Metabolizam visokomliječnih krava, obzirom na njihovu genetsku predispoziciju za visoku proizvodnju mlijeka s jedne i reproduktivnih zahtjeva s druge strane, često je opterećen te izložen promjenama koje za posljedicu mogu imati poremećaj funkcionalnog stanja pojedinih organa, a najčešće jetre i genitalnih organa. Fiziološke vrijednosti biokemijskih parametara krvi krava, koje nude različiti izvori, često znaju znatno varirati. U tom smislu, osobito su interesantni parametri metaboličkog profila u muznih krava, koji imaju višestruko značenje: od pokazatelja hranidbenog statusa i uvjeta držanja životinja do pokazatelja kliničkih bolesti. Cilj je ovog rada bio ustvrditi koncentraciju nekih biokemijskih parametara u krvnoj plazmi krava holštajn-frizijske pasmine tijekom perioda zasušenja. Ispitivanja koncentracije pojedinih sastojaka u krvnoj plazmi radi određivanja metaboličkog profila krava važna su, ne samo za postavljanje objektivne dijagnoze i određivanje težine poremećaja u životinja s izraženim simptomima, već i u prevenciji i rasvjetljavanju mehanizama nastanka novih, metaboličkih i drugih bolesti. Istraživanjem je obuhvaćeno ukupno 46 krava u zasušenju holštajn-frizijske pasmine iz dva farmska uzgoja. Istraženo je 20 krava s farme „A“ i 26 krava s farme „B“. U krvnoj plazmi su spektrofotometrijski određivane vrijednosti parametara koncentracija: glukoze, ukupnih proteina, albumina, kolesterola, triglicerida, bilirubina i ureje. Na temelju rezultata našeg istraživanja, zaključili smo da su krvni parametri koje smo pratili adekvatni za praćenje funkcionalnog stanja jetre i metabolizma u krava, a koji mogu biti od koristi i u procjeni očekivane dužine servis perioda.

Research show that the vibrations of the strings and the radiated sound of the solid body electric guitar depend on the vibrational behavior of its structure in addition to the extended electronic chain. In this regard, most studies focused on the vibro-mechanical properties of the neck of the electric guitar and neglected the coupling of the vibrating strings with the neck and the solid body of the instrument. Therefore, the aim of the study was to understand how the material properties of the solid body could affect the stiffness and vibration damping of the whole instrument when comparing ash (Fraxinus excelsior L.) and walnut (Juglans regia L.) wood. In the electric guitar with identical components, higher modal frequencies were confirmed in the structure of the instrument when the solid body was made of the stiffer ash wood. The use of ash wood for the solid body of the instrument due to coupling effect resulted in a beneficial reduction in the vibration damping of the neck of the guitar. The positive effect of the low damping of the solid body of the electric guitar made of ash wood was also confirmed in the vibration of the open strings. In the specific case of free-free vibration mode, the decay time was longer for higher harmonics of the E2, A2 and D3 strings.

With everyday advances in the field of pharmaceuticals, medicinal plants have high priority regarding the introduction of novel synthetic compounds by the usage of environmentally friendly extraction technologies. Herein, a supercritical CO2 extraction method was implemented in the analysis of four plants (chamomile, St. John’s wort, yarrow, and curry plant) after which the non-targeted analysis of the chemical composition, phenolic content, and antioxidant activity was evaluated. The extraction yield was the highest for the chamomile (5%), while moderate yields were obtained for the other three plants. The chemical composition analyzed by gas chromatography-high-resolution mass spectrometry (GC-HRMS) and liquid chromatography-high-resolution mass spectrometry (LC-HRMS) demonstrated extraction of diverse compounds including terpenes and terpenoids, fatty acids, flavonoids and coumarins, functionalized phytosterols, and polyphenols. Voltammetry of microfilm immobilized on a glassy carbon electrode using square-wave voltammetry (SWV) was applied in the analysis of extracts. It was found that antioxidant activity obtained by SWV correlates well to 1,1-diphenyl-2-picrylhidrazine (DPPH) radical assay (R2 = 0.818) and ferric reducing antioxidant power (FRAP) assay (R2 = 0.640), but not to the total phenolic content (R2 = 0.092). Effective results were obtained in terms of activity showing the potential usage of supercritical CO2 extraction to acquire bioactive compounds of interest.

Abstract The author analyses the discourse about Kosovo in Bosnia and Herzegovina (BiH) during the 1980s. During these years, Serbian media developed several stereotypes to discredit the political leaders of BiH and accuse them of fomenting unrest in Kosovo. The author assesses these stereotypical depictions as well as the response of the Islamic Community and political leadership in BiH to these accusations. He asks what the attitude of Serbia’s political elite towards BiH was, and what role the Serbian political leadership played in the media attacks. He then investigates the evolution of the BiH leadership’s stances towards the events in Kosovo between the beginning and the end of the 1980s. And finally, through a close reading of session minutes and media, he assesses the increasingly deviating views of the BiH political leaders vis-á-vis the situation in Kosovo.

Abstract This paper seeks to empirically explore how an international financial integration influences a country’s GDP growth. The long run relationship is tested by PMG estimator for the sample of ten EU countries from Central, Eastern and Southeastern Europe (CEE-10 countries) between 1995 and 2017. Prior to the conducting of dynamic panel analysis based on PMG estimators, several panel unit root tests were conducted, as well as panel co integration tests. The findings offer mixed impact financial integration on growth. Among the measures of financial integration, growth of the CEE-10 countries is mostly driven in the long run by FDI inflows as well as remittances and financial openness. On the contrary, the study suggests a reversal relationship between growth and financial integration measured by Gross Foreign Assets and Liabilities in percentages of GDP. It might be explained with a fact that CEE-10 countries have not yet reached a certain level of financial development in order to benefit from financial integration. The study concludes that international financial integration does not per se enhance economic growth and country’s growth in the CEE-10 countries can be reached at a higher level of financial integration, further increase their financial openness and financial development.

The mesiodens is the most frequent type of supernumerary tooth which can appear in the maxillary midline area. The etiology of mesiodentes is not fully understood. This report shows a case of incomplete fusion of an unerupted mesiodens with a permanent maxillary central incisor, aligned in the dental arch. Intraoral and radiographic examinations indicated fusion of the crown and cervical part of the root of the supernumerary tooth with the permanent incisor. The clinical situation was further complicated by the presence of another supernumerary tooth located palatally. The treatment approach has included two phase surgical therapy to extract the supernumerary teeth. Early diagnosis and appropriate surgical treatment of mesiodentes are important to decrease the risk of clinical complications. Pre-operative 3D imaging is strongly advisable since it allows accurate data to be obtained, and reduces the extent of surgery and the possibility of procedural complications. In most cases, a multidisciplinary collaboration is necessary for precise diagnosis and predictable treatment outcome.

In this paper, we propose Federated Deep Learning (FDL) for intrusion detection in heterogeneous networks. Local Deep Neural Network (DNN) models are used to learn the hierarchical representations of the private network traffic data in multiple edge nodes. A dedicated central server receives the parameters of the local DNN models from the edge nodes, and it aggregates them to produce an FDL model using the Fed+ fusion algorithm. Simulation results show that the FDL model achieved an accuracy of 99.27 ± 0.79%, a precision of 97.03 ± 4.22%, a recall of 98.06 ± 1.72%, an F1 score of 97.50 ± 2.55%, and a False Positive Rate (FPR) of 2.40 ± 2.47%. The classification performance and the generalisation ability of the FDL model are better than those of the local DNN models. The Fed+ algorithm outperformed two state-of-the-art fusion algorithms, namely federated averaging (FedAvg) and Coordinate Median (CM). Therefore, the DNN-Fed+ model is preferable for intrusion detection in heterogeneous wireless networks.

Accurate downlink channel state information (CSI) is one of the essential requirements for harnessing the potential advantages of frequency-division duplexing (FDD) massive multi-input multi-output (MIMO) systems. The current state-of-art in this vibrant research area include the use of deep learning to compress and feedback downlink CSI at the user equipments (UEs). These approaches focus mainly on achieving CSI feedback with high reconstruction performance and low complexity, but at the expense of inflexible compression rate (CR). High training overheads and limited storage capacity requirements are some of the challenges associated with the design of dynamic CR, which instantaneously adapt to propagation environment. This paper applies transfer learning (TL) to develop a multi-rate CSI compression and recovery neural network (TL-MRNet) with reduced training overheads. Simulation results are presented to validate the superiority of the proposed TL-MRNet over traditional methods in terms of normalized mean square error and cosine similarity.

Malware traffic classification (MTC) is a key technology for solving anomaly detection and intrusion detection problems. And hence it plays an important role in the field of network security. Traditional MTC methods based on port, payload and statistic depend on the manual-designed features, which have low accuracy. Recently, deep learning methods have attracted significant attention due to their high accuracy in terms of classification. However, in practical application scenarios, deep learning methods require a large amount of labeled samples for training, while the available labeled samples for training are very rare. Furthermore, the preparation of a large amount of labeled samples requires a lot of labor costs. To solve these problems, this paper proposes two methods based on semi-supervised learning (SSL) and transfer learning (TL), respectively. Our proposed methods use a large amount of unlabeled data collected in the Internet traffic, which can greatly improve the accuracy classification with few labeled samples. Through experiments, we obtained the best method to improve the accuracy of few labeled samples in different situations. Experiment results show that our proposed methods can satisfy the requirement of MTC in the case of few labeled samples.

Intelligent reflecting surface (IRS)-aided millimeter-wave (mmWave) multiple-input single-output (MISO) is considered one of the promising techniques in next-generation wireless communication. However, existing beamforming methods for IRS-aided mm Wave MISO systems require high computational power, so it cannot be widely used. In this paper, we combine an unsupervised learning-based fast beamforming method with IRS-aided MISO systems, to significantly reduce the computational complexity of this system. Specifically, a new beamforming design method is proposed by adopting the feature fusion means in unsupervised learning. By designing a specific loss function, the beamforming can be obtained to make the spectrum more efficient, and the complexity is lower than that of the existing algorithms. Simulation results show that the proposed beamforming method can effectively reduce the computational complexity while obtaining relatively good performance results.

Background: Patients with cancer are at increased risk of severe outcomes from COVID-19. Understanding the impact of SARS-CoV-2 infection and vaccination induced-immunity is an area of unmet need. Methods: CAPTURE (NCT03226886) is a prospective longitudinal cohort study of COVID-19 vaccine or SARS-CoV-2 infection-induced immunity. SARS-CoV-2 infections were con fi rmed by RT-PCR and ELISA. Neutralising antibody titres (NAbT) against wild- type (WT) SARS-CoV-2 and variants of concern (VOC; Alpha, Beta, Delta) and SARS-CoV-2 speci fi c T-cells (SsT-cells) ed. Results: 118 patients (89% solid malignancy, [SM]) were SARS-CoV-2-positive (median follow-up: 154 days). 85% patients were symptomatic; 2 died of COVID-19. 82% had S1-reactive antibodies, of whom 89% had neutralising antibodies (NAbs); NAbT were lower against all VOCs. While S1-reactive antibody levels declined over time, NAbT remained stable up to 329 days. Most patients had detectable SsT-cells (76% CD4+, 52% CD8+). Haematological malignancy (HM) patients had impaired immune responses that were disease and treatment-speci fi c (anti-CD20), but with evidence suggestive of compensation from T-cells. 585 patients were evaluated following 2 doses of BNT162b2 or AZD1222 vaccines, administered 12 weeks apart. Serocon- version rates after 2 doses were 85% and 54% in patients with SM and HM, respectively. A lower proportion of patients had detectable NAbs against SARS-CoV-2 VOC (Alpha 62%, Beta 54%, Delta 49%) vs WT (84%), with corresponding signi fi cantly lower NAbT. Patients with HM were more likely to have an undetectable NAb and had lower NAbT vs solid malignancies to both WT and VOCs. Seroconversion showed poor concordance with NAbTs against VOCs. Prior SARS-CoV-2 infection boosted NAbT including against VOCs. Anti-CD20 treatment was associated with severely diminished NAbTs. Vaccine-induced T-cell responses were detected in 80% of patients, with no differences between vaccines or cancer types. Conclusions: Patients with HM had blunted humoural responses to infection and vaccination, particularly against VOCs, but preserved cellular responses might contribute to protection. Our results lend support to prioritisation of all cancer pa- tients for further booster vaccination. Background: Patients with cancer are at higher risk of developing COVID-19 disease, adverse outcomes, and increased mortality. Phase III COVID-19 vaccine trials have demonstrated safety/ef fi cacy against COVID-19 and prevented hospitalizations and deaths; however, most excluded ptcpts with cancer.We present phase 3 tozinameran mRNA COVID-19 vaccine trial results from ptcpts with a cancer history at baseline, either ongoing or not, per the Charlson Comorbidity Index and up to 6 months