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: 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.

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).

Radio frequency fingerprint (RFF) identification is a popular topic in the field of physical layer security. However, machine learning based RFF identification methods require complicated feature extraction manually while deep learning based methods are hard to achieve robust identification performance. To solve these problems, we propose a novel RFF identification method based on heat constellation trace figure (HCTF) and slice integration cooperation (SIC). HCTF is utilized to avoid the manual feature extraction and SIC is adopted to extract more features automatically in RF signals. Experimental results show that our proposed HCTF-SIC identification method can achieve higher accuracy than the existing RFF methods. The identification accuracy achieves 91.07% when SNR <inline-formula> <tex-math notation="LaTeX">$\pmb {=}$ </tex-math></inline-formula> 0 dB and it is even higher than 99.64% when the SNR <inline-formula> <tex-math notation="LaTeX">$\pmb {\ge }$ </tex-math></inline-formula> 5 dB.

Due to the implementation and performance limitations of centralized learning automatic modulation classification (CentAMC) method, this paper proposes a decentralized learning AMC (DecentAMC) method using model consolidation and lightweight design. Specifically, the model consolidation is realized by a central device (CD) for edge device (ED) model averaging (MA) and multiple EDs for ED model training. The lightweight is designed by separable convolutional neural network (S-CNN), in which the separable convolutional layer is utilized to replace the standard convolution layer and most of fully connected layers are cut off. Simulation results show that the proposed method substantially reduces the storage and computational capacity requirements of the EDs and communication overhead. The training efficiency also shows remarkable improvement. Compared with convolutional neural network (CNN), the space complexity (i.e., model parameters and output feature map) is decreased by about 94% and the time complexity (i.e., floating point operations) of S-CNN is decreased by about 96% while degrading the average correct classification probability by less than 1%. Compared with S-CNN-based CentAMC, without considering model weights uploading and downloading, the training efficiency of our proposed method is about <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> times of it, where <inline-formula> <tex-math notation="LaTeX">${N}$ </tex-math></inline-formula> is the number of EDs. Considering the model weights uploading and downloading, the training efficiency of our proposed method can still be maintained at a high level (e.g., when the number of EDs is 12, the training efficency of the proposed AMC method is about 4 times that of S-CNN-based CentAMC in dataset <inline-formula> <tex-math notation="LaTeX">$D_{1} = \{2{\mathrm {FSK, 4FSK, 8FSK, BPSK, QPSK, 8PSK, 16QAM}}\}$ </tex-math></inline-formula> and about 5 times that of S-CNN-based CentAMC in dataset <inline-formula> <tex-math notation="LaTeX">$D_{2} = \{2 {\mathrm {FSK, 4FSK, 8FSK, BPSK, QPSK, 8PSK, PAM2, PAM4, PAM8, 16QAM}}\}$ </tex-math></inline-formula>), while the communication overhead is reduced more than 35%.

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%.

Background: Sonography plays an important role in characterizing breast masses and in guiding needle core biopsies and wire localizations of suspicious sonographis abnormalities. Objective: The aim of this study was to show the possibilities of high frequency ultrasound devices in the presentation of microcalcifications of the breast, and the use of these possibilities in performing needle biopsy under ultrasound control. Methods: This was a retrospective study conducted from May 2017 to December 2020 on 32 women, 29-86 years of age using mammograms and ultrasound to show suspected microcalcifications (radiological findings of BI RADS 4B and 4C), and needle biopsy led by ultrasound that confirmed the diagnosis of breast cancer. Patients with suspected microcalcifications on mammography that had previously had the diagnosis of breast cancer confirmed in the same or contralateral breast were excluded from the study. Histology results from each core biopsy and surgical excision were reviewed. The positive predictive values of sonography and mammography for this population were calculated, and the sensitivity, specificity, and negative predictive value of sonography were determined. For analysis of the agreement of ultrasound findings with mammography the McNemar x2-test for dependent samples was used. Results: The sensitivity of mammography in the detection of microcalcifications in this study was 100%. The sensitivity of the ultrasound apparatus with a high frequency probe in the detection of microcalcifications after mammography examination in this study was 87.55%, while the specificity was 42.85%. Conclusion: Ultrasonic devices with high-frequency probes enable the display of accumulations of microcalcifications previously verified by mammography, and thus enable the performance of needle biopsy of suspected microcalcifications under ultrasonic control. An alternative is the much more complicated and significantly more expensive stereotactic biopsy under the control of mammography.

Background: The most commonly used diagnostic tests for evaluation of the dental fear and anxiety (DFA) presence in children were psychometric scales, where interpretation in determining and using of their cut-off scores sometimes was not completely exact. Also, several studies have been conducted where the results were conflicting in terms of who better assessed the DFA presence - the children, their parents, or dentists. Objective: To determine the normative values in the child and parental versions of the Modified version of the CFSS-DS scale (CFSS-DS-mod scale) and to compare the ways in which children, their parents, and the dentist assessed the DFA presence in the dental office. Methods: Survey sample consisted of 200 children aged from 9 to 12 years, whose DFA presence was determined by the CFSS-DS-mod scale. Child parents answered to their version of this scale, and the dentist observed the child behavior in the dental office during the treatment using Venham Anxiety and Behaviour Rating Scales. Results: Parental version of the CFSS-DS-mod scale found to be reliable (Cronbach alpha = 0.955) and valid (67.87% of variance explained) instrument for assessment of the DFA presence in children. Two cut-off scores were determined in a child (37 and 43), as well as in a parental version of CFSS-DS-mod scale (36 and 44), respectively. Dentists assessed the DFA presence in child patients most accurately. Conclusion: The normative values of psychometric instruments should be considered prior to their use. The borderline area of DFA presence should also be taken into account in the future studies. Children could underestimate DFA existence by themselves while interviewing.

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.