In this paper, we present a novel algorithm – DRGBT (Dynamic Rapidly-exploring Generalized Bur Tree), intended for motion planning in dynamic environments. The main idea behind DRGBT lies in a so-called adaptive horizon, consisting of a set of prospective target nodes that belong to a predefined $\mathcal{C}$-space path, which originates from the current node. Each node is assigned a weight that depends on relative distances and captured changes in the environment. The algorithm continuously uses a suitable horizon assessment to decide when to trigger the replanning procedure. A comprehensive simulation study is performed, covering a variety of manipulators, where DRGBT is compared to a state-of-the-art algorithm. Results indicate some promising features of the proposed method.

Background: Patients with chronic diseases, like diabetes need to continuously perform tasks associated with self-management especially with medications they use. It is shown that the patients with diabetes with limited HL and PTHL cannot read medication labels correctly, may misuse their medications, spend much more on therapy and generally have difficulties in understanding printed care instructions and perceiving health advice and warnings. There has been an increasing demand for valid and reliable instruments for HL and PTHL assessment in this population. This review aims to search and critically discuss instruments used to assess HL and PTHL in people with type 2 diabetes and propose their use in different settings. Methods: Authors conducted a comprehensive, electronic search of original studies using a structured approach of the Scopus and PubMed databases, during November and the first 2 weeks of December 2020 to find relevant papers. The review was conducted in accordance with the Cochrane guidelines and the reporting was based on the PRISMA-ScR. The comparison of instruments was made by utilizing a comparison model related to their structure, measurement scope, range, psychometric properties, validation, strengths, and limitations. Results: The final number of included studies was 24, extracting the following identified instruments: Korean Functional Test HL, NVS, FCCHL, HLS-EU-47, TOFLHA, S-TOFHLA, REALM-R, 3-brief SQ, REALM, HLQ and DNT-15. In all, FCCHL and 3-brief SQ are shown with the broadest measurement scopes. They are quick, easy, and inexpensive for administration. FCCHL can be considered the most useful and comprehensive instrument to screen for inadequate HL. The limitation is that the English version is not validated. Three-brief SQ has many advantages in comparison to other instruments, including that it is less likely to cause anxiety and shame. These instruments can be considered the best for measuring functional HL in patients with diabetes mellitus type 2 and other chronic diseases. PTHL instruments (REALM and DNT-15) did not find the best application in this population. Conclusions: The future research should be directed in validation of the FCCHL in English and establishing of the structural validity of this questionnaire. Developing a specific PTHL questionnaire for this population will be of great help in management of their disease.

The airport environment is an extremely complex system with a large number of interdependent factors. A large number of airports have limited infrastructure capacity. One of the solutions to increase the capacity and efficiency of the airport is spatial infrastructure expansion. However, a large number of airports are close to populated areas, and further expansion is not possible. When implementing operational infrastructure solutions, it is necessary to establish a correlation between the Key Performance Indicators (KPI) and the existing limiting factors of the airport and the airspace in the vicinity of the airport. This paper will describe the basic performance indicators important for single-runway airports. Moreover, it will present the scalable and modular aviation software solution. It is used for simulation, allocation, and optimization systems for airport airside. The possibilities of using the output of the software tool and the quality of the datasets thus collected for the application of different prediction algorithms will be investigated. In this way, an attempt would be made to achieve a synergy of simulation tools and advanced algorithms. It will help decision-makers to determine the actual complexity and limitations during the planning and future investments.

An analog time of flight correlator designed in a 150 nm LFoundry CMOS process, capable of correlating photon pulses with an input clock for the use with single-photon avalanche diodes (SPADs) is presented. This correlator will allow highly sensitive and high precision indirect time of flight (iTOF) distance measurement with modulation frequencies up to 1 GHz and a distance resolution of 3 mm and 1.3 mm for a total measurement time of only $4\ \mu\mathrm{s}$ and $40\ \mu\mathrm{s}$, respectively. Additionally long integration times are possible, which guarantee operation with high background-to-signal-ratios (BSR). The small size and low power consumption of less than 1 mW allow the use of many correlators on a single chip. Two correlators and a quenching circuit are integrated on a chip with a size of $1.5 \times 1.3\ \text{mm}^{2}$. The size of a single correlator is $225 \times 143\ \mu\mathrm{m}^{2}$.

In this work a single photon avalanche diode (SPAD) based phase measurement circuit for distance measurements using continuously modulated light in a 150 nm CMOS technology is presented. An on-chip quadruple-voltage quenching circuit, allowing up to 7.2 V excess bias for external SPADs, generates pulses synchronous to the detection times of single photons. Circuit simulations show, that a precision of 0.54 mm can be achieved for distance measurements in low background light environments, in a measurement time of 200 μs. The efficiency of background light suppression can be improved by increasing the measurement time. Even a factor of 100:1 of background to measurement light should allow sub-cm precision given a sufficient measurement time. Correlation frequencies up to 1 GHz are possible. One correlator block has a size of 230×210 µm2 and the power consumption for each correlator is 391 µW.

Existing literature compares neuromarketing and traditional methods, making the questionable assumption that these are monolithic measurement alternatives all serving the same, predictive purpose. This study examines and empirically challenges this notion by relying on a neuroscientific perspective and a robust empirical study to examine the correspondence of expanded sets of diverse electroencephalogram (EEG) and survey advertising indicators. The key findings are that EEG and survey indicators measure different kinds of emotions (and attention) and that the newly developed, momentary EEG indicators are superior to the conventional, aggregated ones. The findings suggest that moment-to-moment EEG advertising indicators, such as peak emotions during branding moments, distinctively enhance advertising effectiveness evaluation and enhancement.

The National Association for the Education of Young Children recently revised its Developmentally Appropriate Practice (DAP), the standard for early childhood care and education. Josh Thompson and Zlata Stanković-Ramirez explore how DAP has evolved over time and what guidance it provides early childhood educators regarding the interaction between typical waves of child development, children’s individual characteristics, and social and cultural context.

Description Young generations are severely threatened by climate change Under continued global warming, extreme events such as heat waves will continue to rise in frequency, intensity, duration, and spatial extent over the next decades (1–4). Younger generations are therefore expected to face more such events across their lifetimes compared with older generations. This raises important issues of solidarity and fairness across generations (5, 6) that have fueled a surge of climate protests led by young people in recent years and that underpin issues of intergenerational equity raised in recent climate litigation. However, the standard scientific paradigm is to assess climate change in discrete time windows or at discrete levels of warming (7), a “period” approach that inhibits quantification of how much more extreme events a particular generation will experience over its lifetime compared with another. By developing a “cohort” perspective to quantify changes in lifetime exposure to climate extremes and compare across generations (see the first figure), we estimate that children born in 2020 will experience a two- to sevenfold increase in extreme events, particularly heat waves, compared with people born in 1960, under current climate policy pledges. Our results highlight a severe threat to the safety of young generations and call for drastic emission reductions to safeguard their future.

We studied clinical and immunological outcome of Covid-19 in consecutive CLL patients from a well-defined area during month 1–13 of the pandemic. Sixty patients (median age 71 y, range 43–97) were identified. Median CIRS was eight (4–20). Patients had indolent CLL (n = 38), had completed (n = 12) or ongoing therapy (n = 10). Forty-six patients (77%) were hospitalized due to severe Covid-19 and 11 were admitted to ICU. Severe Covid-19 was equally distributed across subgroups irrespective of age, gender, BMI, CLL status except CIRS (p < 0.05). Fourteen patients (23%) died; age ≥75 y was the only significant risk factor (p < 0.05, multivariate analysis with limited power). Comparing month 1–6 vs 7–13 of the pandemic, deaths were numerically reduced from 32% to 18%, ICU admission from 37% to 15% whereas hospitalizations remained frequent (86% vs 71%). Seroconversion occurred in 33/40 patients (82%) and anti-SARS-CoV-2 antibodies were detectable at six and 12 months in 17/22 and 8/11 patients, respectively. Most (13/17) had neutralizing antibodies and 19/28 had antibodies in saliva. SARS-CoV-2-specific T-cells (ELISpot) were detected in 14/17 patients. Covid-19 continued to result in high admission even among consecutive and young early- stage CLL patients. A robust and durable B and/or T cell immunity was observed in most convalescents.

In March 2019, the World Health Organization (WHO) declared that humanity was entering a global pandemic phase. This unforeseen situation caught everyone unprepared and had a major impact on several professional categories that found themselves facing important ethical dilemmas. The article revolves around the category of biomedical and clinical engineers, which were among those most involved in dealing with and finding solutions to the pandemic. In hindsight, the major issues brought to the attention of biomedical engineers have raised important ethical implications, such as the allocation of resources, the responsibilities of science and the inadequacy and non-universality of the norms and regulations on biomedical devices and personal protective equipment. These issues, analyzed one year after the first wave of the pandemic, come together in the appeal for responsibility for thought, action and, sometimes, even silence. This highlights the importance of interdisciplinarity and the definitive collapse of the Cartesian fragmentation of knowledge, calling for the creation of more fora, where this kind of discussions can be promoted.

Purpose This study aims to apply the stimulus-organism-response framework to uncover the underlying mechanism by which the perceived helpfulness of online customer reviews (OCRs) drives behavioural intentions in mobile travel app commerce. Also, the current study explores how vendor-driven perceived usefulness of a product and its attributes influence the mediated relationship between perceived helpfulness of OCRs (OCRs helpfulness) and behavioural intentions. Design/methodology/approach The online survey (n = 151) was used to collect the data. The authors used structural equation modelling and the bias-corrected bootstrap method to test the proposed conceptual model for mediation and moderated-mediation effect. Findings Findings indicate that the perceived OCRs helpfulness has an indirect positive effect, via trust and attitude, on travel app downloading intention. Moreover, results suggest that the presence of vendor cues (vendor-generated informational content about a travel app) does not significantly moderate the mediating effect of perceived OCRs helpfulness on travel app downloading intention. Originality/value The present study reinforces the applicability of the warranting principle in the context of travel app commerce by exploring the relative effectiveness of customer-generated and vendor-generated informational content in influencing travel app downloading intention.

Intra-abdominal infections (IAIs) are common surgical emergencies and have been reported as major contributors to non-trauma deaths in hospitals worldwide. The cornerstones of effective treatment of IAIs include early recognition, adequate source control, appropriate antimicrobial therapy, and prompt physiologic stabilization using a critical care environment, combined with an optimal surgical approach. Together, the World Society of Emergency Surgery (WSES), the Global Alliance for Infections in Surgery (GAIS), the Surgical Infection Society-Europe (SIS-E), the World Surgical Infection Society (WSIS), and the American Association for the Surgery of Trauma (AAST) have jointly completed an international multi-society document in order to facilitate clinical management of patients with IAIs worldwide building evidence-based clinical pathways for the most common IAIs. An extensive non-systematic review was conducted using the PubMed and MEDLINE databases, limited to the English language. The resulting information was shared by an international task force from 46 countries with different clinical backgrounds. The aim of the document is to promote global standards of care in IAIs providing guidance to clinicians by describing reasonable approaches to the management of IAIs.

The aim of this research is to determine the relaxation and creep modulus of 3D printed materials, and the numerical research is based on the finite volume method. The basic material for determining these characteristics is ABS (acrylonitrile butadiene styrene) plastic as one of the most widely used polymeric materials in 3D printing. The experimental method for determining the relaxation functions involved the use of a creep test, in which a constant increase of the stress of the material was performed over time to a certain predetermined value. In addition to this test, DMA (dynamic mechanical analysis) analysis was used. Determination of unknown parameters of relaxation functions in analytical form was performed on the basis of the expression for the storage modulus in the frequency domain. The influence of temperature on the values of the relaxation modulus is considered through the determination of the shift factor. Shift factor is determined on the basis of a series of tests of the relaxation function at different constant temperatures. The shift factor is presented in the form of the WLF (Williams-Landel-Ferry) equation. After obtaining such experimentally determined viscoelastic characteristics with analytical expressions for relaxation modulus and shift factors, numerical analysis can be performed. For this numerical analysis, a mathematical model with an incremental approach was used, as developed in earlier works although with a certain modification. In the experimental analysis, the analytical expression for relaxation modulus in the form of the Prony series is used, and since it is the sum of exponential functions, this enables the derivation of a recursive algorithm for stress calculation. Numerical analysis was performed on several test cases and the results were compared with the results of the experiment and available analytical solutions. A good agreement was obtained between the results of the numerical simulation and the results of the experiment and analytical solutions.

This paper presents two schemes to jointly estimate parameters and states of discrete-time nonlinear systems in the presence of bounded disturbances and noise. The parameters are assumed to belong to a known compact set. Both schemes are based on sampling the parameter space and designing a state observer for each sample. A supervisor selects one of these observers at each time instant to produce the parameter and state estimates. In the first scheme, the parameter and state estimates are guaranteed to converge within a certain margin of their true values in finite time, assuming that a sufficiently large number of observers is used and a persistence of excitation condition is satisfied in addition to other observer design conditions. This convergence margin is constituted by a part that can be chosen arbitrarily small by the user and a part that is determined by the noise levels. The second scheme exploits the convergence properties of the parameter estimate to perform subsequent zoom-ins on the parameter subspace to achieve stricter margins for a given number of observers. The strengths of both schemes are demonstrated using a numerical example.

Subject motion during an MRI sequence can cause ghosting effects or diffuse image noise in the phase-encoding direction and hence is likely to bias findings in neuroimaging studies. Detecting motion artifacts often relies on experts visually inspecting MRIs, which is subjective and expensive. To improve this detection, we develop a framework to automatically quantify the severity of motion artifact within a brain MRI. We formulate this task as a regression problem and train the regressor from a data set of MRIs with various amounts of motion artifacts. To resolve the issue of missing fine-grained ground-truth labels (level of artifacts), we propose Adversarial Bayesian Optimization (ABO) to infer the distribution of motion parameters (i.e., rotation and translation) underlying the acquired MRI data and then inject synthetic motion artifacts sampled from that estimated distribution into motion-free MRIs. After training the regressor on the synthetic data, we applied the model to quantify the motion level in 990 MRIs collected by the National Consortium on Alcohol and Neurodevelopment in Adolescence. Results show that the motion level derived by our approach is more reliable than the traditional metric based on Entropy Focus Criterion and manually defined binary labels.