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.

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.

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 $225 \times 143\ \mu\mathrm{m}^{2}$.

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.

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.

The vehicle routing problem is one of the most complex problems in the field of combinatorial optimization. Creating optimal routes leads to timely delivery of orders to end customers, which increases the efficiency of the company and enables maximum earnings. The problem of vehicle routing with a series of real-world constraints is called the rich vehicle routing problem (RVRP). The paper presents an approach to solving RVRP, where the asymmetric routing problem with a heterogeneous vehicle fleet, time windows, customer-vehicle constraints and a number of others is observed. The approach solves the problem in two phases, by dividing customers into clusters using a discrete metaheuristic Bat algorithm, and by solving the routing problem for each obtained cluster. The proposed approach has been tested for 26 days of delivery from large warehouses in Bosnia and Herzegovina. Significant savings were achieved compared to previously implemented approaches. All created routes were feasible. The approach automatically creates routes, and gives results in a shorter time than previously used approaches. Time does not increase significantly with the increase in the number of customers, which is a great advantage of the proposed approach.

This paper represents a solution to the problem of automatization of a web page robustness score grading. Robustness of a web page is best defined as a property of a specific web page to keep its layout and style of elements after applying different modifications. The rapid development of web pages has enabled a quick creation of numerous web pages, but the question is what is the quality of those web pages in terms of robustness. Automatic grading enables a relatively fast way of creating a metric in terms of the score that specific web pages get after being tested for the level of robustness. The research framework consists of different technologies and concepts that have been used during the implementation of a practical solution. The paper describes data structures that have been used to represent web pages as well as the machine learning methods such as neural networks, used to calculate the robustness score.

With the arrival of COVID-19 pandemic in March of 2020 the first lock-down and closing of schools and faculties occurred. Educational institutions had to find a solution overnight. To ensure the continuity of schooling was a great challenge, the strategy of the faculties has only indicated digital transformation, and a small number of faculty staff was ready to face this new situation (according to the research had already been carried out). Teachers that had already used digital technologies and e-learning found it easier to form their classes in online environment that they were already familiar with. But those teachers that have never done so, found themselves facing a great challenge. Faced with the inability to hold classes in a traditional classroom way, they were challenged to quickly transition to online environment and ensure the completion of the academic year. With the arrival of the new academic year, the return to the classic way of classes was expected, but this did not completely occur. The pandemic did not cease and again higher education institutions face closing and classes are more and more held remotely. Levels of preparation and experience of teachers and students at the University of Mostar differ greatly. This paper has a goal of presenting experiences and needs of the teachers of the Faculty of Humanities and Social Sciences and ascertaining how these experiences can be, and how much they have been used relating to the situation we find ourselves in again.

This paper focuses on reviewing relevant work on autonomous ground systems for concrete bridge inspection. The current inspection of bridges is still based on visual inspection by inspectors or by using semi-destructive techniques. Current inspection practices require a large amount of time for inspection. In addition, complex scaffolding or expensive equipment is required for inaccessible areas, which also poses a risk to the safety of inspectors. These drawbacks could be overcome by using robotic systems equipped with non-destructive techniques (NDT). This paper presents the ground robotic systems that have been used in the inspection of concrete bridges, mainly for the localization of reinforcement, corrosion assessment and crack detection.

In today's digital age, presence on the Internet and the Web mean presence in general life. This is generally more pronounced in the context of higher education because these institutions are the primary drivers of overall social development. The quality and highly accessible website of each university is a must as these websites are generally the first contact and first impression for new potential students and also the first step for establishing cooperation with the social economy and society. For this reason, websites need to meet some of the basic standards when it comes to accessibility of the content they provide and it is essential to ensure that content on the websites can be accessed by people with disabilities. This paper deals with the analysis of websites of universities in Bosnia and Herzegovina in the context of their accessibility, from one side, and their position on the international scene in the context of the Webometrics list of universities, on the other side. Based on the obtained results and conducted analysis, recommendations were given on how to improve some of the elements on websites in order to make these websites more accessible in accordance with the standards related to this topic.

This paper deals with the development of control software for a remotely operated vehicle (ROV) as part of an automated fish cage inspection system in aquaculture. The ROV navigates autonomously around the fish cages streaming video to the topside computer that runs the algorithms for vertical rope detection. The topside computer sends back the velocity references to the ROV in real-time in order to successfully complete the inspection task. These images are also used to determine the state of net biofouling using a pre-trained convolutional neural network to help determine which nets are in need of cleaning. Robot Operating System (ROS) framework is developed to enable the topside computer to access the video stream from the ROV, process the images, and send back velocity references that would result in the complete inspection of fish cages. The inspection task is planned by following the recognizable rope segments of the outer structure of the fish cage downwards by controlling the vehicle's yaw, heave, and depth.

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.