Automatic modulation classification (AMC) is a promising technology for identifying modulation types, and deep learning (DL)-based AMC is one of its main research directions. Conventional DL-based AMC methods are centralized solutions (i.e., CentAMC), which are trained on abundant data collected from local clients and stored in the server and generally have advanced performance, but their major problem is the risk of data leakage. Besides, if DL-based AMC is only trained with the data from their corresponding clients, it may exhibit weak performance. Thus, a federated learning (FL)-based AMC (FedeAMC) is proposed under the condition of class imbalance and noise varying. Its advantage is low risk of data leakage without severe performance loss, because data and training are in each local client, while only knowledge (i.e., gradient or model weight), rather than data, is shared with the server. In addition, there is generally class imbalance problem in each local client, and balanced cross entropy is introduced as loss function for solving this problem. Simulation results demonstrated that average accuracy gap between FedeAMC and CentAMC is less than 2%.

This study was intended to determine the effect of adding flax seeds to a concentrate for lamb fattening on the fatty acid composition of the omental fat depot in Pramenka lambs reared indoors. A total of 63 lambs (10±3 kg of live body weight, 30±7 days of age, 30 males and 33 females) were used. They were divided into two groups: a control (CON) fed on hay, ewe's milk, and a 300-g daily ration of a commercial concentrate, and an experimental group (FS) fed on hay, ewe's milk and 300 g/day of the concentrate enriched with 5% of flax seeds. After a 60-day fattening period for each group, 10 lambs (5 males and 5 females) were selected and omental fat samples were analysed for fatty acid composition. Highly significant differences (p⟨0.001) were found between CON and FS in α-linolenic acid, the sum of n-3 fatty acids, and the ratio n-6/n-3 fatty acids. The effect of sex on the fatty acid content in the fat depot was only significant for C20:0 fatty acid (p⟨0.05).

Background: After the World Health Organization declared the outbreak of a new coronavirus on 30 January 2020 a public health emergency of international importance, health authorities in Bosnia and Herzegovinaas in other countries around the world, have ordered active surveillance, early detection, isolation and management, cases, contact monitoring and prevention of the spread of infection. Objective: The aim of this study was to describe and analyze of the organization of family medicine during COVID-19 pandemic in Canton Sarajevo with its positive and negative aspects. Methods: The case study design provided an ideal framework for systematic research into the organization of primary health care in Sarajevo Canton during the COVID-19 pandemic as it is an empirical study exploring a contemporary phenomenon within its real-life context when the boundaries between phenomenon and context are not clearly visible. Multiple sources of evidence are used. Data were collected in several different ways: analyzing policies, laws, regulations, decisions related to the COVID pandemic, insight into changes in the health information system, collecting data from reports, and through a group interview (Delphi exploratory) with eleven family medicine specialists. Results: Primary care was organized as two parallel systems with family medicine in the center. The first system was COVID-19 primary care and the second was regular care for non-COVID-19 patients. Family medicine physicians despite a numerus setbacks provide health care for 106346 COVID-19 cases. Discussion: Every principal (first contact access, person-centered care, comprehensiveness, continuity of care, community based, coordination of care, and holistic modeling) of family medicine was interrupted with consequences for patients and family physicians. Conclusion: Additional research is needed to examine all facets of the family medicine and primary health care response to the COVID-19 pandemic in Sarajevo Canton.

Background: Arrhythmias are common problems in hypertensive patients. The presence and complexity of both supraventricular and ventricular arrhythmias may influence morbidity, mortality, as well as the quality of life of patients. Objective: The aim of this study was to assess the diagnostic value of combined 24h BP and ECG Holter monitoring in detection of cardiac arrhythmias in patients with arterial hypertension. Methods: We analyzed the simultaneous records of combined 24h BP and ECG Holter monitoring for 356 adult patients with diagnosed arterial hypertension in the period from January 2017 until January 2021 year. The cardiac arrhythmias were classified in three main groups as following: a) Supraventricular arrhythmias; b) Ventricular arrhythmias; c) Bradyarrhythmia’s. Standard transthoracic echocardiograms were performed in order to evaluate signs of hypertensive or structural heart disease with focus on left ventricle hypertrophy and LV function. Results: Patients had a mean age of 64 ± 11years, 62% male. Average clinic BP was 153.4+18/87.5+14 mmHg. More than 46% of patients displayed a very high-risk profile. In all enrolled patients, cardiac arrhythmia was detected in 302 (84%) patients. The total number of patients with supraventricular arrhythmias was 153 (50,7%). Ventricular arrhythmias were detected in 98 (32,5%) patients. Bradyarrhythmia’s were detected in 51 (16,9%) patients. Elevated resting heart rate in sinus rhythm was detected in 87 (31,6%) of 275 patients with sinus rhythm. Conclusion: Most arrhythmias are related to longstanding arterial hypertension. Effective treatment of arterial hypertension plays important role in preventing structural and functional cardiac abnormalities which will contribute to the reduction of cardiac arrhythmias in hypertensive patients.

BACKGROUND The pre-analytical phase, which includes all preparatory actions to the analytical procedure, is part of the process during which there is the greatest possibility of laboratory errors. This study was conducted to investigate the frequency and types of laboratory errors during work in the clinical laboratory as well as the frequency and types of laboratory errors in the pre-analytical phase of laboratory work. METHODS The retrospective, descriptive study covered the period from 01/01/2016 to 12/31/2016 within which the presence of 5 different indicators of quality of work, i.e., pre-analytical errors, was monitored: improperly drawn blood, coagulated blood sample, hemolyzed blood sample, improperly marked referral for analysis, and insufficient sample for analysis. RESULTS The most common error in the pre-analytical phase of our study was "coagulated sample", followed by: "improperly drawn blood", "improperly marked referral", "insufficient sample for analysis", and "hemolyzed sample". Using the chi-squared test, a statistically significant difference was found in the frequency of occurrence of certain types of indicators in different departments (p < 0.005). CONCLUSIONS Reduction of these errors can be achieved through analyzing and correcting the reasons for them, education, and by joint action of experts and international organizations, continual training of staff as well as to following the adopted guidelines and standards.

Background Most trials comparing endovascular treatment (EVT) alone versus intravenous thrombolysis with alteplase (IVT) + EVT in directly admitted patients with a stroke are non-inferiority trials. However, the margin based on the level of uncertainty regarding non-inferiority of the experimental treatment that clinicians are willing to accept to incorporate EVT alone into clinical practice remains unknown. Objective To characterize what experienced stroke clinicians would consider an acceptable level of uncertainty for hypothetical decisions on whether to administer IVT or not before EVT in patients admitted directly to EVT-capable centers. Methods A web-based, structured survey was distributed to a cross-section of 600 academic neurologists/neurointerventionalists. For this purpose, a response framework for a hypothetical trial comparing IVT+EVT (standard of care) with EVT alone (experimental arm) was designed. In this trial, a similar proportion of patients in each arm achieved functional independence at 90 days. Invited physicians were asked at what level of certainty they would feel comfortable skipping IVT in clinical practice, considering these hypothetical trial results. Results There were 180 respondents (response rate: 30%) and 165 with complete answers. The median chosen acceptable uncertainty suggesting reasonable comparability between both treatments was an absolute difference in the rate of day 90 functional independence of 3% (mode 5%, IQR 1–5%), with higher chosen margins observed in interventionalists (aOR 2.20, 95% CI 1.06 to 4.67). Conclusion Physicians would generally feel comfortable skipping IVT before EVT at different certainty thresholds. Most physicians would treat with EVT alone if randomized trial data suggested that the number of patients achieving functional independence at 90 days was similar between the two groups, and one could be sufficiently sure that no more than 3 out of 100 patients would not achieve functional independence at 90 days due to skipping IVT.

Recently, much attention has been paid to the reuse of bauxite residues from alumina production, also known as red mud, in the cement industry. Red mud bears the potential to improve concrete properties due to its favourable chemical composition and particle size. In this work, the synergy between locally available red mud and common supplementary cementitious materials such as fly ash, slag, calcined clay and limestone in cement mixes is investigated. All materials used were sourced from the immediate vicinity of the cement plant. The study of synergy involved the evaluation of the individual chemical reactivity of each material using the R3 test by isothermal calorimetry as well as their joint contribution to the heat of hydration and the composition of the reaction products of the paste and the compressive strength of the mortar. The results show how, by understanding the synergy between the materials, a higher level of cement substitutions can be achieved without compromising the mechanical properties of the mortar.

Performance of neural networks greatly depends on quality, size and balance of training dataset. In a real environment datasets are rarely balanced and training deep models over such data is one of the main challenges of deep learning. In order to reduce this problem, methods and techniques are borrowed from the traditional machine learning. Conversely, generative adversarial networks (GAN) were created and developed, a relatively new type of generative models that are based on game theory and consist of two neural networks, a generator and a discriminator. The generator’s task is to create a sample from the input noise that is based on training data distribution and the discriminator should detect those samples as fake. This process goes through a finite number of iterations until the generator successfully fools the discriminator. When this occurs, sample becomes a part of new (augmented) dataset. Even though the original GAN creates unlabeled samples, variants that soon appeared removed that limitation. Generating artificial data through these networks appears to be a meaningful solution to the imbalance problem since it turned out that artificial samples created by GAN are difficult to differentiate from the real ones. In this manner, new samples of minority class could be created and dataset imbalance ratio lowered.