Gravity inversions have contributed greatly to our knowledge of the interior of planetary bodies and the processes that shaped them. However, previous global gravity inversion methods neglect the inference of mantle density anomalies when using techniques to decrease the non‐uniqueness of the inversion. In this work, we present a novel global gravity inversion algorithm, named THeBOOGIe, suited to inferring global‐scale density anomalies within the crust and mantle of planetary bodies. The algorithm embraces the nonuniqueness inherent in gravity inversions by not prescribing at the outset a density interface or depth range of interest. Instead, the method combines a Bayesian approach with a flexible incorporation of prior geological or geophysical information to infer density anomalies at any depth. A validation test using synthetic lunar‐like gravity data shows that THeBOOGIe can constrain the lateral location of crustal density anomalies but tends to overestimate their thicknesses. Importantly, THeBOOGIe can detect deep mantle density anomalies and quantify the level of confidence in the inferred density models. Our results show that THeBOOGIe can provide complementary information to one‐dimensional seismic models of the interior of the terrestrial planets and the Moon by constraining density anomalies that are not spherically symmetric. Additionally, THeBOOGIe is specially suited to constraining the interior of partially differentiated bodies where these large‐scale density anomalies are more likely to exist. Finally, thanks to the flexible use of priors, THeBOOGIe is an essential tool to understand the interior of planetary bodies lacking additional constraints.

Modern business systems have the expectations and requirements of users and stakeholders for safer and better services that are constantly growing. The increasing use of information technology in business increases the threats and vulnerabilities to which information resources are exposed, which causes an increase in information risks. Many business institutions must constantly monitor their activities to establish an organized and sustainable information security management system and services. The requirements of the international standard ISO/IEC 27001 and the generally accepted COBIT management framework are important for the application of such a system. The paper presents a model of a sustainable information security management system (ISMS) at universities.

Workplace stress or professional stress is a specific type of stress that is highly prevalent among police officers. Police officers are exposed to high levels of stress and its negative impact ontheir physical and mental health, as well as their social lives. The aim of this research is to determine the attitudes regarding the connection between physical fitness and stress prevention among police officers. The sample consists of 516 employees from police departments in the Central Bosnia Canton. The sample is structured with 312 male participants and 204 female participants. Both descriptive and analytical methods were applied in this research, as the descriptive method was used to describe the distribution of the studied phenomenon, while the analytical part followed the logic of the research. Analyzing all the results, it can be concluded that there is a high level of satisfaction with the management of work processes among police officers and with stress reduction in the workplace. The conclusion arises about the necessity of increasing the number of hours of police training, primarily for basic and investigative police work, in stress prevention among police officers. The results of comparative analysis indicate that there is no statistically significant difference among participants based on gender. The results show that the age of the participants significantly influences their attitudes towards overall satisfaction with management quality. Theresults suggest that participants who have been employed the longest and make the most use of the existing infrastructure express more positive attitudes.Key words:police, stress, physical fitness, burnout, prevention.

The aim of this study was to investigate the therapeutic potential of resveratrol in combination with cisplatin on the inhibition of tumour angiogenesis, growth, and macrophage polarization in mice bearing the solid form of an Ehrlich ascites tumour (EAT) that were exposed to whole-body hyperthermia treatment. In addition, we investigated whether a multimodal approach with hyperthermia and resveratrol could abolish cisplatin resistance in tumour cells through the modulation of histone deacetylase (HDAC) activity and levels of heat shock proteins (HSP70/HSP90) and contribute to the direct toxicity of cisplatin on tumour cells. The tumour was induced by injecting 1 × 106 EAT cells subcutaneously (sc) into the thighs of Balb/c mice. The mice were treated with resveratrol per os for five consecutive days beginning on day 2 after tumour injection and/or by injecting cisplatin intraperitoneally (ip) at a dose of 2.5 mg/kg on days 10 and 12 and at a dose of 5 mg/kg on day 15. Immediately thereafter, the mice were exposed to systemic hyperthermia for 15 min at a temperature of 41 °C. The obtained results showed that the administration of resveratrol did not significantly contribute to the antitumour effect of cisplatin and hyperthermia, but it partially contributed to the immunomodulatory effect and to the reduction of cisplatin toxicity and to a slight increase in animal survival. This treatment schedule did not affect microvessel density, but it inhibited tumour growth and modulated macrophage polarization to the M1 phenotype. Furthermore, it abolished the resistance of tumour cells to cisplatin by modulating HDAC activity and the concentration of HSP70 and HSP90 chaperones, contributing to the increased lifespan of mice. However, the precise mechanism of the interaction between resveratrol, cisplatin, and hyperthermia needs to be investigated further.

Although miRNA-27a has been identified as a promising candidate for miRNA mimic therapy of obesity, its application is limited due to enzymatic degradation and low membrane permeation. To overcome these problems, we developed cationic nanostructured lipid carriers (cNLCs) using high-pressure homogenization and used them as non-viral carriers for the anti-adipogenic miRNA-27a. Cargo-free octadecylamine-containing NLCs and miRNA/cNLC complexes were characterized regarding particle size, size distributions, zeta potential, pH values, particle topography and morphology, and entrapment efficacy. Furthermore, the cytotoxicity and cellular uptake of the miRNA/cNLC complex in the 3T3-L1 cell line were investigated. The investigation of the biological effect of miRNA-27a on adipocyte development and an estimation of the accumulated Oil-Red-O (ORO) dye in lipid droplets in mature adipocytes were assessed with light microscopy and absorbance measurements. The obtained data show that cNLCs represent a suitable DDS for miRNAs, as miRNA/cNLC particles are rapidly formed through non-covalent complexation due to electrostatic interactions between both components. The miRNA-27a/cNLC complex induced an anti-adipogenic effect on miRNA-27a by reducing lipid droplet accumulation in mature adipocytes, indicating that this approach might be used as a new therapeutic strategy for miRNA mimic replacement therapies in the prevention or treatment of obesity and obesity-related disorders.

Premature babies and those born with a medical condition are cared for within the neonatal intensive care unit (NICU) in hospitals. Monitoring physiological signals and subsequent analysis and interpretation can reveal acute and chronic conditions for these neonates. Several advanced algorithms using physiological signals have been built into existing monitoring systems to allow clinicians to analyse signals in real time and anticipate patient deterioration. However, limited enhancements have been made to interactively visualise and adapt them to neonatal monitoring systems. To bridge this gap, we describe the development of a user-friendly and interactive dashboard for neonatal vital signs analysis written in the Python programming language where the analysis can be performed without prior computing knowledge. To ensure practicality, the dashboard was designed in consultation with a neonatologist to visualise electrocardiogram, heart rate, respiratory rate and oxygen saturation data in a time-series format. The resulting dashboard included interactive visualisations, advanced electrocardiogram analysis and statistical analysis which can be used to extract important information on patients’ conditions.Clinical Relevance— This will support the care of preterm infants by allowing clinicians to visualise and interpret physiological data in greater granularity, aiding in patient monitoring and detection of adverse conditions. The detection of adverse conditions could allow timely and potentially life-saving interventions for conditions such as sepsis and brain injury.

Unsupervised learning (UL) is widely used in the wireless resource allocation problems due to its lower computational complexity and better performance compared with traditional optimization algorithms. Since wireless resource allocation problems usually have several constraints, primal-dual learning based UL framework are widely adopted. However, the primal-dual learning approach has the problem of oscillation around the constraint threshold while training and there may be serious constraint violations when deployment. In addition, although the output of the neural network can also be restricted to the feasible region by the penalty function method, the optimality of such training methods cannot be guaranteed. In this article, we combine the primal dual learning method with the penalty function method and propose a regularized unsupervised learning (RUL) framework to enhance the robustness of the primal-dual learning based UL framework. In the proposed RUL framework, we use regularization techniques to improve the robustness of primal-dual learning by reducing the risk of constraint violations while training. A quadratic penalty term is introduced into the Lagrangian function of the wireless optimization problem where the constraints can be equivalent to equality constraints to form its augmented Lagrangian function. In the simulation, we give a simple point to point power optimization problem as an example to show that the proposed RUL can improve the robustness of constraint convergence, and can also accelerate training speed.