High Probability Of Occurrence Research Articles

금융권 종업원의 마키아벨리즘과 비윤리적 친조직 행동 : 도덕적 이탈의 매개효과 및 조직동일시의 조절효과

This study paid attention to the lack of Unethical Pro-organizational Behvaiour(UPB) research on financial sector employees who have a high probability of actual occurrence of UPB, such as act of commission and act of omission. As a representative antecedent for UPB, machiavellianism was considered. As a mediator, moral disengagement was related to a personal internal psychological change that linked between machiavallianism and UPB. This study also examined the moderating role of organizational identification in order for testing a controversial debate on positive/negative influence of organizational identification on organizational effectiveness. In doing this empirical test, 483 questionnaires were collected (respondent rate 80.5%), and 438 copies were used to analyze. The study tested the direct effect by using an hierarchical regression analysis and the mediation and moderation effects by Hayes' PROCESS Macro analysis. The findings were as followed. First, machiavellianism had a significantly positive effect on UPB. Second, moral disengagement significantly mediated the relationship between machiavellianism and UPB. Third, the relationship of positive between moral disengagement and UPB was non-linearly adjusted in the form of an inverted U-shaped of organizational identification. In conclusion, the summary, theoretical and practical implications were discussed.

Rurality, Socioeconomic Status, and Residence in Environmental Risk Areas Associated with Increased Lyme Disease Incidence in Ontario, Canada: A Case-Control Study.

Background: Lyme disease (LD) is the most common tick-borne illness in North America. LD is acquired through exposure to the tick vector, Ixodes scapularis, known as the blacklegged tick. In Canada, LD is rapidly emerging, with the establishment of I. scapularis in many newly endemic regions posing a growing risk to local communities. In the Canadian context, many environmental and socioeconomic risk factors for human LD infection are yet to be ascertained and the degree of risk associated with residential and community exposure to ticks is not well known. Methods: We conducted a matched case-control study in southeastern Ontario, using LD patient data from provincial laboratory databases and uninfected population controls from 2014 to 2018. We aimed to identify area-level risk factors for LD and associations with residence in environmental risk areas, defined as areas with high model-predicted probability of I. scapularis occurrence, using the neighborhood dissemination area as the unit of analysis. Results: Using multivariable conditional logistic regression analysis, we identified that patients with LD had higher odds (odds ratio, OR; 95% confidence interval, CI) of living in neighborhoods with high probability of tick occurrence in the environment (OR = 2.2; 95% CI: 2.0-2.5), low walkability (OR = 1.6; 95% CI: 1.2-2.1), low material deprivation (OR = 1.4; 95% CI: 1.2-1.7), and low ethnic concentration (OR = 8.1; 95% CI: 6.7-9.9). We also found that the odds of LD infection for individuals residing in environmental risk areas was highest for those living in public health units (PHUs) with <250,000 population (OR = 3.0; 95% CI: 2.4-3.9) compared to those living in PHUs with >1,000,000 population (OR = 1.5; 95% CI: 1.1-2.1). Conclusion: This study shows that odds of human LD infection in Ontario, Canada is higher in less urbanized areas with higher socioeconomic status and indicates that exposure to ticks around the home residence or neighborhood is linked to increased odds of LD.

Risk assessment of mobile crane overturning in Asymmetric Tandem Lifting (ATL) operation based on fuzzy fault tree analysis (FFTA)

Lifting operation, especially Asymmetric Tandem Lift, is one of the essential activities in the construction industry, posing a substantial threat to sustainable management. This study aims to assess the risk of crane overturning in ATL using the fuzzy fault tree analysis method. The risk factors affecting crane overturning were identified and quantified. the required information was collected through literature review, previous incidents data and expert opinions. The weight of experts was determined based on a combination of two methods, including conventional scoring methods and the best-worst fuzzy method. A total of 53 events in four categories of loading technique, weather conditions, ground failure, and organizational factors were determined as the main factors of crane overturning. The probability of the crane overturning was 10.68%. The highest probability of occurrence among 34 minimum cut sets was related to the risks due to failure in the supply of modern equipment and technologies (0.132), failure in load/equipment information provided by the manufacturer (0.125) and failure in instructions and administration (0.110). The proposed method in this study could reduce the ambiguities and uncertainties in identifying and evaluating risk factors. Moreover, presented prevention strategies could enhance the reliability and sustainability of cranes in asymmetric tandem lift operations.

Veteran trees in decline: Stratified national monitoring of oaks in Norway

Old veteran trees function as biodiversity hotspots in both forests and open landscapes, and protecting such trees is an important measure to halt loss of biodiversity. Nevertheless, the number of veteran trees continues to decline worldwide, although estimates of this decline mainly stem from geographically restricted case studies. In Norway, veteran oak trees have received special protection since 2011 through the Norwegian Biodiversity Act, however, there is a lack of knowledge on status and trends for these trees. A national monitoring program was started in 2012, using a random, stratified sampling procedure. We use the data from the baseline survey and the first monitoring revisit to estimate the total number as well as mortality trends of veteran oaks in Norway. Further, we assess recruitment potential (in the baseline survey) and changes in variables describing ecological state such as regrowth.The monitoring area covered the geographical distribution of oaks in Norway and was divided into > 200000 plots of 500 × 500 m. A set of 500 monitoring plots were randomly selected from two strata: High probability plots (n = 100; plots with high probability of occurrence of veteran oaks), and Low probability plots (n = 400), using existing knowledge and databases. Plots were surveyed over a five year-period (2012–2016), with 20 HighProb-plots and 80 LowProb-plots each year. All veteran oaks that were observed during the baseline survey were revisited in 2019, three to seven years after they were initially registered. Tree absence and cause of death/change of ecological status was recorded. We estimated a total of 138100 veteran oaks in Norway based on the baseline survey, of which 25000 could be denoted “top quality oaks”. Based on the revisit, we estimated a loss of 7600 veteran trees, i.e., an annual mortality rate of 1.2%. Recruitment oaks were present in most plots with veteran oaks, but recruitment into the veteran oak category is slow and unlikely to balance out the mortality rate. More precise estimates of recruitment should be prioritized in future monitoring. The estimate of 138000 veteran oaks far exceeds the appr. 10000 trees registered in the national database, and clearly demonstrates the need for continued mapping and monitoring to improve the foundation for a knowledge-based land management. Further, this short-term monitoring demonstrates the decline of this biodiversity hotspot and pivotal source of ecosystem functions, despite increased protection in recent years. Our results and conclusions are relevant also for veteran trees of other species than oak.

Meteorological flash droughts risk projections based on CMIP6 climate change scenarios

Meteorological flash droughts (MFDs) are sub-seasonal-to-seasonal drought phenomena characterized by rapid onset/intensification. This study assesses the changes in trends and hotspot regions of MFDs for the present and five future CMIP6 SSP forcing scenarios (SSP-FS) at global-, continental- and regional-scales. Analysis with 12 GCMs indicates that globally, frequency, duration and severity of MFDs are projected to increase ~20–50%, 20–58%, and 26–62%, respectively, with the highest occurrence probability during the summer season. The MFD hotspot regions appeared prominent in arid and semi-arid zones. MFD exposure risk is projected to exceed ~1.5 folds in most continents, with the highest risk in the Indian sub-continent. Furthermore, in Europe and South America, which are currently less impacted by MFDs, a considerable increase in hotspot regions (~122–127%) is projected under the warmest SSP-FS. The LULC-classes and elevation range most vulnerable to MFDs, and regional potential hydrometeorological drivers that trigger the development of MFDs are identified.

Probabilistic Evaluation of Susceptibility to Fluid Injection-Induced Seismicity Based on Statistics of Fracture Criticality

AbstractFault reactivation and associated microseismicity pose a potential threat to industrial processes involving fluid injection into the subsurface. In this research, fracture criticality, defined as the gradient of critical fluid pressure change to trigger seismicity (Δpc/h), is proposed as a novel reservoir depth-independent metric of fault slip susceptibility. Based on statistics of the fracture criticality, a probabilistic evaluation framework for susceptibility to injection-induced seismicity was developed by integrating seismic observations and hydrogeological modelling of fluid injection operations for faulted reservoirs. The proposed seismic susceptibility evaluation method considers the injection-driven fluid pressure increase, the variability of fracture criticality, and regional fracture density. Utilising this methodology, the probabilistic distribution of fracture criticality was obtained to evaluate the potential for injection-induced seismicity in both fault and off-fault zones at the Hellisheiði geothermal site, Iceland. It has been found that the fracture criticality within both fault and off-fault zones shows natural variability (mostly ranging between 0.001 and 2.0 bar/km), and that fault zones tend to be characterised by larger fracture criticality values than the off-faut zones. Fracture criticality values estimated within each zone roughly follow a Gaussian distribution. Fault zones around five geothermal fluid re-injection wells at the site were estimated to have relatively high probability of seismic event occurrence, and these regions experienced high levels of induced seismicity over the microseismic monitoring period. The seismotectonic state estimated for each zone is generally consistent with the forecasted susceptibility to seismicity based on statistics of fracture criticality.

Modeling drought stress impacts under current and future climate for peanut in the semiarid pampas region of Argentina

In the semiarid pampas region of Argentina, peanut ( Arachis hypogaea L.) crop undergoes frequent and unpredictable drought stress periods, with high probability of occurrence under future climate change projections. However, the overall frequency of occurrence and timing of different drought stress patterns under current and future climates has not been well investigated for the main peanut region in central Argentina. The aims of this study were to: (i) define the main peanut drought stress patterns and their occurrence (frequency) during the peanut growing season, via a crop growth modeling approach, (ii) test seed yield stability of the formerly defined (in i) drought stress patterns under future climate scenarios, and (iii) analyze the effect of sowing dates on peanut seed yield as a management strategy to mitigate the impact of future climate scenarios for peanut seed yield in the semiarid pampas region of Argentina. The APSIM-peanut growth model was calibrated and validated for local genotypes and production environments. Our study simulated seasonal drought stress patterns at five representative locations across the region under current and future climate scenarios, and tested six sowing dates as a practice to mitigate the impact of climate change. Clustering analysis identified two contrasting environment types (ETs). The high stress ET showed greater frequency of occurrence (>50%) at the southern locations. Future climate conditions increased the frequency of high stress ET by roughly 6% and reduced peanut seed yield by 12%, as average across locations. For both current and future climates, earlier sowing dates maximized peanut seed yield, regardless the locations. Changing sowing date was not an effective practice to mitigate the negative impact of climate change on peanut seed yield. The defined ETs allowed identifying a target population of environments (TPE) having implications for optimizing peanut breeding and management strategies. The projected increase in the frequency of drought stress for all tested locations provides a challenging scenario for sustaining peanut productivity in this region. • The aims were to determine drought patterns under current and future climate, and to test sowing date as a mitigation tool • The defined drought stress patterns changed the frequency across locations, identifying a target population of environments • ·Future climate increased the frequency of drought stress by ~6% and reduced peanut seed yield by ~12% • Sowing date did not mitigate climate change impact. • This study provides insights to optimize breeding and management, and assists policy makers to address climate change.

Integrating plot‐based and remotely sensed data to map vegetation types in a New Zealand warm‐temperate rainforest

AbstractQuestions(1) What can be learned by extending a national classification into unsampled forest types? (2) Are both remotely sensed and environmental predictors needed to model and map associations? (3) For mapping, are LiDAR‐generated canopy structure parameters or reflectance from spectral imagery more useful? (4) How can we assess uncertainty of a final map?LocationWarawara Forest, Northland, New Zealand.MethodsWe sampled 205 vegetation plots and assigned them to an existing national classification using the fuzzy classification framework of noise clustering. Plots too distinct to be assigned were used to define new associations. We produced spatial models of each association using boosted regression trees. Predictors included 11 environmental, 11 canopy reflectance, and 17 canopy structure variables. We created a composite map by assigning each map pixel to the association with the highest occurrence probability. We evaluated uncertainty by examining locations where no class was predicted with probability above 0.2 and by creating a confusion map based on entropy.ResultsForty‐five plots were assigned to six of 79 existing national associations and 147 plots were used to define two new forest associations. Three shrubland types are widespread nationally, whereas two young forest types are northern. Three mature forest types are narrowly distributed nationally, with the new “High‐elevation hardwood forest” largely restricted to Warawara Forest. Three associations were mapped using remotely sensed predictors alone, whereas two also required environmental predictors. Overall, canopy reflectance predictors explained more deviance than canopy structure. Examining locations where no association was predicted well and where multiple associations were predicted equally showed areas mapped as younger forests to have greatest uncertainty.ConclusionsIn answering our questions, we present a vegetation classification and map for Warawara Forest that provides a framework to guide the indigenous people's management responses to threats to valued communities and their species.

Flexural behavior of wood in the transverse direction investigated using novel computer vision and machine learning approach

Abstract A deep-learning-based semantic segmentation approach (U-Net) was used to partition the anatomical features in the cross-section of hinoki (Chamaecyparis obtusa) wood during a micro three-point bending test. Using the Crocker–Grier linking algorithm, thousands of cells were successfully extracted, and several parameters (area, eccentricity, fitted ellipse aspect ratio, bounding box aspect ratio) were used to evaluate the intensity of the cells’ deformation. Thus, the 2D map of the deformation intensity distribution was constructed. By analyzing flat-sawn, quarter-sawn, and rift-sawn specimens, it was confirmed that the annual ring orientation affects the flexural behavior of wood in the transverse direction. The quarter-sawn specimens exhibited the largest modulus of elasticity (MOE) and modulus of rupture (MOR). The ray tissue aligned against the load may have contributed to the restriction of cell deformation. The rift-sawn specimens exhibited the smallest MOE and MOR, possibly owing to the loading of the specimen in the in-plane off-axial direction, which induced the shear deformation of the cell wall. For all three specimen types, the fracture had high occurrence probability in the tension part of the specimen, which exhibited large cell deformation. Therefore, the proposed method can be adapted to the prediction of wood specimen fractures. With different test wood species, this approach can be of great help in elucidating the relationship between the anatomical features and the mechanical behavior of wood to improve the effective utilization of wood resources.

Design and analysis of the bulbous-bottomed oscillating resonant buoys for an optimal point absorber wave energy converter

This study proposes innovative bulbous-bottomed buoy designs for an optimal oscillating-body wave energy converter (WEC). The effects of buoy shapes and the shape-influenced hydrodynamic coefficients on the motion and power absorption efficiency of a single-body heaving WEC are investigated. The frequency-domain analyses and spectral modeling were performed in ANSYS AQWA considering regular and irregular waves for optimal and sub-optimal power take-off (PTO). The wave climate data was obtained for ShiDao station China, and the middle frequency of the wave range with the highest probability of occurrence was selected as standard natural frequency, which was achieved by equalizing the diameter, mass, and volume of all the buoys. The bulbous-bottomed buoys could achieve 28.1% higher absorption efficiencies than the non-bulbous shapes. The buoy with the most expansive bulbous bottom of 1.6m height (SB-3) is the most optimal buoy with the highest power absorption and efficiency in both optimal and suboptimal PTO modes, with a maximum of 16.8% and 21.5% increase in response amplitude operator (RAO) and power absorption, correspondingly, relative to non-bulbous cylindrical-hemispherical (C-HS) buoy. The experimental validation of the simulated RAO and power of the 1:12.5 scale model of the SB-3 revealed 28% and 27.18% greater values, respectively, compared to C-HS, justifying that the SB-3 buoy could be a better choice for designing an oscillating-body WEC in all waves. By increasing the bulbous bottom width by 90% and fillet height by 100%, the performance of the bulbous buoys was enhanced by 12.2%.

Quantifying controls on the occurrence of nonmarine fossils

Abstract Although numerous studies have described differential preservation of nonmarine fossils in channel and floodplain facies, quantitative comparisons are lacking. We present measurements of the probability of occurrence of plant, mollusk, and vertebrate fossils in the Campanian Judith River Formation of north-central Montana, USA. The data reveal little difference in the probability of occurrence among higher taxa in channel and floodplain facies, except for plants, which have a higher probability in floodplain deposits. This surprising result supports more recent models in which many organisms are buried initially in floodplain deposits, but those deposits are subsequently exhumed by migrating rivers, and finally buried in those channels. Comparisons across systems tracts revealed intriguing patterns in which plants have a higher probability of occurrence in high-accommodation systems tracts in channel and floodplain deposits, and vertebrates have a higher probability of occurrence in channels of the low-accommodation systems tract. These results confirm that sequence-stratigraphic architecture should be considered in interpretations of the nonmarine fossil record. This probability of occurrence method has promise for many other comparisons of fossilization potential.

Systemic evaluation of human resources risks in the public sector

AbstractThis study tries to design a model for assessing and prioritizing human resources risks, using systems thinking and relying on the experiences of Mashhad Municipality in Iran. Reviewing various sources, this study identifies risks in human resources and uncovers the cause and effect relationships between their dimensions and components. Then, using qualitative and quantitative methods, the proposed model is evaluated. Results show five main subsystems of human resources operational risks, personal risks, professional risks, human capital risks and contextual risks. The results also show that there is a dynamic relationship between the components of these subsystems. It is shown that human resources' operational risks have the highest probability of occurrence and intensity of impact and human capital risks have the lowest probability of occurrence and intensity of impact. The system diagrams of this study provide researchers and practitioners with a comprehensive perspective to consider human resources risks in public organizations.

Predicting habitat suitability for Ixodesricinus and Ixodespersulcatus ticks in Finland

BackgroundTicks are responsible for transmitting several notable pathogens worldwide. Finland lies in a zone where two human-biting tick species co-occur: Ixodesricinus and Ixodespersulcatus. Tick densities have increased in boreal regions worldwide during past decades, and tick-borne pathogens have been identified as one of the major threats to public health in the face of climate change.MethodsWe used species distribution modelling techniques to predict the distributions of I.ricinus and I.persulcatus, using aggregated historical data from 2014 to 2020 and new tick occurrence data from 2021. By aiming to fill the gaps in tick occurrence data, we created a new sampling strategy across Finland. We also screened for tick-borne encephalitis virus (TBEV) and Borrelia from the newly collected ticks. Climate, land use and vegetation data, and population densities of the tick hosts were used in various combinations on four data sets to estimate tick species’ distributions across mainland Finland with a 1-km resolution.ResultsIn the 2021 survey, 89 new locations were sampled of which 25 new presences and 63 absences were found for I.ricinus and one new presence and 88 absences for I.persulcatus. A total of 502 ticks were collected and analysed; no ticks were positive for TBEV, while 56 (47%) of the 120 pools, including adult, nymph, and larva pools, were positive for Borrelia (minimum infection rate 11.2%, respectively). Our prediction results demonstrate that two combined predictor data sets based on ensemble mean models yielded the highest predictive accuracy for both I.ricinus (AUC = 0.91, 0.94) and I.persulcatus (AUC = 0.93, 0.96). The suitable habitats for I.ricinus were determined by higher relative humidity, air temperature, precipitation sum, and middle-infrared reflectance levels and higher densities of white-tailed deer, European hare, and red fox. For I.persulcatus, locations with greater precipitation and air temperature and higher white-tailed deer, roe deer, and mountain hare densities were associated with higher occurrence probabilities. Suitable habitats for I.ricinus ranged from southern Finland up to Central Ostrobothnia and North Karelia, excluding areas in Ostrobothnia and Pirkanmaa. For I.persulcatus, suitable areas were located along the western coast from Ostrobothnia to southern Lapland, in North Karelia, North Savo, Kainuu, and areas in Pirkanmaa and Päijät-Häme.ConclusionsThis is the first study conducted in Finland that estimates potential tick species distributions using environmental and host data. Our results can be utilized in vector control strategies, as supporting material in recommendations issued by public health authorities, and as predictor data for modelling the risk for tick-borne diseases.

Improvement of the Resilience of a Microgrid Using Fragility Modeling and Simulation

The modern microgrid is designed to withstand various disruptive events that have a high probability of occurrence but have a low impact on the system. This improves the reliability of the system but does not take into consideration the disruptive events that have a low probability of occurrence but have a large impact on the system, such as extreme weather or natural disasters. Redesigning a microgrid to withstand low probability high impact events is very costly and is not a feasible solution to existing microgrids. This paper proposes a method to improve the resilience of an existing microgrid to quickly recover from low probability high impact events. The method used for this purpose is a combination of Monte Carlo simulation and prioritization of load of the microgrid. The efficacy of the method is examined by modeling microgrids using a fragility model. Using the proposed novel resilience index, the resilience of the IEEE 5-Bus system and IEEE 14-Bus system and the effect of load shedding on the resilience of the microgrid are analyzed and presented. The effect on smaller and larger grids and their resilience is examined. A novel resilience index is used to quantify the improvement of resilience of the proposed method when compared to other methods available in the literature.

Risk Analysis of Seaport Construction Project Execution

This article concerns the assessment of the level of risk at the stage of construction of a seaport, with particular emphasis on selected adverse incidents that can significantly affect the timeliness of the investment. In this article, the matrix method was used to analyse and evaluate the level of risk, and statistical analysis and case studies were used to identify incidents occurring during the port construction project. This allowed the identification of incidents with the highest probability of occurrence during the port construction process and to determine their impact on environmental pollution and the timeliness and success of the investment. The risk analysis performed identified 15 typical incidents of technical nature. The determined risk level for these incidents is at a moderate level or lower, which can be considered acceptable. For all undesirable incidents the values of probability and loss levels have been averaged, because e.g., a fire can have an extremely different dimension and can cause a different scale of losses. Analysis presented in the paper indicate the need to develop procedures for proceeding during the implementation of significant technical tasks to minimize the level of risk of adverse incidents and their consequences.

Automated diagnosis of optical coherence tomography imaging on plaque vulnerability and its relation to clinical outcomes in coronary artery disease

This study sought to develop a deep learning-based diagnostic algorithm for plaque vulnerability by analyzing intravascular optical coherence tomography (OCT) images and to investigate the relation between AI-plaque vulnerability and clinical outcomes in patients with coronary artery disease (CAD). A total of 1791 study patients who underwent OCT examinations were recruited from a multicenter clinical database, and the OCT images were first labeled as either normal, a stable plaque, or a vulnerable plaque by expert cardiologists. A DenseNet-121-based deep learning algorithm for plaque characterization was developed by training with 44,947 prelabeled OCT images, and demonstrated excellent differentiation among normal, stable plaques, and vulnerable plaques. Patients who were diagnosed with vulnerable plaques by the algorithm had a significantly higher rate of both events from the OCT-observed segments and clinical events than the patients with normal and stable plaque (log-rank p < 0.001). On the multivariate logistic regression analyses, the OCT diagnosis of a vulnerable plaque by the algorithm was independently associated with both types of events (p = 0.047 and p < 0.001, respectively). The AI analysis of intracoronary OCT imaging can assist cardiologists in diagnosing plaque vulnerability and identifying CAD patients with a high probability of occurrence of future clinical events.

Field observation and numerical analysis of rip currents at Ten-Mile Beach, Hailing Island, China

Rip currents are a type of high-speed cross-shore current that occur in coastal areas. They are one of the deadliest natural hazard that occur along coasts. At Ten-Mile Beach on Hailing Island in Yangjiang, China, there have been a number of drowning accidents, most of which have been investigated to be related to rip currents. In order to investigate the rip current phenomenon at this beach, a 24-day beach observation was conducted from August 7 to August 30, 2021. This field investigation included wave observation in the surf zone, bathymetric measurements, unmanned aerial vehicle (UAV) monitoring, and sediment sampling. During the investigation, the beach state changed successively from barred to low tide terrace rip currents and low tide bar/rip, which are beach types with a high probability of rip current occurrence. Wave height was the main factor controlling the beach state and the occurrence of rip currents. The numerical simulation results of the XBeach model were in good agreement with images taken by UAV, confirming that the rip current hazard estimation model can effectively characterize the rip current hazard level for different beach stages. The results of the study provide a useful reference for beach development management and rip current warning at Ten-Mile Beach.

Farm households’ flood risk perception and adoption of flood disaster adaptation strategies in northern Ghana

Northern Ghana is noted for its significant contribution to the food basket in Ghana. Farmers in the region suffer severely from extreme climatic conditions, with floods among the most devastating disasters. This study uses binary logistic regression model and the Poisson count model to address this threat to food security by analyzing the nexus between flood risk perception and farm households' adoption of flood disaster adaptation strategies in Northern Ghana, including significant factors such as off-farm employment, cooperative memberships, and access to credit. Results indicate that the flood disaster adaptation rate was low among farmers in the region, with only 41% adopting at least one adaptation strategy. Flood disaster risk perception had a significant effect on farm households' preparedness. Farm households with the perception of severe floods, high probability of flood occurrence, sense of worry, and threats to farm inputs and yield from flood disasters were more likely to adopt more strategies to adapt and mitigate flood risks. Additionally, off-farm employment, cooperative membership, access to credit, extension services, household income, and education significantly affected farmers’ flood disaster adaptation behaviour. This study recommends that great attention be shifted towards empowering farm households on flood risk awareness and the fundamental strategies involving on-farm (agronomic practices and farm water distribution) and off-farm practices (off-farm employment and cooperative memberships) to mitigate flood risks.

Effects of vaccination, new SARS-CoV-2 variants and reinfections on post-COVID-19 complications.

Post-COVID-19 complications involve a variety of long-lasting health complications emerging in various body systems. Since the prevalence of post-COVID-19 complications ranges from 8–47% in COVID-19 survivors, it represents a formidable challenge to COVID-19 survivors and the health care system. Post-COVID-19 complications have already been studied in the connection to risk factors linked to their higher probability of occurrence and higher severity, potential mechanisms underlying the pathogenesis of post-COVID-19 complications, and their functional and structural correlates. Vaccination status has been recently revealed to represent efficient prevention from long-term and severe post-COVID-19 complications. However, the exact mechanisms responsible for vaccine-induced protection against severe and long-lasting post-COVID-19 complications remain elusive. Also, to the best of our knowledge, the effects of new SARS-CoV-2 variants and SARS-CoV-2 reinfections on post-COVID-19 complications and their underlying pathogenesis remain to be investigated. This hypothesis article will be dedicated to the potential effects of vaccination status, SARS-CoV-2 reinfections, and new SARS-CoV-2 variants on post-COVID-19 complications and their underlying mechanisms Also, potential prevention strategies against post-COVID complications will be discussed.

ASSESSMENT OF GRAIN YIELD STABILITY AND RELIABILITY IN SOME WINTER WHEAT VARIETIES

Considering the continued and unpredictable variation of climatic condition, the yield stability has become an important topic in wheat breeding. This study evaluated the grain yield of 11 winter wheat varieties with different genetic and ecologic origin during three years, to compare the effects of genotype, year and genotype × year interactions and to determine their stability and reliability for cultivar recommendations. The climatic conditions during the three years had the highest contribution (80.03%) to the yield variability of wheat, while the varieties had a lower influence (11.41%), and the variety x year interaction contributed only with 8.56% to the total variation. In 2020, the climatic conditions were significantly more favorable than in 2018–2019, allowing obtaining yield increases of 33.82-44.20%. Also, in 2018 there was a higher favorability of the growing conditions compared to that of 2019, associated with significant yield increases of 7.75%. The highest yield stability was observed in Boema and Galio varieties, on the background of a non-crossover genotype x environment (GE) interaction. The stability of these varieties has been associated with different yield levels, above the experience mean in Galio and below the experience mean in Boema, respectively. In Akteur and Josef varieties, the yield was strongly influenced by the GE interaction, being associated with lower levels than the experience mean. On the background of high occurrence probabilities (0.75–0.95) of unfavorable environmental conditions for wheat crop, Galio and Laurenzio varieties would have the highest yield reliability, associated with values of 5173–6328 kg/ha (Galio) and 5101–5979 kg/ha (Laurenzio). As such, given the results of all stability parameters, it turns out that the Romanian varieties showed a good adaptation to the local ecological conditions compared to most of the foreign varieties.