Typical Measures Research Articles

AS MEDIDAS COERCITIVAS NA AÇÃO DE EXECUÇÃO DE ALIMENTOS NO BRASIL E NO CHILE: análise dos apremios no ordenamento jurídico chileno e sua aplicabilidade ou não no ordenamento jurídico brasileiro.

O presente artigo versa sobre as medidas coercitivas na ação de execução de alimentos no Brasil e no Chile, especialmente no estudo dos apremios utilizados no ordenamento jurídico chileno e sua aplicabilidade ou não no ordenamento jurídico brasileiro. Para isso, faz-se necessário o estudo de algumas decisões judiciais, que adotaram as medidas que serão tratadas no presente artigo, pautando-se nos meios executórios atípicos trazidos pelo Código de Processo Civil. Assim, foi possível evidenciar que a adoção de algumas destas medidas podem demonstrar ofensa à garantia fundamental do devido processo constitucional, vez que para a utilização das medidas executórias atípicas permitidas pelo Código de Processo Civil, é de suma importância à adoção de parâmetros razoáveis e proporcionais em cada caso levado à apreciação do poder judiciário, devendo sempre ser pautadas sob a égide dos princípios basilares trazidos pela Constituição e pelo próprio Código de Processo Civil.

CG-SENSE revisited: Results from the first ISMRM reproducibility challenge.

The aim of this work is to shed light on the issue of reproducibility in MR image reconstruction in the context of a challenge. Participants had to recreate the results of "Advances in sensitivity encoding with arbitrary k-space trajectories" by Pruessmann et al. METHODS: The task of the challenge was to reconstruct radially acquired multicoil k-space data (brain/heart) following the method in the original paper, reproducing its key figures. Results were compared to consolidated reference implementations created after the challenge, accounting for the two most common programming languages used in the submissions (Matlab/Python). Visually, differences between submissions were small. Pixel-wise differences originated from image orientation, assumed field-of-view, or resolution. The reference implementations were in good agreement, both visually and in terms of image similarity metrics. While the description level of the published algorithm enabled participants to reproduce CG-SENSE in general, details of the implementation varied, for example, density compensation or Tikhonov regularization. Implicit assumptions about the data lead to further differences, emphasizing the importance of sufficient metadata accompanying open datasets. Defining reproducibility quantitatively turned out to be nontrivial for this image reconstruction challenge, in the absence of ground-truth results. Typical similarity measures like NMSE of SSIM were misled by image intensity scaling and outlier pixels. Thus, to facilitate reproducibility, researchers are encouraged to publish code and data alongside the original paper. Future methodological papers on MR image reconstruction might benefit from the consolidated reference implementations of CG-SENSE presented here, as a benchmark for methods comparison.

Artifact Correction in Short-Term HRV during Strenuous Physical Exercise.

Heart rate variability (HRV) analysis can be a useful tool to detect underlying heart or even general health problems. Currently, such analysis is usually performed in controlled or semi-controlled conditions. Since many of the typical HRV measures are sensitive to data quality, manual artifact correction is common in literature, both as an exclusive method or in addition to various filters. With proliferation of Personal Monitoring Devices with continuous HRV analysis an opportunity opens for HRV analysis in a new setting. However, current artifact correction approaches have several limitations that hamper the analysis of real-life HRV data. To address this issue we propose an algorithm for automated artifact correction that has a minimal impact on HRV measures, but can handle more artifacts than existing solutions. We verify this algorithm based on two datasets. One collected during a recreational bicycle race and another one in a laboratory, both using a PMD in form of a GPS watch. Data include direct measurement of electrical myocardial signals using chest straps and direct measurements of power using a crank sensor (in case of race dataset), both paired with the watch. Early results suggest that the algorithm can correct more artifacts than existing solutions without a need for manual support or parameter tuning. At the same time, the error introduced to HRV measures for peak correction and shorter gaps is similar to the best existing solution (Kubios-inspired threshold-based cubic interpolation) and better than commonly used median filter. For longer gaps, cubic interpolation can in some cases result in lower error in HRV measures, but the shape of the curve it generates matches ground truth worse than our algorithm. It might suggest that further development of the proposed algorithm may also improve these results.

Are green cities sustainable? A degrowth critique of sustainable urban development in Copenhagen

ABSTRACT This paper proposes a case-based degrowth critique of sustainable urban development strategies. Copenhagen, European Green Capital in 2014, is considered a role model of planning for sustainability. Does this hold in a degrowth perspective? Sustainable development assumes that environmental impacts can decline while the economy grows. Degrowth maintains that such a process of absolute decoupling is infeasible. Analyzing Copenhagen’s planning documents in this perspective, I find three factors that make the city’s sustainability strategy ineffective for ecological sustainability. First, Copenhagen’s strategy for climate neutrality is based on externalization: only emissions produced locally are counted. Meanwhile, emissions produced outside of the city for products and services consumed locally remain high. Secondly, policies focus on the efficiency of activities rather than their overall impact: efficiency gains are considered reductions of impact, but really mean slower growth of impact. Finally, sustainability measures are proposed as a ‘green fix’, to increase competitiveness and promote economic growth, leading to increased consumption and impact. Analyzing the critical case of Copenhagen in a degrowth perspective, sheds doubts on sustainable urban development, but does not imply the rejection of all its typical planning measures. This induces reflections on how these results can contribute to a degrowth-oriented urban planning.

Intelligent detection of fetal hydrocephalus

ABSTRACT This paper describes an enhanced process able to attain righteous classification of morphological malformation in foetal head ultrasound images. These anomalies can be detected approximately 20–22 weeks. In effect, the experts rely on manual analysis by extracting typical biometric measures from head region to interpret pregnancy evolution. The contribution of this work presents a totally computerised method of cerebral defect-recognition based on conventional neural network (CNN) in order to supply quantitative appraisal of hydrocephalus (HD) or healthy (HL) topics. The obtained results have achieved an important classification (Accuracy = 97.20%, sensitivity = 97.95% and specificity = 98.23%) when applying the CNN. The proposed methodology enables us to assess the anomalous cases in premature period within a reduced processing time. Experimental results prove the success of the proposed rating system for a suitable diagnostic of foetal head hydrocephalus when compared to previous work.

Deep learning with wearable based heart rate variability for prediction of mental and general health

The ubiquity and commoditisation of wearable biosensors (fitness bands) has led to a deluge of personal healthcare data, but with limited analytics typically fed back to the user. The feasibility of feeding back more complex, seemingly unrelated measures to users was investigated, by assessing whether increased levels of stress, anxiety and depression (factors known to affect cardiac function) and general health measures could be accurately predicted using heart rate variability (HRV) data from wrist wearables alone. Levels of stress, anxiety, depression and general health were evaluated from subjective questionnaires completed on a weekly or twice-weekly basis by 652 participants. These scores were then converted into binary levels (either above or below a set threshold) for each health measure and used as tags to train Deep Neural Networks (LSTMs) to classify each health measure using HRV data alone. Three data input types were investigated: time domain, frequency domain and typical HRV measures. For mental health measures, classification accuracies of up to 83% and 73% were achieved, with five and two minute HRV data streams respectively, showing improved predictive capability and potential future wearable use for tracking stress and well-being.

Dangerous shortage of blood banks as an indirect effect of SARS-CoV-2: An obstetrics perspective.

ObjectiveTo describe the impact of the SARS‐CoV‐2 pandemic on the frequency of blood donation (BD) in a Latin American hospital and how the social isolation policy implemented during the pandemic jeopardizes the quality of postpartum hemorrhage (PPH) care due to shortages at blood banks (BB).MethodsA retrospective, descriptive study was conducted, lasting for 31 months, including the start of the pandemic. Frequency of BD and the use of obstetric emergency services was observed.ResultsA direct relationship was observed between the pandemic and a decrease in BD. Although emergency obstetric visits decreased, the frequency of deliveries and cases of PPH remained unchanged. After applying strategies to promote voluntary BD, a very slight increase was observed in the frequency of BD, with a negative indicator persisting between donation and blood demand.ConclusionThe SARS‐CoV‐2 pandemic has led to shortages at BBs. In this context, typical measures to encourage an altruistic attitude toward BD have not had a significant impact. As causes of PPH continue, quality of care may be affected by the current situation at BBs. Governments and institutions must implement new strategies to motivate BD.

The Complex Interrelationship of Work-Related Factors Underlying Risky Driving Behavior of Food Delivery Riders in Athens, Greece.

BackgroundIn this study, the association of work and demographic characteristics with different traffic offenses committed by food delivery riders in Greece was examined. Previous research has identified various factors related to risky driving however, there is a need for exploring the complex interrelationship of work-related factors underlying risky driving behavior.Materials and MethodsA 2-items uestionnaire was used exploring delivery riders demographic characteristics, terms of employment, issues of concern during work and type of traffic offenses committed. In total, uestionnaires were analyzed using logistic regression in order to identify characteristics independently associated with serious traffic offenses, namely, red-light running and helmet non-use.ResultsThe analysis showed that: (i) typical health and safety measures had no effect on serious traffic offenses, (ii) young age was related to both offenses however (iii) different sets of work conditions were associated with reports of red-light running (i.e. low work experience, use of personal vehicle for work, and payment by hour) and helmet non-use respectively (i.e. intense work pace, high tip income per day and low concern about vehicle condition).ConclusionThe above findings provide evidence that serious traffic offenses are manifestations of underlying conflict experienced by the riders between safety and various performance criteria. Each one of the two offenses is related to different rider profiles aiming to satisfy different goals, namely, those mainly trying to maximize profit non-helmet users and those, mostly inexperienced ones, trying to cope with work pressure red light runners. Potential regulatory measures to alleviate risky practices are discussed.

Soil Erosion and Typical Soil and Water Conservation Measures on Hillslopes in the Chinese Mollisol Region

The Chinese Mollisol region is affected by soil erosion. Soil and water conservation (SWC) measures are effective in preventing these phenomena. However, few studies have systematically reviewed soil erosion and SWC measures in this region. The objectives of this paper were to analyze soil erosion and identify typical SWC measures on hillslopes in this Mollisol region. A literature review and analysis were conducted. Soil erosion is widespread in this region and is dominated by snowmelt and wind erosion in winter and spring, rainfall in summer and wind erosion in autumn. The A-horizon thicknesses and organic matter content of the Mollisol decreased with an increase in the number of years of cultivation. Therefore, controlling soil erosion is a means to protect this precious Mollisol resource. The characteristics of 39 SWC measures used on hillslopes were summarized. Among these measures, the contour ridge, large ridge, minimal tillage with residue mulching, no-tillage, straw returning, slope terrace, ridge belt, and agricultural protection forest approaches were the most typical SWC measures. Furthermore, the new tillage measure of half-ridge planting needs to be examined in future studies. In conclusion, it is of practical significance to select suitable SWC measures for different hillslopes in the Mollisol region.

Fibre optic sensing of ageing railway infrastructure enhanced with statistical shape analysis

Developing early-warning sensor-based maintenance systems for ageing railway infrastructure, such as masonry arch bridges, can be a challenging task due to the difficulty of identifying degradation/damage as the source of small, gradual changes in sensor data, as opposed to other environmental and loading effects. This paper offers a new method of applying statistical modelling and machine learning to enhance the interpretation of fibre optic sensing data, and, therefore, improve deterioration monitoring of railway infrastructure. Dynamic strain and temperature monitoring data between 2016 and 2019 from a fibre Bragg grating (FBG) network installed in a Victorian railway viaduct are first presented. The statistical shape analysis adopted in this study is modified to track changes in the shape of FBG signals directly linked to train speed and dynamic strain amplitudes. The method is complemented by a support vector machine, which is trained to identify different classes of trains. After distinguishing train types, dynamic strain was found to be clearly correlated to temperature, verifying previous findings. No correlation with train speed was observed. The integrated system is then able to compensate for changes in the structural performance due to variations in train loading and ambient temperature, and identify changes in dynamic deformation caused by degradation, in an order comparable to the signal noise (± 2 micro-strain). As a result, the new procedure is shown to be capable of detecting small magnitudes of local degradation well before this degradation manifests itself in typical global measures of response.

Sensitivity of conventional gait model to lower limb marker misplacement

Walking speed influences a variety of typical outcome measures in gait analysis. Many researchers use a participant’s preferred walking speed (PWS) during gait analysis with a goal of trying to capture how a participant would typically walk. However, the best practices for estimating PWS and the impact of laboratory size and walk distance are still unclear.Is measured PWS consistent across different distances and between two laboratory sites?Participants walked overground at a “comfortable speed” for six different conditions with either dynamic (4, 6, 10, and 400 m) or static (4 and 10 m) starts and stops at two different data collection sites. Repeated measures ANOVA with Bonferroni corrections were used to test for differences between conditions and sites.Participants walked significantly faster in the 4, 6, and 10 m dynamic conditions than in the 400 m condition. On average, participants walked slower in the static trials than the dynamic trials of the same distance. There was a significant interaction of lab and condition and so results were examined within each lab. Across both labs, we found that the 4 and 10 m dynamic conditions were not different than the 6 m dynamic condition at both sites, while other tests did not provide consistent results at both sites.We recommend researchers use a 6 m distance with acceleration and deceleration zones to reliably test for PWS across different laboratories. Given some of the differences found between conditions that varied by site, we also emphasize the need to report the test environment and methods used to estimate PWS in all future studies so that the methods can be replicated between studies.

Organic carbon, nitrogen accumulation, and soil aggregate dynamics as affected by vegetation restoration patterns in the Loess Plateau of China

Afforestation and natural succession on former croplands are typical measures used for revegetation in ecologically fragile areas worldwide. However, there are few studies regarding the differences between natural grasslands and artificial plantations in terms of soil aggregate dynamics, organic carbon (OC), and total nitrogen (TN) accumulation. We sampled soils from farmland (FL) and from two vegetation restoration patterns [Robinia pseudoacacia plantations (RP) and natural grasslands (NG)] of two age classes (18 and 42 years) on the Loess Plateau of China. The size-distribution and stability of soil aggregates, as well as OC and TN stocks in bulk soil and aggregates were measured. Revegetation of FL resulted in considerable increases in bulk soil OC and TN stocks at depths of 0–40 cm: OC increased by 101.3% in NG and 75.5% in RP, and TN by 77.5% in NG and 106.1% in RP. Bulk soil OC stocks in 18- and 42-year-old NG at depths of 0–40 cm were 9.0% and 17.4% higher, respectively, than those in RP of the same age. Conversely, the 18- and 42-year-old RP had 18.6% and 16.4% higher TN stocks than those in NG of the same age. Microaggregates dominated aggregate-size distribution in all land uses and had the highest OC and TN stocks. NG soils had higher proportions of macroaggregates and mesoaggregates and greater aggregate stability than RP soils of the same restoration age. However, there was no significant difference in macroaggregate- and mesoaggregate-associated OC and TN stocks between NG soils and RP soils of the same age. Furthermore, bulk soil OC and TN stocks were strongly associated with aggregate stability. Bulk soil OC stocks were positively correlated with mesoaggregate-associated OC stocks, whereas TN stocks in bulk soil were closely related to macroaggregate-associated TN stocks. Overall, the results of this study suggest that restoration with RP favors soil N accumulation, whereas NG may be optimal for increasing C sequestration and stabilizing soil aggregates in the Loess Plateau.

EVALUATION OF DEBLOCKING METHODS FOR CHANG’E-4 DESCENT IMAGES

Abstract. Chang’e-4 lunar probe has successfully landed on the far side of the moon in Von Kármán crater inside the South Pole-Aitken (SPA) basin at 10:26 am on January 3, 2019. Due to the reduction of the coding rate, obvious block effects appear at the boundaries of descent images. Unblock, adaptive fast bilateral filtering, structure-texture enhancement and high-order Markov random field methods, are applied to remove the block effect of the descent images. Based on analysing the quality of descent images, quantitative comparison of four methods is performed using simulated compressed 1:64 descent images and real images. Comprehensive analysis was performed using typical measures such as PSNR, SSIM and NIQE. Experimental results show that adaptive fast bilateral filtering is better than other methods. The deblocked 1:64 image sequences have been used to assist localizing the landing point quickly during the mission.

Confounding in Studies on Metacognition: A Preliminary Causal Analysis Framework.

By definition, metacognitive processes may monitor or regulate various stages of first-order processing. By combining causal analysis with hypotheses expressed by other authors we derive the theoretical and methodological consequences of this special relation between metacognition and the underlying processes. In particular, we prove that because multiple processing stages may be monitored or regulated and because metacognition may form latent feedback loops, (1) without strong additional causal assumptions, typical measures of metacognitive monitoring or regulation are confounded; (2) without strong additional causal assumptions, typical methods of controlling for first-order task performance (i.e., calibration, staircase, including first-order task performance in a regression analysis, or analyzing correct and incorrect trials separately) not only do not deconfound measures of metacognition but may even introduce bias; (3) that the first two problems cannot be solved by using simple models of decision-making derived from Signal Detection Theory. We conclude the paper by advocating robust methods of discovering properties of latent mechanisms.

Design of standard security measures database for various types of maintenance operations

With the continuous deepening of smart grid construction, more and more smart substations are being used in actual projects. Compared with traditional substations, smart substations have realized digitalization of information, communication network, and standardization of sharing. However, the secondary circuit of intelligent substation has high integration and no obvious electrical isolation point, so the traditional safety measures are no longer suitable for the actual situation of intelligent substation. Therefore, based on the analysis of typical equipment security measures, this article designs a set of general rules for automatic generation of security measures according to the relevant specifications of security measures of intelligent substations. Through the modeling of different maintenance tasks, the characteristics of the safety measures applied to the intelligent substation equipment are analyzed, and the designed safety measures are classified according to the equipment type and operation mode to establish a safety measures database; finally, according to the established database Develop an automated ticket generation plan.

Never Change a Running System – What Worked for Personnel Selection Works for Promotion

The economic utility of a diligent use of valid personnel selection methods for hiring and promoting decisions is highly recognized across organizations and industries. Meta-analytical results support the fact that General Mental Ability (GMA) tests and Situational Judgment Tests (SJT) explain unique variance in typical criterion measures of selection and promotion processes (i.e. job performance). In this connection, job analysis often leads to the assessment of similar job requirements for selection and promotion decisions, fostering the idea of using the same tools for selection and promotion. However, little is known about how their repetitive usage affects the predictive validity of proven test concepts. After being selected with similar GMA tests (numeric reasoning, verbal reasoning, logical reasoning) and an SJT several years earlier, the current study examines the predictive validity of the given test formats for a leadership promotion program within a police department. 119 police officers and executives participated in the study. Results show incremental validity of the SJT above the three different test dimensions of GMA. These robust validities for the parallel test formats should urge decision makers to invest in specific item pools and proven test concepts to maximize utility in HR processes.

The µ-opioid system in midline thalamic nuclei modulates defence strategies towards a conditioned fear stimulus in male mice.

Background:Nuclei located in the dorsal midline thalamus, such as the paraventricular nucleus of the thalamus (PVT), are crucial to modulate fear and aversive behaviour. In addition, the PVT shows a dense expression of µ-opioid receptors (MORs) and could mediate the anxiolytic effects of opioids.Methods:We analysed the contribution of MORs in the dorsal midline thalamus (i.e. the PVT) to the performance of mice in a classical fear conditioning paradigm. We locally injected a specific agonist (DAMGO), an antagonist (CTAP) of MOR or saline as a control into the dorsal midline thalamus of male mice, prior to fear extinction training. We assessed freezing as a typical measure of fear and extended our analysis by evaluation of aversive, non-aversive and neutral behavioural features using compositional data analysis.Results:Pharmacological blockade of MORs through CTAP in the dorsal midline thalamus induced a fear memory extinction deficit, as evidenced by maintained freezing during extinction sessions. Stimulation of MORs by DAMGO resulted in an overall increase in locomotor activity, associated with decreased freezing during recall of extinction. Compositional data analysis confirmed the freezing-related pharmacological effects and revealed specific differences in basic behavioural states. CTAP-treated mice remained in an aversive state, whereas DAMGO-treated mice displayed predominantly neutral behaviour.Conclusions:Fear extinction requires the integrity of the µ-opioid system in the dorsal midline thalamus. Pharmacological stimulation of MOR and associated facilitation of fear extinction recall suggest a potential therapeutic avenue for stress-related or anxiety disorders.

New Electrosurgical Technologies for High Amputations of the Lower Limbs

We present here results obtained using hightech bipolar instruments with an electrosurgical device and a non-linear dynamic feedback system for excision of large tissue blocks. The effectiveness of using bipolar scissors with blades made of nanostructured zirconium dioxide and thermostabilized bipolar forceps was assessed using high amputation of the lower limbs as an example. Significant results were obtained showing that the use of innovatory electrosurgical technologies for transfemoral amputation in patients with terminal-stage peripheral arterial disease increases the typical clinical measures of efficacy by an average of 39%. The results can be taken as the basis for a new method of using electrosurgical technology for high amputations of the lower limbs.

Topology optimization of compliant mechanisms considering strain variance

In this work, compliant mechanisms are designed by using multi-objective topology optimization, where maximization of the output displacement and minimization of the strain are considered simultaneously. To quantify the strain, we consider typical measures of strain, which are based on the p-norm, and a new class of strain quantifying functions, which are based on the variance of the strain. The topology optimization problem is formulated using the Solid Isotropic Material with Penalization (SIMP) method, and the sensitivities with respect to design changes are derived using the adjoint method. Since nearly void regions may be highly strained, these regions are excluded in the objective function by a projection method. In the numerical examples, compliant grippers and inverters are designed, and the tradeoff between the output displacement and the strain function is investigated. The numerical results show that distributed compliant mechanisms without lumped hinges can be obtained when including the variance of the strain in the objective function.

Teleconnection-based evaluation of seasonal forecast quality

In response to the high demand for more skillful climate forecasts at the seasonal timescale, innovative climate prediction systems are developed with improved physics and increased spatial resolution. Alongside the model development process, seasonal predictions need to be evaluated on past years to provide robust information on the forecast performance. This work presents the quality assessment of the Meteo-France coupled climate prediction system, taking advantage of an experiment performed with 90 ensemble members over a 37-year re-forecast period from 1979 to 2015. We focus on the boreal winter season initialised in November. Beyond typical skill measures we evaluate the model capability in reproducing ENSO and NAO teleconnections on precipitation and near surface temperature respectively. Such an assessment is carried out first through a composite analysis, and shows that the model succeeds in reproducing the main patterns for near surface temperature and precipitation. A covariance method leads to consistent results. Finally we find that the teleconnection representation of the model is not affected by shortening the verification period and reducing the ensemble size and therefore can be used to evaluate operational seasonal forecast systems.