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
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.
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.
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.
: 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.
Due to the rapid advancement of online social networks in recent years, the prevalence of fake news has increased significantly. Fake news is deliberately created to deceive users by imitating real news, making it challenging to identify early on. So, we need to explore the accompanying information to improve its disclosure such as the publisher. This study focuses on analyzing and investigating various traditional machine learning models to determine the most effective one. The goal is to develop a supervised machine learning algorithm that can classify news articles as either true or fake, utilizing tools like Python‘s scikit-learn and NLP for text analysis. The proposed approach involves feature extraction and vectorization. To accomplish this, the scikit-learn library in Python is utilized, which offers helpful tools like CountVectorizer and TfidfVectorizer. The experiment involved implementing well-known algorithms: Logistic regression, Neural networks and SVM, and comparing their performance to determine the most suitable one. Each of the three algorithms performed well, but SVM demonstrated superior outcomes across nearly all categories.
The golden ratio (golden section, golden mean, divine proportion) is an irrational number whose value is approximately Φ = 1.618. The golden ratio has imposed itself throughout history as a kind of principle of unison and harmony that is so subtly and fascinatingly repeated in nature, science, art, and even in the structure and function of the human body. What is typical for the golden ratio is that it places the larger segment in relation to the smaller segment, uniting them into a single whole, which again place it in the same relationship with its larger part. If we consider the cardiac cycle as one such whole, its “larger segment” would refer to the diastolic phase, while the “smaller segment” would refer to the systolic phase of one cardiac cycle. In this article, the mathematical processing of 100 ECG records included the measurement of intervals representing the systolic and diastolic phases of the cardiac cycle, where the ratio of diastolic and systolic phases, and the ratio of one cardiac cycle and diastolic phase was obtained. The study has shown that people with normal ECG records have a ratio of the diastolic and systolic phases of the cardiac cycle, and the cardiac cycle and the diastolic phase, which are very close to the golden ratio. On the other hand, persons whose ECG records indicate certain pathological conditions in the heart muscle have ratios of diastolic and systolic phase, and of the total cardiac cycle and diastolic phase, which deviate to varying degrees from the value of the golden ratio. It has been shown that for a certain pathological condition there is a characteristic deviation of the diastole/systole and cardiac cycle/diastole ratio from the number Φ, which opens the possibility of applying this method as a potential diagnostic or screening method in rapid analysis of ECG records.
Fuzzy TOPSIS is one of the sensitive methods for multi-criteria decision making (MCDM). This paper presents the possibility of using fuzzy TOPSIS method and fuzzy evaluation framework for the quality of student mobility in the Erasmus programme. The framework estimates the mobility quality by analysing the answers from the final report study of the implemented mobility. The quality analysis is carried out at the level of individual responses, the entire report and the faculties participating in the programme. The numerical example demonstrates the use of frameworks and determination of quality.
• Wood heat treatment is an environmentally friendly method, and the heat-treated wood properties are closely related to thermal modification intensity. This study focuses on the 0-3 mm surface layer (SL) of poplar wood heat treated at 160~220 °C. The modification intensity, including surface color, hardness, chemical component and morphological changes of the SL, was evaluated. The findings of this research showed that the color difference of the poplar wood before and after heat treatment (ΔE *1 ) increased; the color difference between up-surface and down-surface of the SL (ΔE *2 ) also increased with the treatment temperature. Consequently, the surface hardness (H R ) decreased with the increase of treatment intensity. When the treatment temperature was higher than 160 °C, the up-surface and down-surface of the SL were statistically different in color. Chemical component analysis revealed that the heat treatment degrades wood components, especially the hemicellulose, and correlation analysis showed a significant correlation between the change rate of hemicellulose and the ΔE * 1 or H R value; the prediction functions have been established at a high confidence level of 0.99. Overall, the thermal modification intensity of the heat-treated surface layer (SL) of poplar wood varies, and the H R and ΔE *1 value could be used to characterize and predict the modification intensity and degree of thermal degradation of the surface layer of heat-treated poplar wood.
Milk is a food of high biological value and as part of a properly balanced diet plays a major role in human health. The composition of milk varies depending on the origin and the animals from which it originates. Disruption of milk stability usually is the result of changes in the concentration of Ca 2+ ions. Increasing stability in this case can be achieved by the addition of phosphate, polyphosphate or citrate of an alkali metal or by removal of calcium by ion exchangers. The present salts and ions directly has effects on the physical properties of the milk, such as osmotic pressure, the freezing point and boiling point, conductivity, titratable acidity, pH, and buffering capacity of milk. Ca 2+ ions influence on the dispersity of the casein and on the amount of bound water directly influence the density and viscosity of milk. Milk acidity, density, viscosity, surface tension, refractive index, electrical conductivity are important physical - chemical indicators of the quality of the milk. The aim of this study is to examine the effect of heat treatment on the physical-chemical properties of the milk and the calcium content on which depend the quality of the final product, and to establish the correlation between certain parameters. For this research, different milk samples from different geographical regions of the Tuzla Canton were analyzed. Due to the extreme importance of the milk and dairy products in the diet of all age groups of people, monitoring of the physical-chemical properties of milk and the calcium content is of particular importance.
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