Byzantine fault-tolerant state-machine replication (BFT-SMR) is a technique for hardening systems to tolerate arbitrary faults. Although robust, BFT-SMR protocols are very costly in terms of the number of required replicas (3 f + 1 to tolerate f faults) and of exchanged messages. However, with łhybridž architectures, where łnormalž components trust some łspecialž components to provide properties in a trustworthy manner, the cost of using BFT can be dramatically reduced. Unfortunately, even though such hybridization techniques decrease the message/time/space complexity of BFT protocols, they also increase their structural complexity. Therefore, we introduce Asphalion, the first theorem prover-based framework for verifying implementations of hybrid systems and protocols. It relies on three novel languages: (1) HyLoE: a Hybrid Logic of Events to reason about hybrid fault models; (2) MoC: a Monadic Component language to implement systems as collections of interacting hybrid components; and (3) LoCK: a sound Logic of events-based Calculus of Knowledge to reason about both homogeneous and hybrid systems at a high-level of abstraction (thereby allowing reusing proofs, and capturing the high-level logic of distributed systems). In addition, Asphalion supports compositional reasoning, e.g., through mechanisms to lift properties about trusted-trustworthy components, to the level of the distributed systems they are integrated in. As a case study, we have verified crucial safety properties (e.g., agreement) of several implementations of hybrid protocols.

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An outbreak of acute hepatitis of unknown aetiology in children was reported in Scotland 1 in April 2022 and has now been identified in 35 countries 2 . Several recent studies have suggested an association with human adenovirus with this outbreak, a virus not commonly associated with hepatitis. Here we report a detailed case–control investigation and find an association between adeno-associated virus 2 (AAV2) infection and host genetics in disease susceptibility. Using next-generation

Platelet-rich plasma (PRP) is autologous blood product, that contains platelets concentration two to three times above normal blood level. As such, PRP is a rich source of different bioactive molecules including grow factors, enzymes, cytokines, and chemo-kines. Beside its regenerative properties, a limited number of studies has proven that PRP can induce antimicrobial effect against single growing pathogens and biofilms. Aim of this study was to analyze PRP antimicrobial effect against three most common biofilm forming bacteria, including S. aureus , E. coli and P. aeruginosa . The antimicrobial property of PRP was evaluated after 24 h of incubation with selected bacteria in Brain heart infusion (BHI) media using spectrophotometer with a light source of 600 nm. To check whether PRP can inhibit bacterial biofilm formation, after 24h incubation, tube screening test (TM) was applied. Bacteria treated with PRP and platelet poor plasma (PPP) were compared with untreated control, composed of bacteria growing spontaneusly in BHI media. PRP produced strong growth inhibiton in all tested bacteria when compared to bacteria treated with PPP and control group. Based on the obtained results it can be concluded that PRP can induce antimicrobial effect on S. aureus , P. aeruginosa and E. coli . PRP also reduced biofilm formation for P. aeruginosa and E. coli . However, there was no effect on S. aureus biofilm formation.

The fieldwork carried out in 2015 as part of the Varvaria / Breberium / Bribir Archaeological Project continued the field operations undertaken in 2014 along the following lines2: excavation below the floor level of the church of Sts Joachim and Ann (fig. 1) and to the NE of the trench T2 opened last year; UDC: 726.54(497.581.2) V. Ghica 726.822(497.581.2) A. Milošević Preliminary communication N. Uroda Manuscript received: 10. 02. 2017. D. Dzino* Revised manuscript accepted: 15. 02. 2017. DOI: 10.1484/J.HAM.5.113762

—Social navigation is a desirable capacity of every mobile robot that operates in a human-populated environment. A core challenge is the need to account for a vast number of possible configurations of social spaces, interaction contexts, and individual preferences. We assert that a mobile robot should be able to explain its navigational choices to humans in terms of social aspects of a situation. This way, humans can challenge the robot’s decisions and give corrective feedback. In our approach, explanations are first-class citizens employed both as inputs and as outputs. As inputs, explanations enhance human feedback (“Robot, you should not go this way, because . . . ”). Our preliminary results indicate that allowing humans to formulate explanations as feedback can speed up training. As outputs, explanations make navigational decisions transparent to humans. This way, humans can verify that the learnt model incorporates the intended social norm. We show how explanation-generation methods known from explainable AI (XAI) community can be adopted for this task. We sketch the project in its early stage and point out planned research directions.

Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors or originators and do not necessarily reflect the views of the National Science Foundation. Abstract Attacks on industrial control systems remain rare overall, yet they may carefully target their victims. A particularly challenging threat consists of adversaries aiming to change a plant's *process flow*. A prominent example of such a threat is Stuxnet, which manipulated the speed of centrifuges to operate outside of their permitted range. Existing intrusion detection approaches fail to address this type of threat. In this paper we propose a novel network monitoring approach that takes process semantics into account by (1) extracting the value of process variables from network traffic, (2) characterizing types of variables based on the behavior of time series, and (3) modeling and monitoring the regularity of variable values over time. We implement a prototype system and evaluate it with real‐world network traffic from two operational water treatment plants. Our approach is a first step towards devising intrusion detection systems that can detect semantic attacks targeting to tamper with a plant's physical processes.

What distinguishes the AGI approach from the initial, supposedly equally idealistic and holistic, AI approach? Why do we think that we could make any progress in our recent times? The answer to these questions is not clear

APTw imaging is a potential imaging biomarker to assess treatment effects in brain tumours, especially at high field MRI (7T) due to improved signal-to-noise-ratio enabling the assessment of APTw values in heterogenous tumours. Embedding of APTw imaging in clinical decision making requires insight in the repeatability of APTw imaging. Therefore, we evaluated the repeatability of APTw imaging at 7T by using a phantom and in vivo in the human brain subjects. Repeatable and specific APTw maps were obtained at 7T, which facilitate the potential of detecting metabolic changes in brain tumours due to treatment.

After sentinel lymph nodes are detected using SPIONs and excised, their characterization is important to detect possible metastases. In this research a low-field (0.5T) tabletop MRI scanner was tested for this purpose using 4x accelerated high resolution 3D acquisition. Both simulations and experiments on excised pig lymph nodes showed promising results, with the accelerated scans showing similar image quality with respect to fully sampled datasets. This protocol shows lymph nodes can be imaged at 0.25 mm isotropic resolution within reasonable scan times. Clinical usage should be proven by scanning true metastatic lymph nodes.

ASL-MRI is reported as an option to assess potentially heterogeneous physiological processes important for tumour treatment. Therefore, we explored the heterogeneity in normalised CBF as an imaging biomarker for assessment of treatment effect in pLGG. There is a noticeable effect of chemotherapy observed as a change in texture of healthy appearing brain tissue. A high difference in texture between treated and non-treated patients for non-enhancing tumour part is observed, suggesting that texture, based on co-occurrence matrices, is suitable as an imaging biomarker for assessment of treatment effect in pLGG.

: Enhancing soil fertility and maize productivity is crucial for sustainable agriculture. This study aimed to evaluate the effects of tillage practices, nitrogen management strategies, and acidified hydrochar on soil fertility and maize productivity. The experiment used a randomized complete block design with split-split plot arrangement and four replications. Main plots received shallow tillage and deep tillage. Subplots were treated with nitrogen (120 kg ha − 1 ) from farmyard manure (FYM) and urea, including control, 33% FYM + 67% urea (M U ), and 80% FYM + 20% urea (M F ). Acidified hydrochar treatments H 0 (no hydrochar) and H 1 (with hydrochar, 2 t ha − 1 ) were applied to sub-sub plots. Deep tillage significantly increased plant height, biological yield, grain yield, ear length, grains ear − 1 , thousand-grain weight, and nitrogen content compared to shallow tillage. M U and M F improved growth parameters and yield over the control. Hydrochar effects varied; H 1 enhanced yield components and soil properties such as soil organic matter and nitrogen availability compared to H 0 . Canonical discriminant analysis linked deep tillage and M U /M F nitrogen management with improved yield and soil characteristics. In conclusion, deep tillage combined with integrated nitrogen management enhances maize productivity and soil properties. These findings highlight the importance of selecting appropriate tillage and nitrogen strategies for sustainable maize production along with hydrochar addition. These insights guide policymakers, agronomists, and agricultural extension services in adopting evidence-based strategies for sustainable agriculture, enhancing food production, and mitigating environmental impacts. The implication of this study suggests to undertake long-term application of hydrochar for further clarification and validation.

: As the population grows, more food is needed to keep the food supply chain running smoothly. For many years, intensive farming systems have been used to meet this need. Currently, due to intense climate change and other global natural problems, there is a shift towards sustainable use of natural resources and simplified methods of tillage. Soil tillage intensity influences the distribution of nutrients, and soil’s physical and mechanical properties, as well as gas flows. The impact of reduced tillage on these indices in spring barley cultivation is still insufficient and requires more analysis on a global scale. This study was carried out at Vytautas Magnus University, Agriculture Academy (Lithuania) in 2022–2023. The aim of the investigation was to determine the effect of the tillage systems on the soil temperature, moisture content, CO 2 respiration and concentration in spring barley cultivation. Based on a long-term tillage experiment, five tillage systems were tested: deep and shallow moldboard ploughing, deep cultivation-chiseling, shallow cultivation-chiseling, and no tillage Shallow plowing technology has been found to better conserve soil moisture and maintain higher temperatures in most cases. During almost the entire study period, the spring barley crop with deep cultivation had lower moisture content and lower soil temperature. Shallow cultivation fields in most cases increased CO 2 emissions and CO 2 concentration. When applying direct sowing to the uncultivated soil (10–20 cm), the concentration of CO 2 decreased from 0.01 to 0.148 percent. pcs. The results show that in direct sowing fields, most cases had a positive effect on crop density. Direct sowing fields resulted in significantly lower, from 7.9 to 26.5%, grain yields of spring barley in the years studied.