Two copper(II) complexes of 4-chloro- and 4-dimethylaminobenzaldehyde nicotinic acid hydrazones were prepared and characterized by elemental analysis, mass spectrometry, infrared and electron spectroscopy and conductometry. These rare examples of bis(hydrazonato)copper(II) complexes are neutral complex species with copper(II) center coordinated with two monoanionic bidentate O,N-donor hydrazone ligands coordinated in enol-imine form. The interaction of hydrazone ligands and corresponding copper(II) complexes with CT DNA and BSA was investigated. Copper(II) complexes are slightly effective in binding the DNA than pristine hydrazones. The results indicate groove binding or moderate intercalation which are not significantly affected by the nature of substituent at hydrazone ligands. On contrary, affinities of two copper(II) complexes toward BSA significantly differs and depends on the nature of the substituent, however in absence of thermodynamic data difference in nature of binding forces cannot be excluded. The complex bearing electron-withdrawing 4-chloro substituent has larger affinity toward BSA compared to 4-dimethyamino analogue. These findings were theoretically supported by molecular docking study.

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Glioblastomas presenting topographically at the cerebellopontine angle (CPA) are exceedingly rare. Given the specific anatomical considerations and their rarity, overall survival (OS) and management are not discussed in detail. The authors performed an integrative survival analysis of CPA glioblastomas. A literature search of PubMed, Scopus, and Web of Science databases was performed per PRISMA guidelines. Patient data including demographics, clinical features, neuroimaging, management, follow-up, and OS were extracted. The mean age was 39 ± 26.2 years. The mean OS was 8.9 months. Kaplan–Meier log-rank test and univariate Cox proportional-hazards model identified hydrocephalus (log-rank, p = 0.034; HR 0.34; 95% CI 0.12–0.94; p = 0.038), chemotherapy (log-rank, p < 0.005; HR 5.66; 95% CI 1.53–20.88; p = 0.009), and radiotherapy (log-rank, p < 0.0001; HR 12.01; 95% CI 3.44–41.89; p < 0.001) as factors influencing OS. Hydrocephalus (HR 3.57; 95% CI 1.07–11.1; p = 0.038) and no adjuvant radiotherapy (HR 0.12; 95% CI 0.02–0.59; p < 0.01) remained prognostic on multivariable analysis with fourfold and twofold higher risk for the time-related onset of death, respectively. This should be considered when assessing the risk-to-benefit ratio for patients undergoing surgery for CPA glioblastoma.

Triply periodic minimal surface (TPMS) metamaterials characterized by mathematically-controlled topologies exhibit better mechanical properties compared to uniform structures. The unit cell topology of such metamaterials can be further optimized to improve a desired mechanical property for a specific application. However, such inverse design involves multiple costly 3D finite element analyses in topology optimization and hence has not been attempted. Data-driven models have recently gained popularity as surrogate models in the geometrical design of metamaterials. Gyroid-like unit cells are designed using a novel voxel algorithm, a homogenization-based topology optimization, and a Heaviside filter to attain optimized densities of 0-1 configuration. Few optimization data are used as input-output for supervised learning of the topology optimization process from a 3D CNN model. These models could then be used to instantaneously predict the optimized unit cell geometry for any topology parameters, thus alleviating the need to run any topology optimization for future design. The high accuracy of the model was demonstrated by a low mean square error metric and a high dice coefficient metric. This accelerated design of 3D metamaterials opens the possibility of designing any computationally costly problems involving complex geometry of metamaterials with multi-objective properties or multi-scale applications.

This article examines the recent trends in whistleblowing regulation, analysing the issue of financial rewards as one of the key distinctions between the legislative solutions on the matter in the United States as compared to European jurisdictions. Using the lens of corruption theories, the article concludes that the usage of financial rewards increases the overall regulatory capacity of the state to reduce corruption and fraud and reduce the emerging, largely anonymous digital whistleblowing. The financial rewards are also, due to the peculiar nature of both corruption and whistleblowing, an adequate tool to help to quantify the effects of whistleblowing. The article argues that the introduction of financial rewards should not be viewed as dependent on the differences in the legal traditions or culture but on the quality of the institutions and their ability to assess the reports of the whistleblowers. The article offers considerations concerning the conditions for the introduction of financial rewards.

Introduction: Antimicrobial resistance and the rapid spread of multiresistant bacteria represent one of the main public health problem in limited resources countries. This issue is significantly worsening since the COVID-19 pandemic due to the unreasonably increased antibiotics prescription to patients with confirmed SARS-CoV-2 infection. The aim of this study was to examine whether COVID-19 pandemic (2020, 2021) was associated with increased antibiotic consumption in inpatient and outpatient settings in the middle size urban region (Republic of Srpska/Bosnia and Herzegovina) in comparison to period before the pandemic (2019). Additionally, we aimed to determine antimicrobial resistance and the presence of multiresistant bacteria in the regional hospital (“Saint Apostol Luka” Hospital Doboj) in 2021. Methodology: The consumption of antibiotics in inpatient was calculated as Defined Daily Dose per one hundred of patient-days. The consumption of antibiotics in outpatient was calculated as Defined Daily Dose per thousand inhabitants per day. Resistance of bacteria to antibiotics is expressed as a rates and density for each observed antibiotic. The rate of resistance was calculated as a percentage in relation to the total number of isolates of individual bacteria. The density of resistance of isolated bacteria against a specific antibiotic was expressed as the number of resistant pathogens/1000 patient days. Results: Antibiotic consumption in hospital setting registered during 2019, 2020 and 2021 was as follows: carbapenems (meropenem: 0.28; 1.91; 2.33 DDD/100 patient-days, respectively), glycopeptides (vancomycin: 0.14; 1.09, 1.54 DDD/100 patient-days, respectively), cephalosporins (ceftriaxone: 6.69; 14.7; 14.0 DDD/100 patient-days, respectively) and polymyxins (colistin: 0.04; 0.25; 0.35 DDD/100 bed-days, respectively). Consumption of azithromycin increased drastically in 2020, and dropped significantly in 2021 (0.48; 5.61; 0.93 DDD/100 patient-days). In outpatient setting, an increase in the consumption of oral forms of azithromycin, levofloxacin and cefixime, as well as parenteral forms of amoxicillin-clavulanic acid, ciprofloxacin and ceftriaxone, was recorded. In 2021, antimicrobial resistance to reserve antibiotics in hospital setting was as follows: Acinetobacter baumanii to meropenem 66.0%, Klebsiella spp to cefotaxime 67.14%, Pseudomonas to meropenem 25.7%. Conclusion: Recent COVID-19 pandemic was associated with increased antibiotic consumption in inpatient and outpatient settings, with characteristic change of pattern of azithromycin consumption. Also, high levels of antimicrobial resistance to reserve antibiotics were registered in hospital setting with low prevalence of identified pathogen-directed antimicrobial prescription. Strategies toward combat antimicrobial resistance in the Doboj region are urgently needed.

The Internet of Things (IoT) is considered a new paradigm that aims to connect a large number of devices. IoT is increasingly present in domains such as healthcare, transport, agriculture, and other industrial branches. An increasing number of IoT devices, as well as the amount of data, leads to increased energy consumption and a negative impact on the environment. Therefore, researchers are focusing on the concept of Green IoT that aims to increase energy efficiency and create a safe environment. The focus of this paper is on energy-efficient techniques within green data centers. Also, the performance evaluation of data centers was performed in the GreenCloud simulator for the optimal load of data centers in terms of energy efficiency and sustainability.

The increase in the number of wind farms and their share in the total electrical energy generation leads to the need for a different approach to this source in cases where the stability of the power system is potentially impaired. With the development of different types of wind power plants, equipped with power electronics devices, there is the possibility of quick power management and injection, in conditions when it is needed, where a huge amount of accumulated kinetic energy can also be used. This paper presents the influence of a wind power plant equipped with a full-scale converter on the transient stability in cases of close and distant short circuits, during the outage of a heavily loaded line. Special attention was paid to the Rate of Change of Frequency (RoCoF) in the power system in cases with and without a wind farm where fast power injections were possible.

The contribution of renewable energy sources to the power system stability will have to be greater in the future. The problem will arise if the share of wind power plants in total production increases and large failures occur. Then, wind farms, which are often called inertia-less sources in the literature, will have to help maintain the frequency in a normal amount by changing the management method and based on fast PMU measurements. This can be done by using the synthetic inertia size, which is defined for sources that are derived from the system via energy converters and which do not participate in defining the total inertia of the system. This paper provides a better insight into the understanding of the concept of synthetic inertia, as well as insight into the current development of management and the application of synthetic inertia in maintaining the stability of the power system.

New forms of communication are created as a result of the advancement of information and communication technologies, particularly the Internet and the WWW. These technologies introduce technological solutions as a response to ongoing difficulties. Relying on the predominant written form, besides its semantics, content on WWW must convey additional information like its structure, formatting, and relationships between its parts. Markup languages were born. Although markup languages addressed the issue at hand, they also raised several new issues, one of which is how to exchange material between disparate markup languages. In this paper, creating a meta-model of the two most commonly used markup languages, Markdown and HTML, is shown. The meta-model is created using the Eclipse Modeling Framework (EMF) ECore model, which relies on grammar obtained from markup languages. This meta-model simplifies comprehension of the relationship between markup language content and its model, which represents the first step towards the automatic transformation between models, i.e., the interchange of their content.

When students enroll at universities, various datasets can be available to managers and teachers. Clustering techniques can be applied in order to divide the instances within those datasets into natural groups. In this paper, one clustering-based approach combined with attribute selection methods for identifying specific input dataset variables meaningful for the disjunction of distinct students' profiles has been proposed. Also, an analysis of the descriptive students' model obtained by the proposed methodology is performed.