Background It is known that drug shortages represent a major challenge for all stakeholders involved in the process, but there is little evidence regarding insights into patients′ awareness and perspectives. This study aimed to investigate the patients-perceived drug shortages experience and their view on outcomes in different European hospital settings. Furthermore, we wanted to explore information preferences on drug shortages. Methods A retrospective, cross sectional, a mixed method study was conducted in six European hospital settings. One hospital (H) from each of this country agreed to participate: Bosnia and Herzegovina (H-BiH), Croatia (H-CR), Germany (H-GE), Greece (H-GR), Serbia (H-SE) and Poland (H-PO). Recruitment and data collection was conducted over 27 months from November 2017 until January 2020. Overall, we surveyed 607 patients which completed paper-based questionnaire. Questions related to: general information (demographic data), basic knowledge on drug shortages, drug shortages experienced during hospitalization and information preferences on drug shortage. Differences between hospital settings were analyzed using Chi-squared test or Fisher’s exact test. For more complex contingency tables, Monte Carlo simulations (N = 2000) were applied for Fisher’s test. Post-hoc hospital-wise analyses were performed using Fisher’s exact tests. False discovery rate was controlled using the Bonferroni method. Analyses were performed using R: a language and environment for statistical computing (v 3.6.3). Results 6 % of patients reported experiences with drug shortages while hospitalized which led to a deterioration of their health. The majority of affected patients were hospitalized at hematology and/or oncology wards in H-BiH, H-PO and H-GE. H-BiH had the highest number of affected patients (18.1 %, N = 19/105, p  < 0.001) while the fewest patients were in H-SE (1 %, N  = 1/100, p  = 0.001). In addition, 82.5 %, ( N  = 501/607) of respondents wanted to be informed of alternative treatment options if there was a drug shortage without a generic substitute available. Majority of these patients (66.4 %, N = 386/501) prefer to be informed by a healthcare professional. Conclusions Although drug shortages led to serious medical consequences, our findings show that most of the patients did not perceive shortages as a problem. One possible interpretation is that good hospital management practices by healthcare professionals helped to mitigate the perceived impact of shortages. Our study highlights the importance of a good communication especially between patients and healthcare professionals in whom our patients have the greatest trust.

To promote collaboration across canine science, address reproducibility issues, and advance open science practices within animal cognition, we have launched the ManyDogs consortium, modeled on similar ManyX projects in other fields. We aimed to create a collaborative network that (a) uses large, diverse samples to investigate and replicate findings, (b) promotes open science practices of preregistering hypotheses, methods, and analysis plans, (c) investigates the influence of differences across populations and breeds, and (d) examines how different research methods and testing environments influence the robustness of results. Our first study combines a phenomenon that appears to be highly robust, dogs’ ability to follow human pointing, with a question that remains controversial: do dogs interpret pointing as an informative gesture, as an imperative command, or as a simple associative cue? We collected preliminary data (N = 61) from a single laboratory on two conditions of a 2-alternative object choice task: (1) Ostensive (experimenter pointed to a baited cup after making eye-contact and saying the dog’s name); (2) Non-ostensive (experimenter pointed to a baited cup without making eye-contact or saying the dog’s name). Dogs followed the ostensive point, but not the non-ostensive point, significantly more often than expected by chance. Preliminary results also provided suggestive evidence for variability in point-following across dog breeds. The next phase is the global participation stage of the project. We propose to replicate this protocol in a large and diverse sample of research sites, simultaneously assessing replicability between labs and further investigating the question of dogs’ point-following comprehension.

The development intelligence tools is gaining a new dimension every day, and this is an area of dynamic development. The importance of this paper is to select the tool that represents the best solution for the given needs in public administration. A multi-stage, broad- based survey with clear selection criteria leads to the choice of three tools. Criteria for tool evaluation were set, virtual machines were created, tests and analyzes were performed. The evaluations carried out give the choice of the most accepTable business intelligence tool for use and interoperability in public administration.

Making informed driving decisions requires reliable prediction of other vehicles' trajectories. In this paper, we present a novel learned multi-modal trajectory prediction architecture for automated driving. It achieves kinematically feasible predictions by casting the learning problem into the space of accelerations and steering angles - by performing action-space prediction, we can leverage valuable model knowledge. Additionally, the dimensionality of the action manifold is lower than that of the state manifold, whose intrinsically correlated states are more difficult to capture in a learned manner. For the purpose of action-space prediction, we present the simple Feed-Forward Action-Space Prediction (FFW-ASP) architecture. Then, we build on this notion and introduce the novel Self-Supervised Action-Space Prediction (SSP-ASP) architecture that outputs future environment context features in addition to trajectories. A key element in the self-supervised architecture is that, based on an observed action history and past context features, future context features are predicted prior to future trajectories. The proposed methods are evaluated on real-world datasets containing urban intersections and roundabouts, and show accurate predictions, outperforming state-of-the-art for kinematically feasible predictions in several prediction metrics.

The thematic conception of the work consists of legal issues of special forms of control of state administrative in Bosnia and Herzegovina (at the state level, the level of federal units and districts). The paper analyzes the structure of bodies that perform this type of control, starting with the ombudsman institutions (Ombudsman for Human Rights of Bosnia and Herzegovina, Ombudsman for Children of Republic of Srpska), and with special reference to the institutions of auditors (of which there are four in Bosnia and Herzegovina). The author will present the organization of these institutions, the election of their members (ombudsmen and auditors), the way they act, and the possibilities they have, as well as the legal mechanisms they can use to protect both citizens and the public interest.

Karst aquifers are important sources of thermal and groundwater in many parts of the world, such as the Alpine–Dinaric–Carpathian region in Europe. The Upper Triassic dolomites are regionally recognized thermal and groundwater aquifers but also hydrocarbon reservoirs. They are characterized by predominantly fractured porosity, but the actual share of depositional and diagenetic porosity is rarely investigated. In this research, we presented the geometric characterization of the measured microporosity of the Upper Triassic dolomites of the Žumberak Mts (Croatia), through thin-section image processing and particle analysis techniques. Pore parameters were analyzed on microphotographs of impregnated thin sections in scale. A total of 2267 pores were isolated and analyzed. The following parameters were analyzed: pore area, pore perimeter, circularity, aspect ratio (AR), roundness, solidity, Feret AR, compactness, and fractal dimension. Furthermore, porosity was calculated based on the pore portion in each image. The effective porosity on rock samples was determined using saturation and buoyancy techniques as an accompanying research method. We analyzed distributions of each parameter, their correlation, and most of the parameters are characterized by an asymmetric or asymmetric normal distribution. Parameters that quantify pore irregularities have similar distributions, and their values indicate the high complexity of the pore geometry, which can significantly impact permeability.

Aim: Global expenditure on medicines is rising up to 6% per year driven by increasing prevalence of non-communicable diseases (NCDs) and new premium priced medicines for cancer, orphan diseases and other complex areas. This is difficult to sustain without reforms. Methods: Extensive narrative review of published papers and contextualizing the findings to provide future guidance. Results: New models are being introduced to improve the managed entry of new medicines including managed entry agreements, fair pricing approaches and monitoring prescribing against agreed guidance. Multiple measures have also successfully been introduced to improve the prescribing of established medicines. This includes encouraging greater prescribing of generics and biosimilars versus originators and patented medicines in a class to conserve resources without compromising care. In addition, reducing inappropriate antibiotic utilization. Typically, multiple measures are the most effective. Conclusion: Multiple measures will be needed to attain and retain universal healthcare.

Motivation/Background: positive staphylococci (CPS) are common contaminants of raw milk. Before it is used, various heat treatments are applied to destroy microorganisms, inactivate enzymes and improve technological properties and concentration of dry matter of milk. This work aimed to determine the influence of commonly used heat treatments in diary on presence and number CPS in raw milk from Bosnia and Herzegovina area and to affirm whether there is a difference in efficacy between different treatments. Method: Using the standard method, 40 samples of raw milk from farms were inoculated for counting the initial number of CPS in raw milk. Samples were then exposed to heat treatments in vapor sterilizer and CPS number was counted using the same standard method. Results: Applied treatments included heat treatments at: 68 °C/40 s, 70 °C/15 s, 72 °C/without holding, 63 °C/30 min and 72 °C/15 s. CPS presence was detected in all tested samples of raw milk in numbers ranging from 2,82 to 5,32, with an average of 4,30, calculated as log10 /ml. Conclusions: Raw milk samples collected in the field initially registered a high CPS number. The applied heat treatments were effective to a large extent. The initial CPS count of milk seems to be the most important factor determining the number of CPS after heat treatments as well as traits of the strains.

The molecular strong-field approximation is employed to study high-order harmonic generation by linear and planar polyatomic molecules exposed to an orthogonally polarized two-color laser field, which consists of two orthogonal linearly polarized components with commensurable frequencies. For such a driving field, we find that the harmonic emission rate and the shape of the spectrum strongly depend on the laser-field parameters including the relative phase and the ratio of the intensities of the two components. The values of the relative phase that correspond to the optimal harmonic emission rate, as well as the cutoff position, can be assessed using a classical model. The possible production of an isolated attosecond pulse is investigated. For suitable symmetry of the laser field an attosecond pulse train with only one attosecond pulse per cycle can be generated. Depending on the frequencies of the two field components, the molecular symmetry properties and the orientation of the molecule with respect to the field, the even harmonics can be absent from the spectrum, which can be used to determine the molecular orientation. The emitted harmonics are elliptically polarized and their ellipticity depends on the molecular orientation.

Efficiently approximating local curvature information of the loss function is a key tool for optimization and compression of deep neural networks. Yet, most existing methods to approximate second-order information have high computational or storage costs, which can limit their practicality. In this work, we investigate matrix-free, linear-time approaches for estimating Inverse-Hessian Vector Products (IHVPs) for the case when the Hessian can be approximated as a sum of rank-one matrices, as in the classic approximation of the Hessian by the empirical Fisher matrix. We propose two new algorithms as part of a framework called M-FAC: the first algorithm is tailored towards network compression and can compute the IHVP for dimension $d$, if the Hessian is given as a sum of $m$ rank-one matrices, using $O(dm^2)$ precomputation, $O(dm)$ cost for computing the IHVP, and query cost $O(m)$ for any single element of the inverse Hessian. The second algorithm targets an optimization setting, where we wish to compute the product between the inverse Hessian, estimated over a sliding window of optimization steps, and a given gradient direction, as required for preconditioned SGD. We give an algorithm with cost $O(dm + m^2)$ for computing the IHVP and $O(dm + m^3)$ for adding or removing any gradient from the sliding window. These two algorithms yield state-of-the-art results for network pruning and optimization with lower computational overhead relative to existing second-order methods. Implementations are available at [9] and [17].

With the advent of modern embedded systems, logging as a process is becoming more and more prevalent for diagnostic and analytic services. Traditionally, storage and managing of the logged data are generally kept as a part of one entity together with the main logic components. In systems that implement network connections, this activity is usually handled over a remote device. However, enabling remote connection is still considered a limiting factor for many embedded devices due to the demanding production cost. A significant challenge is presented to vendors who need to decide how the data will be extracted and handled for an embedded platform during the design concept phase. It is generally desirable that logging memory modules are able to be addressed as separate units. These devices need to be appropriately secured and verifiable on a different system since data compromise can lead to enormous privacy and even financial losses. In this paper, we present two patterns. First, a pattern that allows flexible logging operation design in terms of module and interface responsibility separation. Second, a pattern for the design of secure logging processes during the utilization of constrained embedded devices. The introduced patterns fulfil the following conditions: (i) flexibility – design is independent of the chip vendors making the logging memory modules easily replaceable, (ii) self-sufficiency – every logging controller is maintained as a separate entity in a decentralized topology, (iii) security – through providing authenticity, confidentiality, and integrity by means of using a dedicated security module.