A machine learning (ML)-based methodology for predicting frosts is applied to the southern and southeastern regions of Brazil, as well as to other countries including Uruguay, Paraguay, northern Argentina, and southeastern Bolivia. The machine learning model (using TensorFlow (TF)) was compared to the frost index IG (from the Portuguese: Índice de Geada) developed by the National Institute for Space Research (INPE, Brazil). The IG index is estimated using meteorological variables from a regional weather numerical model (RWNM). After calculating the two indices using the ML model and the RWNM, a voting committee (VC) was trained to select between the computed outputs. The AdaBoostClassifier algorithm was employed to implement the voting committee. The study area was subdivided into three distinct subregions: R1 (outside Brazil), R2 (the southern of Brazil), and R3 (the southeastern of Brazil). Two forecasting time scales were evaluated: 24 hours and 72 hours. The 24-hour forecasts from both approaches (TF and RWNM) exhibited similar performance in terms of the number of accurate predictions. However, in the region covering Uruguay and northern Argentina, the TensorFlow model demonstrated superior frost prediction accuracy. Additionally, the TensorFlow model outperformed the RWNM for the 72-hour forecast horizon.

Climate change poses new challenges for agricultural production as an increase in temperature also brings an increase in frequency and intensity of droughts. We study the occurrences of droughts in recent years as well as their effect on agricultural yields in combination with other factors such as winter frost. Furthermore we run experiments that aim to predict future drought events in order to provide insights whether current agricultural products will remain viable long-term and to indicate short-term drought risks. Our study area consists of the South-Moravian region in the Czech Republic and Saxony in Germany with the timeframe ranging from 1990 − 2022. For the effect on agricultural yields we use statistical methods such as regression and correlation. We train a Long-Short Term Memory (LSTM) neural net on data for the Standardised Precipitation-Evapotranspiration Index (SPEI) in order to predict future events. Our results indicate that the increased severity of droughts in recent years didn’t yet cause yield losses in our researched area. Our predictions with the LSTM look promising, but will need more data for future use-cases in order to increase accuracy and robustness.

In the seasonally frozen regions, during the grouting of prestressed bridge ducts in low-temperature environments, incompletely cured grout materials undergo volumetric changes due to the freeze-thaw cycling, resulting in structural cracks along the prestressing ducts of the bridge, thereby diminishing the bridge's operational lifespan. To investigate the frost heaving characteristics of grout materials under freeze-thaw cycles and propose potential enhancements, this study was devised to conduct frost heaving stress tests on grout materials. Through this research, we gained insights into how various additives affect the frost heaving stress characteristics of grout materials under freeze-thaw cycles. Incorporating analyses of free water content, setting time, compressive strength, as well as macroscopic examinations such as XRD and SEM, this study delves into the mechanisms for enhancing frost heaving characteristics of grout materials. Furthermore, it proposes a research approach that utilizes multiple admixtures to improve the frost heaving properties of grout materials. Through frost heaving stress tests and other macroscopic experiments, the study investigates the influence of these combined admixtures on frost heaving stress in grout materials and elucidates the underlying improvement mechanisms. The results indicate that reducing the water-cement ratio, incorporating calcium formate, sulfoaluminate cement, air-entraining agents, and carbamide all have a positive impact on mitigating frost heaving stress in grout materials. However, the improvement mechanisms differ, and employing a single measure alone is insufficient to effectively reduce frost heaving stress while meeting performance criteria such as compressive strength, setting time, and flowability. Free water content emerges as a crucial indicator determining the magnitude of frost heaving stress in grout materials, with 11.5% of free water content representing the critical threshold for frost heaving in grout materials. Utilizing composite admixtures can simultaneously decrease free water content, lower the freezing point of free water, and alleviate frost heaving deformation, resulting in more efficient reduction of frost heaving stress. When the admixture content reaches 9.9%, frost heaving stress is eliminated, and the comprehensive performance parameters including compressive strength, setting time, and flowability meet the specified requirements.

Mulberry leaves are a classic herb commonly used in traditional Chinese medicine, and experience since ancient times has shown that leaves collected after frost have better medicinal properties. However, the characteristics of the changes of critical metabolic components in mulberry leaves, especially Morus nigra L., are still unknown. To further study the influence of harvesting time on the dynamic changes of metabolites, especially DNJ compounds and flavonoids, in mulberry leaves after frost. We used metabolomics technology to select 100+ metabolites as indexes to reflect the dynamic changes of metabolites in mulberry leaves comprehensively. The results showed significant differences in the effects of defrosting on the accumulation of metabolites in the leaves of Morus nigra L. and Morus alba L. The content of DNJ in the leaves of Morus nigra L. showed a decreasing trend after the frost, while flavonoids reached the peak of the second frost. For Morus alba L, DNJ showed an increasing trend after frost, especially reaching its peak one day after the second frost. Flavonoids mainly peak in the week before the frost. In addition, by analyzing the influence of picking time on metabolite accumulation in two mulberry leaves, it was concluded that higher DNJ alkaloids and flavonoids would be obtained in mulberry leaves collected in the morning. This study also provides scientific guidance for the optimum harvesting time of mulberry leaves.

Rising temperatures due to the climate change can significantly impact the frost/thaw condition of airport pavements in cold regions. This case study investigates the implications of the the warming temperatures on frost/thaw penetration and frost-heave of pavements for critical airports across Canada. To this end, different methods were used in the quantification process through climate change simulations considering the emission scenario RCP8.5 in a 20- and 40-year time horizon. The results show that climate change would have different design implications for airport pavements depending on their location. The predictions suggest a shallower frost penetration depth and possibly less frost-heave for the airports not underlain by permafrost, while airports over permafrost areas might experience an increase in thickness of the active layer ranging from 41 to 57 percent by 2061. Among the different methods used in this study, it was observed that some methods performed the best in predicting frost depth of fine soils, while others worked better with the frost depth prediction of coarse soils. The results indicate the need for more mechanistic models to provide a more realistic prediction of frost/thaw penetration as compared to the existing empirical models.

Improvement of hydrophysical properties and corrosion resistance of self-compacting concrete to the effects of alternate freezing-thawing and aggressive soils of southern and central Kazakhstan is of interest to a wide range of researchers from the side of practical application of the obtained results in construction practice. It is proposed to form a spatially reinforced fine crystalline structure of cement matrix with maximum dense packing by using a complex modifier (Hyperplasticiser + Polymer + Microsilica + Fibro fibers) in the composition of self-compacting concretes (SCC). The introduction of the calculated amount of the above additives increases the operational reliability of the current SCC compositions, increasing the water resistance to W16, frost resistance to F=500, increasing the compressive strength by 20%, reducing the mass loss of samples during corrosion leaching to 50%. It has been experimentally established that the proposed addition of complex modifier (Hyperplasticiser + Polymer + Microsilica + Fiber fibers) to the SCC composition allows obtaining self-compacting concrete of high quality with improved performance characteristics (compressive strength, water resistance, frost resistance and corrosion resistance). Studies have shown that the complex modifier-modified SCC compositions have a high degree of resistance in aggressive environments and leaching corrosion. Based on the results of the conducted tests, it is possible to recommend the obtained SCC compositions for production of building products working in the zone of alternating freezing-thawing and aggressive soils.

Low temperatures in the autumn induce enhanced expression/relative accumulation of several cold-inducible transcripts/proteins with protective functions from Late-embryogenesis-abundant (LEA) superfamily including dehydrins. Several studies dealing with plants grown under controlled conditions revealed a correlation (significant quantitative relationship) between dehydrin transcript/protein relative accumulation and plant frost tolerance. However, to apply these results in breeding, field experiments are necessary. The aim of the review is to provide a summary of the studies dealing with the relationships between plant acquired frost tolerance and COR/LEA transcripts/proteins relative accumulation in cereals grown in controlled and in the field conditions. The impacts of cold acclimation and vernalization processes on the ability of winter-type Triticeae to accumulate COR/LEA proteins are discussed. The factors determining dehydrin relative accumulation under controlled cold acclimation treatments versus field trials during winter seasons are discussed. In conclusion, it can be stated that dehydrins could be used as suitable indicators of winter surival in field-grown winter cereals but only in plant prior to the fullfilment of vernalization requirement.

In this study, based on frost formation data provided by Harbin Meteorological Bureau, combined with geographical factors, temperature and population density, linear fitting, Mann-Kendall mutation test, pettitt method and sliding T test were used to analyze the spatio-temporal variation characteristics of frost date in Harbin Municipality and the effects of geographical factors, temperature and population density on frost regularity. The results showed that (1) The earliest year of FSD appeared was 1966 and 1967, on the 255th, i.e., August 18th, and the latest was 283 days, i.e., October 10th, 2006. The earliest year in which the FED appeared was April 24th of 2015, the 114th day of that year, and the latest was April 21st of 1974, the 141st day of that year. The year with the most frost was 2012, with 161 days, and the year with the shortest was 1966, with 123 days. (2) Throughout the study period, FSD increased by 7.8 days at a rate of -1.27d/10a, FED increased by 10.9 days at a rate of 1.77d/10a, and FFS increased by 18.9 days at a rate of 3.05d/10a. The tendency rate of FSD and FFS at each site in Harbin showed an increasing trend. For FED, the tendency rate of some sites showed an increasing trend. In general, FSD showed a delayed trend, FED showed an advanced trend, and FFS showed a prolonged trend. Using the method of unary linear regression, FSD of each site showed an increasing trend, FFS showed an increasing trend, and FED showed a decreasing trend in general. (3) Throughout the study period, FSD was mutated in 2000, and the arrival time of it in the study area averaged the 265th, i.e., September 22nd, and after that, the arrival time of it changed to the 272nd, i.e., September 29th of that year. FED was mutated in 2006, and the arrival time of it in the study area averaged 128th, i.e., April 8th. After the mutation, the arrival time of FED changed to 121st, i.e., April 1st of that year. FFS was mutated in 2004. Before the mutation, with an average arrival time of 137days in the study area .But after that, the time changed to 150 days.(4) FSD and FFS in Harbin Municipality were negatively correlated with latitude and positively correlated with temperature, while FED was positively correlated with latitude and negatively correlated with temperature. The FSD, FED and FFS in the central part of Harbin Municipality were the earliest, the latest and the longest, respectively, so the Pearson correlation coefficient method and the influence of longitude could not be reflected in the multiple regression. Several factors were judged by grey correlation analysis method. The longitude is significantly related to FSD, FED and FFS.

Fraudulent transactions pose a significant threat to financial institutions and e-commerce platforms.Machine learning models, trained on historical labeled data (fraudulent vs. legitimate transactions), are often employed to identify and prevent fraud. However, real-world datasets frequently exhibit class imbalance, where fraudulent transactions (minority class) are significantly outnumbered by legitimate transactions (majority class). Machine learning models may perform poorly as a result of this imbalance, underestimating fraud and favouring the majority class. This paper proposes a novel approach to address class imbalance and improve fraud detection accuracy. We explore the implementation of FROST (Feature space RObust Synthetic saTuration) oversampling, a technique specifically designed to generate synthetic samples for the minority class. The FROST function leverages the k-nearest neighbors (KNN) algorithm and a user-defined amplification factor (m) to create synthetic data points that closely resemble existing minority class instances. We integrate the FROST-enhanced oversampling technique into the machine learning pipeline for fraud detection. The paper evaluates the effectiveness of this approach compared to traditional oversampling methods and analyzes its impact on classification accuracy metrics.

Frost heave, which is the volumetric expansion of frozen soil, has great ecological significance, since it creates water storage spaces in soils at the beginning of the growing season in cold temperate forests. To understand the characteristics of frost heave in seasonally frozen soil and the factors that impact its extent, we investigated the frost heave rates of forest soil from different depths and with different soil moisture contents, using both lab-based simulation and in situ measurement in a broadleaved Korean pine forest in the Changbai Mountains (northeastern China). We found that frost heave was mainly affected by soil moisture content, soil type, and gravitational pressure. Frost heave rate increased linearly with soil moisture content, and for each 100% increase in soil moisture content, the frost heave rate increased by 41.6% (loam, upper layer), 17.2% (albic soil, middle layer), and 4.6% (loess, lower layer). Under the same soil moisture content, the frost heave rate of loam was highest, whereas that of loess was lowest, and the frost heave of the uppermost 15 cm, which is the biologically enriched layer, accounted for ~55% of the frost heave. As a result, we determined the empirical relationship between frost heave and freezing depth, which is important for interpreting the effects of frost heave on increases in the storage space of forest soils and for calculating changes in soil porosity.

In order to reveal the frost heaving mechanism of void water behind the lining of high-speed railway tunnels in cold regions，the voids were first classified according to the positional relationship between voids and waterproof panels，and then the water supply and discharge conditions of different types of voids were investigated，then the influence of the excretion conditions on the frost heave force was experimentally studied. Based on these conditions，circular wedge-shaped and flying saucer-shaped void freezing models were established to analyze the evolution process of accumulated water frost heave. Then，according to the relative position of the excretion channel and the void，the excretion coefficient was introduced，and the calculation method of the frost heaving force of the voided water was proposed，and the influencing factors and laws of the frost-heave force were revealed. The results are shown as follows: 1) The blockage of the excretion channel will lead to the generation of frost heaving force; 2) The freezing and thawing process of the water within the cavity develops from the thinnest part of the void edge to the thicker part，and the process of frost heave-thaw，water replenishment-re-freeze heave of the water within the cavity leads to greater and greater frost heave force; 3) The frost-heaving force of the water within cavity is controlled by the void height and the position of the excretion channel. The larger the cavity height is or the closer the excretion channel is to the bottom surface of the void，the greater the frost-heave force is.

The genetic pool of valuable old ornamental cultivars and their in situ maintenance may be threated by climate change. Meanwhile, the ornamental plants like roses make up an important share of both gardens and urban green spaces, where they are particularly vulnerable to multistress growth conditions. The aim of this research was to evaluate the effect of changing climatic conditions on growth and flowering of 11 historic climber roses through long-term studies (2000-2017) conducted in Central Europe. The evaluation of plants consisted of assessment of frost damage and the timing of early phenological stages (starting of bud break, leaf unfolding) as well as gathering data on beginning, fullness and end of flowering and its abundance. Frost damage was not recorded in any year only in ‘Mme Plantier’, and did not occur for any cultivar after the winter in the years 2007, 2008, and 2014. Only a little damage to one-year shoots was recorded after the winter in the years 2015-2017. Frost damage to ‘Alberic Barbier’, ‘Albertine’, ‘Chaplin's Pink Climber’, ‘Orange Triumph clg’ and ‘Venusta Pendula’ led to pruning to ground level in every year excluding those listed above. Frost damage of once blooming roses limited their flowering; however, the many-year data-sets showed a trend for decreased frost damage and improved abundance of flowering, and these results can be interpreted as a response to the increase of average air temperature. The timing of bud breaking and leaf development in all climber roses was strictly correlated with average air temperature in the dormancy period. The reactions of climber roses to weather conditions confirmed the influence of climatic changes on ornamental crop plants in Central Europe, introducing the potential possibility for the wider application of climber roses, but without certainty of flowering every year.

In road construction, before applying an asphalt or concrete surface, the ground must be compacted and stabilized. There are two basic methods of soil stabilization: in situ and in a stationary node (ex-situ). The method of performing stabilization in place (in-situ) is the most frequently used method due to its convenience and lower price. The most popular type of binder for stabilization is a hydraulic binder (most often cement and various ashes). Such stabilization is performed at a depth of 10-50 cm, achieving the desired load-bearing parameters. In order to improve them, various chemical additives for stabilization are often used, such as ion exchange compounds, additives based on sulfuric acid, additives based on vinyl polymers or even organic additives using lignosulfonates. However, the use of such additives is associated with much greater costs and environmental burden, resulting in seeking for cheaper and equally effective alternatives. The win-win situation would be for instance recycling the problematic waste-based materials that on one hand are landfilled or impossible to recycle and on the other hand cause problems for the waste producers. Therefore, an interesting issue is the production of stabilization additives from various types of waste materials. As a result of the extensive testing of various waste-based materials blends with soil, the mechanical (compressive strength after 7 and 28 days) and hydraulic (capillary rise, water absorption, frost resistance) soil properties were measured. The optimization process led to obtaining additives compositions ensuring the best strengthening and sealing properties. These were for sandy soil: Pure foil (wax emulsion), Pure foil (wax emulsion) + waste sulphuric acid, RDF from waste tires (wax emulsion), Pure foil (wax emulsion) + “by-pass” waste ash + NaOHx2 and for clayey soil: Pure foil (wax emulsion) + NaOH, Pure foil (wax emulsion) + waste sulphuric acid, Tequant, Pure foil (wax emulsion).