suggested theoretical framework and corresponding measurement instrument. The results partially support the relationship of data literacy with performance as a significant effect of data literacy on internal performance. However, counter-intuitively, this significant effect is not found in relation to external performance.
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The catalytic coconversion of glycerol and toluene (93/7 wt %) over a technical H-ZSM-5/Al2O3 (60-40 wt %) catalyst was studied, aiming for enhanced production of biobased benzene, toluene, and xylenes (bio-BTX). When using glycerol/toluene cofeed with a mass ratio of 93/7 wt %, a peak BTX carbon yield of 29.7 ± 1.1 C.% (at time on stream (TOS) of 1.5-2.5 h), and an overall BTX carbon yield of 28.7 C.% (during TOS of 8.5 h) were obtained, which are considerably higher than those (19.1 ± 0.4 C.% and 11.0 C.%) for glycerol alone. Synergetic effects when cofeeding toluene on the peak and overall BTX carbon yields were observed and quantified, showing a relative increase of 3.1% and 30.0% for the peak and overall BTX carbon yield (based on the feedstock). These findings indicate that the strategy of cofeeding in situ produced toluene for the conversion of glycerol to aromatics has potential to increase BTX yields. In addition, BTX production on the catalyst (based on the fresh catalyst during the first run for TOS of 8.5 h and without regeneration) is significantly improved to 0.547 ton ton-1catalyst (excluding the 76% of toluene product that is 0.595 ton ton-1catalyst for the recycle in the cofeed) for glycerol/toluene cofeed, which was 0.426 ton ton-1catalyst for glycerol alone. In particular, this self-sufficient toluene product recycling strategy is advantageous for the production and selectivity (relative increase of 84.4% and 43.5% during TOS of 8.5 h) of biobased xylenes.
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As Vehicle-to-Everything (V2X) communication technologies gain prominence, ensuring human safety from radiofrequency (RF) electromagnetic fields (EMF) becomes paramount. This study critically examines human RF exposure in the context of ITS-5.9 GHz V2X connectivity, employing a combination of numerical dosimetry simulations and targeted experimental measurements. The focus extends across Road-Side Units (RSUs), On-Board Units (OBUs), and, notably, the advanced vehicular technologies within a Tesla Model S, which includes Bluetooth, Long Term Evolution (LTE) modules, and millimeter-wave (mmWave) radar systems. Key findings indicate that RF exposure levels for RSUs and OBUs, as well as from Tesla’s integrated technologies, consistently remain below the International Commission on Non-Ionizing Radiation Protection (ICNIRP) exposure guidelines by a significant margin. Specifically, the maximum exposure level around RSUs was observed to be 10 times lower than ICNIRP reference level, and Tesla’s mmWave radar exposure did not exceed 0.29 W/m2, well below the threshold of 10 W/m2 set for the general public. This comprehensive analysis not only corroborates the effectiveness of numerical dosimetry in accurately predicting RF exposure but also underscores the compliance of current V2X communication technologies with exposure guidelines, thereby facilitating the protective advancement of intelligent transportation systems against potential health risks.
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This paper compares different low-cost sensors that can measure (5G) RF-EMF exposure. The sensors are either commercially available (off-the-shelf Software Defined Radio (SDR) Adalm Pluto) or constructed by a research institution (i.e., imec-WAVES, Ghent University and Smart Sensor Systems research group (S3R), The Hague University of Applied Sciences). Both in-lab (GTEM cell) and in-situ measurements have been performed for this comparison. The in-lab measurements tested the linearity and sensitivity, which can then be used to calibrate the sensors. The in-situ testing confirmed that the low-cost hardware sensors and SDR can be used to assess the RF-EMF radiation. The variability between the sensors was 1.78 dB on average, with a maximum deviation of 5.26 dB. Values between 0.09 V/m and 2.44 V/m were obtained at a distance of about 50 m from the base station. These devices can be used to provide the general public and governments with temporal and spatial 5G electromagnetic field values.
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In this article a generic fault detection and diagnosis (FDD) method for demand controlled ventilation (DCV) systems is presented. By automated fault detection both indoor air quality (IAQ) and energy performance are strongly increased. This method is derived from a reference architecture based on a network with 3 generic types of faults (component, control and model faults) and 4 generic types of symptoms (balance, energy performance, operational state and additional symptoms). This 4S3F architecture, originally set up for energy performance diagnosis of thermal energy plants is applied on the control of IAQ by variable air volume (VAV) systems. The proposed method, using diagnosis Bayesian networks (DBNs), overcomes problems encountered in current FDD methods for VAV systems, problems which inhibits in practice their wide application. Unambiguous fault diagnosis stays difficult, most methods are very system specific, and finally, methods are implemented at a very late stage, while an implementation during the design of the HVAC system and its control is needed. The IAQ 4S3F method, which solves these problems, is demonstrated for a common VAV system with demand controlled ventilation in an office with the use of a whole year hourly historic Building Management System (BMS) data and showed it applicability successfully. Next to this, the influence of prior and conditional probabilities on the diagnosis is studied. Link to the formal publication via its DOI https://doi.org/10.1016/j.buildenv.2019.106632
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