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Abstract Long-term oral health issues caused by fungi and bacteria are a primary concern for individuals who wear dentures. Denture stomatitis, primarily caused by Candida albicans (C. albicans), is a prevalent condition among denture users. Metal nanoparticles exhibit improved antimicrobial effectiveness and fewer adverse effects. This study aimed to evaluate the antifungal and antibacterial effects of nystatin-coated silver nanoparticles (Nys-coated AgNPs) embedded in acrylic resin as a more biocompatible material for denture resins. AgNPs and Nys-coated AgNPs were synthesized and characterized using UV-Vis, SEM, EDX, and DLS. Specimens of polymethyl methacrylate (PMMA) with three different concentrations of Nys, AgNPs, and Nys-coated AgNPs (0.1%, 1%, 10% w/w) were prepared. The water absorption properties of the disks and drug release were investigated for 14 days and 120 h, respectively. The hydrophilic and hydrophobic properties of the samples and their contact angles were evaluated using the sessile drop technique. The antifungal and antimicrobial activity of the prepared discs was studied against C. albicans and Streptococcus mutans, respectively. Adding Nys-coated AgNPs decreased the contact angle of discs from 67° to 49°. Furthermore, the water absorption rates of the different discs were not significantly different from those of the control groups. Results showed that Nys-coated AgNPs (10% w/w) in PMMA effectively inhibited C. albicans growth better than Nys composites (10% w/w). Additionally, Nys-coated AgNPs composites, as well as AgNPs-containing composites, showed considerable antibacterial activity against S. mutans. Nys-coated AgNPs (10% w/w) had no toxic effect on NIH3T3 cells. In conclusion, Nys-coated AgNPs could be considered a good candidate for incorporation into denture resins to address chronic oral diseases.

Regarding the importance of preventing peri-implantitis in dental implants, the current study aimed to coat a healing abutment with gelatin–curcumin nanocomposites, and the stability of this coating on the healing abutment was evaluated. A cell viability measuring test was used to determine the cytotoxicity of nanocomposites against dental pulp stem cells. To show the pattern of curcumin release from nanocomposites, drug dissolution apparatus two was applied. Then, 16 healing abutments were examined in vitro. Titanium healing abutments were coated with the gelatin–curcumin nanocomposite. The dip coating method was applied for coating and the consistency of coated cases was evaluated at intervals of one, 30, and 60 days after coating inside the simulated body fluid (SBF) solution. A scanning electron microscope (SEM) was used for investigating the microstructure and morphology of coatings, and an energy dispersive X-ray (EDX) was applied for determining the combination of the coating. Moreover, the healings were weighed before and after coating via an accurate digital scale with an accuracy of 0.0001. Finally, the data were analyzed using SPSS software. The prepared nanocomposite was non-cytotoxic against tested cells. The nanocomposite showed a relatively rapid release pattern in the first 10 days for curcumin. The release of curcumin from the nanoparticles continued slowly until the 30th day. The weight changes were statistically significant (p-value < 0.001) during this time. Based on the post hoc test, the weight between two times immediately after coating and 30 days after coating, and also one day after coating and 30 days after coating, was statistically insignificant. The results revealed that the coating of the gelatin–curcumin nanocomposite on the healing was successful and this consistency was kept for at least one month. It is necessary to investigate more evaluations in different fields of physicochemical, mechanical, and antimicrobial aspects for coated healing abutments.

Background. This systematic review and meta-analysis investigated the prevalence of proximal contact loss and its associated factors. Methods. A bibliographic search was conducted in June 2021 with no limitation in the article date or language and updated in January 2022 by hand searching. There was no time limit on the search to retrieve all studies. The search included randomized controlled trials or quasi-experiments, and cross-sectional or cohort studies were included in the absence of these studies. Two authors screened the title and abstract. After evaluating the full texts of selected articles, irrelevant studies and or non-English papers that were impossible to translate were excluded. Disagreements between the re­viewers’ selection process were resolved by debate on the eligibility of studies. Standardized critical appraisal instruments from the Joanna Briggs Institute for different types of studies were used to assess the studies’ quality. Comprehensive Meta-Analysis (CMA) software (Version 2.2; Biostat, Englewood, NJ) was used for data analysis. Results. The proximal contact loss (PCL) frequency was %29. According to the results, the frequencies of PCL for the distal and mesial aspects were %7 and %21, respectively. The meta-analysis results showed that the contact loss events on the mesial aspect were statistically higher than on the distal aspect (P%50, the proximal contact loss was higher (OR: %95[ 2.43 CI: 4.03‒1.47], P=0.0006). The PCL in the anterior area was lower than in the posterior area (P=0.004). Although the frequency of contact loss in females was higher than in males, this rate was not statistically significant. Conclusion. The PCL on the mesial aspect and the posterior area was high. In individuals with bone loss >%50, the proximal contact loss was higher than in others.

Background. The most common problem associated with dental implants is the abutment screw loosening. This research aimed to investigate the effect of the type of connection on screw loosening, using a finite element method (FEM). Methods. Periosave system and different types of the implant–abutment connection were used for modeling. After being measured, CAD files were modeled using CATIA software and imported to the ANSYS analysis software, and the model was loaded. Results. A force of 100 N was applied at 0.1 second, and no force was applied at 0.42 second. The screw head deformation at 0.1 and 0.42 seconds was 8 and 3.8 μm, and 7.6 and 2.8 μm at morse taper and octagon dental implant connections, respectively. The displacement rate of the internal surface of the abutment at 0.1 and 0.42 seconds was 10.7 and 8.4 μm, and 5.7 and 5.6 µm in the octagon and morse taper dental implant connections, respectively. The displacement of the implant suprastructure–abutment interface from the screw head at 0.1 and 0.42 seconds was 9 and 7 μm, and 7 and 6 μm in the morse taper and octagon dental implant connections, respectively. At intervals of 0 to 0.1 seconds and 0.6 to 0.8 seconds, the octagon connection was separated at the maximum screw head displacement and the internal part of the abutment, but the morse taper connection did not exhibit any separation. In the above time intervals, the results were similar to the maximum state in case of the minimum displacement of the screw head and the internal part of the abutment. Conclusion. Screw loosening is less likely to occur in the morse hex connection compared to the octagon connection due to the lack of separation of the screw from the internal surface of the abutment.

Background. Monolithic zirconia is an emerging material for crowns and bridges. The possibility of full digital design has made it an attractive alternative material for implant-supported prostheses. A proper design is vital in the success of such a prosthesis like any other. This study, in the shortage of scientific evidence, has tried to assess the stress distribution of occlusal forces inside the implant-prosthesis system of a 3-unit bridge made of monolithic zirconia. Methods. A 3-unit monolithic zirconia bridge supported by two implant fixtures placed on the teeth #13 and #15 was digitalized. It was converted to a mesh of 59000 nodes and 34000 elements. Five types of occlusal forces (one as vertical centric, two at 15º and 30º simulating canine pattern of lateral movement, and two at 15º and 30º simulating group function pattern) were applied. The stress distribution among all the components of the implant-bridge system was assessed using Ansys Workbench 14 software and finite element analysis. Results. The maximum stress was between 286 and 546 MPa, which were found in either the fixture‒abutment screw area or in the upper part of the pontic connector between the canine and first premolar. The maximum pressure increased with an increase in the angle of occlusal force. Significantly higher stress was recorded in the group function occlusal pattern. Conclusion. Monolithic zirconia can be promising in designing bridges in the canine‒premolar area. However, proper design is necessary with more attention to the connectors and types of occlusal forces.

Background and aims. Various materials and methods have been introduced for obturating cleaned and shaped root canal systems. This in vitro study aimed to evaluate the sealing ability of single-cone obturation technique with mineral trioxide aggregate and calcium-enriched mixture based on bacterial leakage approach. Materials and methods. Sixty-four single-canal teeth were prepared and randomly divided into 5 groups, consisting of three experimental groups (n = 16) and two control groups (n = 8). In group 1, root canal obturation was performed using gutta-percha with 0.02 taper and AH26 sealer by lateral compaction technique. In groups 2 and 3, single Protaper guttapercha cone was used for obturation with MTA and CEM cement, respectively. A bacterial leakage apparatus was utilized for leakage assessment for 60 days. Leakage comparison between the experimental groups was performed by one-way ANOVA using SPSS 16 statistical software. Results. The mean bacterial leakage intervals in groups 1, 2 and 3 were 33.68 ± 9.39, 40.68 ± 11.03 and 39.56 ± 9.03 days, respectively. One-way ANOVA indicated no significant differences in bacterial leakage between the three experimental groups (P = 0.109). Conclusion. Single-cone obturation with well-fitted gutta-percha and MTA and CEM cement is an appropriate alternative for traditional lateral compaction technique.

GPS based vehicle navigation systems have difficulties in tracking vehicles in urban canyons due to poor satellite availability. ABS (Antilock Brake System) Navigation System consists of self-contained optical encoders mounted on vehicle wheels that can continuously provide accurate short-term positioning information. In this paper, a new concept regarding GPS/ABS integration, based on Fuzzy Logic is presented. The proposed algorithm is used to identify GPS position accuracy based on environment and vehicle dynamic knowledge. The GPS is used as reference during the time it is in a good condition and replaced by ABS positioning system when GPS information is unreliable. We compare our proposed algorithm with other common algorithm in real environment. Our results show that the proposed algorithm can significantly improve the stability and reliability of ABS/GPS navigation system.

Study region: Oulujoki River basin- Inland sub-Arctic. Study focus: Understanding the impact of projected accelerated warming and increasing precipitation in the Arctic and sub-Arctic is crucial. This study examines how these changes will reshape the hydroclimatic dynamics of the inland sub-Arctic river basin, using cold climate and precipitation indices derived from statistically downscaled General Circulation Models. New hydrological insights for the region: The results show an increase in precipitation indices, with mid-century primarily dominated by scenarios SSP1–2.6 and SSP3–7.0. Under SSP5–8.5, precipitation magnitude and intensity steadily rise throughout the century. The projected increase in precipitation magnitudes, intensity, and extreme events are highly correlated with the increasing spring and summer precipitation, linking intensified and heavy precipitation events during these seasons under all future scenarios. Cold climate indices are projected to decrease with a shortened frost season by 3.3 months, advance in spring freshet by 1.5 months under SSP5–8.5, and a drastic decline in cold spell duration index in all scenarios, indicating a lack of supercooling events. These decreasing indices are strongly correlated with warming temperatures with a Pearson correlation coefficient reaching 0.84 under SSP5–8.5. The findings also highlight the limitations of the CMIP6 ensemble in capturing extreme values, as extreme climate indices were not statistically significant. This study thus contributes to the broader understanding of climate dynamics and their potential impacts on cold regions.

Understanding the impact of Climate Variability (CV) on crop yield is crucial for developing sustainable agriculture practices, especially in regions vulnerable to climate change. This study aims to identify the causes of the observed decline in potato yield in Northern Finland by analyzing Remote Sensing data and statistical analysis on climatic variables from 2001 to 2020. First, the exception years with critical production (2004, 2006, 2008, 2012, 2015) were selected based on the anomaly in the annual potato yield. Then a variety of extreme indices based on precipitation and Land Surface Temperature occurrence and intensity during the growing season were calculated to find how much impact they have on potato yield. Principal Component Analysis was used to select the most significant ones among the extreme indices. Finally, through a multiple regression analysis, we found that extreme precipitation events and cumulative temperature explain around 48 % potato yield variations in which extreme precipitation (with 38 %) had much more impact than cumulative temperature (with 10 %). We concluded that one degree increase in cumulative temperature increases potato yield by 19.64 kg/ha and in contrast, heavy precipitation plays a negative role, i.e., one day increase in extreme precipitation events, decreases potato yield by 2085 kg/ha.

Advanced genome sequencing technologies have provided us with the opportunity to deeply understand the mechanisms underlying conditions associated with the genome. There has been significant interest recently in understanding the characteristics of de novo mutations, which are genetic changes that arise in reproductive cells and are not present in parents, as well as the mechanisms involved in their occurrence. These mutations can be transmitted to subsequent generations and have the potential to influence genetic diversity and susceptibility to diseases, making this topic important. Due to limited studies in this area, the formation mechanisms and characteristic features of such mutations have not yet been fully understood. Background/Aims: In this study, we aimed to conduct a comprehensive analysis of de novo mutations in families undergoing trio clinical exome sequencing analysis. The objectives of the study were to investigate the relationship between parental ages and the frequency of de novo mutations, the distribution, prevalence, relationships, and molecular characteristics of de novo mutations. Methods: A total of 69 families who underwent Trio Clinical Exome Sequencing (CES) analysis at the Department of Medical Genetics, Faculty of Medicine, Selçuk University, between January 1, 2017, and December 31, 2023, were included in the study. DNA samples extracted from peripheral venous blood of individuals were sequenced using the Roche CES kit and DNBSEQ-G400™ sequencing device, and a total of 3892 genes were analyzed using the Seq Platform. Results: After analysis, 407 de novo variants were identified, with the majority being variants of unknown significance (55.28%). When examining the base change profile, the most common changes were found to be C -> G, G -> A, A -> G. The most commonly mutated genes were found to be DSPP, HPS4, VCL, and BMP4 genes. Conclusions: Correlation analysis revealed no significant relationship between parental age and the number of de novo mutations, and regression analysis showed that age was not a significant parameter in determining the number of de novo mutations

Dust storms have been an increasing concern in the Middle East. Severe drought events and human activities, particularly water and land management, have led to emerging dust sources in the last few decades. This study combines spatio-temporal maps of land susceptibility to dust storm incidence with agricultural land use change data to examine the link between farming patterns and dust storm generation in the Tigris and Euphrates Basin from 2000 to 2021. Farmland and bare ground trends depend heavily on water availability, affecting land susceptibility to dust storms. We observed a direct connection between cropping regimes and high land susceptibility to becoming a dust source. Our analysis found no significant correlation between low to intermediate dust storm source (DSS) susceptibility and bare ground trends. However, we found a positive correlation between highly susceptible land and areas where bare ground showed an increasing trend, including the lands that were abandoned for more than 50% of the study period. Among the farming patterns, i.e. single and double cropping, single cropping is more prone to DSS occurrence, underscoring the importance of year-round vegetation cover and effective water management. The disturbed lands, particularly those abandoned post-cropping, show higher susceptibility to DSS incidence. Between 2008 and 2012, dust sources and land susceptibility increased substantially, alongside a significant rise in bare ground, possibly due to severe drought. We highlight cases where changes in farming patterns and land abandonment contribute to the increased or decreased susceptibility of land to being a DSS, as well as consistent susceptibility in the cases where there is no land use change. Given the broad geographical scope of the study, this research underscores the need for further investigation, combining field measurements with remote sensing to obtain a more detailed picture of the link between farming patterns, land abandonment, and dust storms.

In recent years, the effects of human activities and climate change on river flow patterns have become a major concern worldwide. This is particularly true in the southern Caspian Sea (SCS) region of Iran, where increasing water-intensive socio-economic development and climate change have significantly altered river flow regimes. To better understand these changes, this study employs two nonparametric methods, the modified Mann-Kendall method (MK3) and Innovative Trend Analysis (ITA), to examine spatial and temporal changes in hydrometeorological variables in the SCS. The study also evaluates the impact of human activities and climate change on river flow alteration using elasticity-based methods and the Budyko hypothesis in 40 rivers on the closest gauges to the Caspian Sea. The results indicate an alarming trend of increasing temperature, potential evapotranspiration, and decreasing river flows in the SCS region. In particular, human activities were found to be responsible for around 91.7 % of the change on average, resulting in a significant decline in inflow to the Caspian Sea by about 3216 MCM annually. This declining trend in inflow could potentially exacerbate the eutrophication conditions in the Sea and negatively impact its ecosystem and economics. Therefore, appropriate measures need to be taken to address these environmental and socio-economic issues in the southern Caspian Sea region.

Abstract Since spring discharge, especially in arid and semiarid regions, varies considerably in different months of the year, a time series of spring discharge observations is needed to determine the firm yield of the spring and the amount of water allocated to different needs. Because most springs are in mountainous and inaccessible areas, long-term observational data are often unavailable. This study proposes a probabilistic method based on bivariate analysis to estimate the discharge of the Absefid spring in Iran. This method constructed the bivariate distribution of the outflows of Absefid (AS) and Gerdebisheh (GS) springs using Copula functions. For this purpose, the fit of 11 different univariate distributions to the discharge data of each spring was tested. The results revealed that the GEV and log-normal distributions best fit the discharge data of GS and AS springs, respectively. In addition, among eight different copula functions, the Joe copula function was selected to construct the bivariate distribution of the discharge data of AS and GS springs. With the help of the created bivariate distribution and assuming a certain probability level, it is possible to estimate the discharge of Absefid spring based on the discharge of Gerdebisheh spring in a particular month. The estimated values of the discharge of the Absefid spring in the period from March 1993 to August 2022 show that with a probability of 90%, the lowest discharge of this spring is 600 L per second and occurred in June 2001. Therefore, to allocate the water from this spring for drinking purposes, this discharge value can be considered as the firm yield of this source. However, the amount of allocated water from this source should be determined by considering the ecological needs of the river downstream of this spring.

Abstract Introduction Telomeres protect the ends of chromosomes, and shorter leukocyte telomeres are associated with major group diseases. Maternal psychological stress may be related to the shortening of telomeres in infants. This systematic review and meta-analysis set out to consolidate the varying effect sizes found in studies of maternal psychological stress and telomere length (TL) in newborns and identify moderators of the relationship between stress during pregnancy and newborn TL. Methods Our systematic review was registered in Prospero. Six databases (PubMed, Scopus, Embase, PsycINFO, Web of Science, and CINAHL Complete) were searched for records in English from inception to February 10, 2023. Observational studies were included that measured the relationship of psychological stress of the mother during pregnancy on the TL of the newborn. The Newcastle–Ottawa quality assessment scale was used to assess the quality of the included studies. A random-effect model was selected. Statistical analysis performed by Stata software version 17. Results Eight studies were included for qualitative and four for quantitative analysis. There was an inverse statistically significant relationship between maternal stress and newborn TL; A one score increase in maternal psychological stress resulted in a 0.04 decrease in the TL of the newborn (B = -0.04, 95% CI = [-0.08, 0.00], p = 0.05). Selectivity analysis showed that the pooled effect size was sensitive to one study; After removing this study, the pooled effect size remained significant (B = -0.06, 95% CI = [-0. 10, -0.02], p

This research study investigates the impact of air temperature and precipitation on annual potato crop yield in Finland region and a local area in northern Finland. For this, the annual crop yield data of regional and local case study area is processed using Z-score normalization technique. Classification of computed z-score values was carried out into different classes ranging between the most beneficial crop yield year and the most vulnerable crop yield year. Later, the detection of feasible potato cropping season at monthly and daily scale was carried out using different weather parameters. Further, long-term trend analysis using Mann-Kendall's approach at annual, seasonal, and monthly scales was carried out using 60 years of dataset of both case study areas. Then after, the comparative analysis of annual crop yield and the characteristics obtained within climate data using different statistical approaches at annual, seasonal, and monthly scale. Finally, multivariate analysis was carried out to find most influential climate variables obtained using different statistical signatures. The results shows that, over the 100 years of period the annual potato crop yield of regional case study area shows a rising trend with declining area under potato crop. Classification approach found 16 % annual yield scored lowest Z-score while, 18% the highest. Likewise, 20 years of data for the local case study area found that 25 % of the dataset scored the highest Z-score and 15 % of the dataset values scored the lowest. Long-term trend analysis of air temperature shows significant increasing trend annually, seasonally and for monthly during the months between July-September. Whereas, similar procedure with the precipitation data showed increasing trend only at annual scale with the precipitation data analysis. During the comparative analysis between the annual crop yield data based on z-score classification and different statistical results obtained from weather parameters such as variation of precipitation and temperature sum, long-term climate data maximum-minimum totals seasonally as well as monthly during crop growing season; noticeable anomalies were observed in the weather parameters in line with the crop yield years grouped into the lowest and the highest Z-scores. The Multivariate analysis emphasized the impact of air temperature over precipitation on potato crop yield. Present study provides quantitative assessment on usefulness of long-term climate signatures for region specific either event-based or crop-based modelling development efforts to provide efficient decision support for enhancing farm-level crop productivity and sustainability of local and regional agriculture.

Climate change and anthropogenic activities have impacts on fish habitat suitability, demanding more accurate modeling of species abundance for effective conservation and management. In this study, we applied Machine Learning techniques to model the habitat-abundance relationship of juvenile Atlantic salmon (Salmo salar) in the Teno catchment in Finland and Norway. To capture the complexity and nonlinearity of the habitat-abundance relationship, we employed Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting (GB), and Support Vector Classification (SVC) and compared their performances. Among the regression models considered, those incorporating input variables such as substrate, shade, and vegetation demonstrate higher performance. Support Vector Regression yields the highest mean cross-validation score (R2 = 0.58), and Gradient Boosting produces the highest test score (R2 = 0.6) among the regression techniques. The mean cross-validation and test scores obtained for the classification models are notably higher compared to the regression models across all scenarios. A comparison between regression and classification results highlights the challenges of accurately modeling the habitat-abundance relationship. This study provides insights into the challenges and potential of machine learning techniques for juvenile Atlantic salmon habitat-abundance modeling in complex riverine habitat environments. The findings emphasize the importance of considering the limitations of machine learning models, particularly in ecological contexts, and the need for further research to address temporal variations and improve the precision of habitat-abundance modeling.

Sustainable water management measures are being developed to address the challenges posed by agriculture runoff and leaching on water resources. These measures are based on experts' opinions from various sectors and disciplines, ensuring that all stakeholders' perspectives are considered. For this, establishing a common understanding of 'sustainability' is essential to avoid misunderstandings, conflicts, and operational challenges. In this research, the Delphi survey technique was utilized to develop a definition of ‘sustainability’ in agricultural water management (SAWM) by considering the interdisciplinary group of experts from different parts of the world and those involved in a Horizon 2020 Research and Innovation Action. Twenty-six experts' perspectives on environmental, economic, and social dimensions of sustainability were assessed, and identified key concepts included climate change, water quality, water availability, stakeholder participation, capacity building, subsidies, and incentives. These concepts were used to define sustainability for multi/interdisciplinary project settings. The definition was validated with consortium members of the project in the regular consortium-wide meetings and used in the respective deliverables dealing with sustainability. The results serve as a foundation for communication between the involved actors and the project's definition of 'sustainability.' One recommendation from this work for broader policy formulation for SAWM in Europe is to prioritize farmer needs and focus on environmental sustainability. HIGHLIGHTS The research in agricultural water sustainability is essential to find pathways that optimize food production, limit water resource pollution, and promote sustainability of water management practices.; The absence of a common definition of sustainability can lead to miscommunication among partners due to varying interpretations resulting in ineffective collaboration, confusion, and a lack of coordination.; The Delphi survey technique is a powerful tool to capture diverse opinions from various experts in a complex discipline like "Sustainability".; Climate change, the environmental pillar of sustainability, and farmers as major stakeholders should be taken into prime focus when dealing with sustainable water management in agriculture.;

The COVID-19 pandemic has caused new conditions, problems, and different research platforms for qualitative research. The aim of the present study was to analyse the challenges and opportunities facing qualitative researchers during the COVID-19 pandemic in Iran. This qualitative research was conducted with a conventional content analysis approach with twenty-four Iranian health sciences researchers. The participants were selected by snowball and purposive sampling. Data collection was carried out using semi-structured face-to-face and online interviews until reaching saturation. Data analysis was also carried out using the Graneheim & Lundman approach in MAXQDA-2018 software, and to improve the trustworthiness of the results, Guba and Lincoln’s criteria were used. Data analysis led to the identification of two main categories, 13 subcategories, and 69 primary codes: The challenges were in areas such as data collection methods, access to participants and how to conduct interviews. Opportunities also included formation of new topics for qualitative research, highlighting the importance of qualitative research, strengthening the technological knowledge of researchers, research cost-effectiveness, and presenting further information on sensitive topics. It is also possible to strengthen qualitative research by supporting qualitative researchers at universities and research centres, facilitating the administrative processes, providing communication infrastructure such as suitable Internet in universities, ensuring more diversity in data collection methods, developing an appropriate protocol during the COVID-19 pandemic, and dedicating some university rooms to qualitative researchers to conduct interviews.

Abstract Heatwaves have had adverse affects on human life, ecosystems, and society. Global warming is expected to heighten the characteristics of heatwaves such as severity, duration, and frequency. Therefore, understanding the evolution of heatwaves is a central issue in climate change research with high relevance for society. Establishing a proper threshold for issuing a heatwave can be one of the most important issues in heatwaves studies, however, fewer studies focused on characterizing and modeling a heatwave threshold according to non‐stationary behavior, local geographic and physiographic characteristics. We have developed an applicable probabilistic framework to explore the heatwave events with different durations by applying appropriate thresholds. In this study, the proposed framework was applied to define the nonstationary frequency analysis of heatwaves models to account for the temporal trend caused by climate variability and change across Iran. The results showed that shorter heatwaves odds have been intensified more over Iran while longer heatwaves have not changed substantially. We find a substantial increase in heatwave hazard across Iran with a 40‐year available daily record, collectively from 1977 to 2019. The spatial distribution of the best non‐stationary models confirms the temporal evolution of heatwaves features due to global warming over Iran.

Abstract Extended periods of hydro-climate extremes with excessive or scarce rainfall associated with high or low temperatures have resulted in an imbalanced water cycle and inefficient socio-economic systems in several regions of Iran. However, there is a lack of comprehensive investigations on short-term to long-term variations in timing, duration, and temperature of wet/dry spells. This study bridges the current gap through a comprehensive statistical analysis of historical climatic data (1959–2018). Results indicated that the negative tendency of the accumulated rainfall (− 0.16/ − 0.35 mm/year during the past 60/30 years) in 2- to 6-day wet spells had made significant contributions to the ongoing downward trend in annual rainfall (− 0.5/ − 1.5 mm/year during the past 60/30 years) owing to a warmer climate condition. Warmer wet spells are likely responsible for precipitation patterns changes in snow-dominated stations since their wet spells temperature has more than threefold growth with increasing distance to coasts. The most detected trends in climatic patterns have started in the last two decades and become more severe from 2009 to 2018. Our results confirm the alteration of precipitation features across Iran due to anthropogenic climatic change, and suggest expected increase in air temperature would likely result in further dry and warm conditions over the coming decades.

This article aims to show that virtual water has historically been an adaptation strategy that enabled some arid regions to develop a prosperous economy without putting pressure on their scarce water resources. Virtual water is referred to as the total amount of water that is consumed to produce goods and services. As an example, in arid central Iran, the deficiency in agricultural revenues was offset by more investment in local industries that enjoyed a perennial capacity to employ more workers. The revenues of local industries weaned the population from irrigated agriculture, since most of their raw materials and also food stuff were imported from other regions, bringing a remarkable amount of virtual water. This virtual water not only sustained the region’s inhabitants, but also set the stage for a powerful polity in the face of a rapid population growth between the 13th and 15th centuries AD. The resultant surplus products entailed a vast and safe network of roads, provided by both entrepreneurs and government. Therefore, it became possible to import more feedstock such as cocoons from water-abundant regions and then export silk textiles with considerable added-value. This article concludes that a similar model of virtual water can remedy the ongoing water crisis in central Iran, where groundwater reserves are overexploited, and many rural and urban centers are teetering on the edge of socio-ecological collapse. History holds an urgent lesson on sustainability for our today’s policy that stubbornly peruses agriculture and other high-water-demand sectors in an arid region whose development has always been dependent on virtual water.

This study evaluated the comprehensive Water-Energy-Food-Carbon Nexus (WEFC) by focusing on energy assessment in northwest Iran. The energy evaluation indices for different products were calculated by estimating the total input and output energies. Multi-objective optimization based on five individual objectives and WEFC Nexus policies was used to identify the optimal land-use allocation of wheat, barley, rapeseed, and sugar beet, silage corn, and potato while minimizing water and energy consumption and CO2 emissions, and maximizing food production and profit. The results indicate that the suggested framework provides a practical methodology for determining the optimal land-use allocation considering quantitative WEFC Nexus. To increase economic efficiency and reduce energy consumption, agricultural practices and policy recommendations should be adopted, including promoting renewable energy sources, implementing energy-saving technologies, improving fertilizer management, improving crop rotation practices, conservation tillage, and improving water management and adoption of sustainable farming practices. The results allow policymakers to optimize multiple resources and recommend the best resource allocation under recommendation policy, technology, and constraints to achieve sustainable development in agriculture.

Study region: Once, the Tigris River (with its twin, the Euphrates) was the remarkable river in the west of Asia, making Mesopotamia a cradle of civilization thousands of years ago. Upstream anthropogenic activity has choked the Tigris River, the connecting lifeline across Iraq, and, due to droughts and desertification, caused the country to be plagued by poverty. Study focus: Here, we give a perspective on flow regime alteration in the main corridor of the Tigris River at five crucial points (Cizre, Mosul, Baiji, Baghdad, and Kut) before and after the planned water resources development in Turkey. Turkey’s Tigris River regulation goal is to generate about 7247 GWh of energy and irrigate over 640,000 ha of farmlands. New hydrological insights for the region: We reconstructed the natural flow along the Tigris River. In addition, to evaluate hydrological droughts, we proposed a modified streamflow drought index (MSDI) and compared it with the original streamflow drought index (SDI). The results show that the worst hydrological conditions could be found below the Samarra barrage in Iraq before the Tigris River regulation in Turkey. This negative hydrological condition will be extended to the whole corridor of the Tigris River in Iraq after the implementation of Turkey's goal. As a result, for example, Cizre and Mosul will experience extreme conditions in 37.5–87.5% of the years; this means a considerable reduction in the Mosul reservoire’s inflow (135–326 m3/sec). Consequently, some parts of Mosul's hydropower and reservoir capacity will be useless, and hydrological drought upstream of the Samarra barrage will be dominated.

The accumulation of pollutants in the sediment along surface water may negatively affect riparian zones and increase ecological risk. This article investigates the effects of metal sediments on riparian soil via field monitoring and ICP-OES analysis. To this end, pollution levels, seasonal changes, and potential sources of the pollutants were determined for the Melen River watershed, Turkey. The ecological statuses (contamination factor, enrichment factor, index of geo-accumulation, pollution index, modified pollution index, and potential and modified ecological risk indexes) of the watershed were also analyzed. Although no significant seasonal differences in the metal sediments were observed, their spatial distribution in the sediments and riparian soils varied markedly. Cr (11.4 to 136), Co (7.7 to 21.52), Cu (11.4 to 76.6), and Ni (14.06 to 128.2) recorded as mg/kg significantly increased from the upstream to the downstream. The metals possessing the highest risk in the sediment and riparian soil regarding the river health were Cu, Co, and Ni. The risk values were found to be heavily polluted (PI > 3 and MPI > 10), and the risk indexes were above the “desired environment without the risk”. The risk index was found to be more than 50, and the modified risk indexes exceeded 200 at many points. The transportation of pollutants in surface water became evident in the sediment, resulting in adverse effects on the riparian zone and the ecological system.

Abstract Urban development broadly impacts the hydrological cycle, leading to increased peak flow and flooding. Surface water detention ponds are among the most efficient measures for attenuating peak flow and returning it from development to pre‐development conditions. However, the major challenge is identifying optimal locations and cost‐effective designs for these ponds. This paper presents a new framework for identifying the best strategies for using detention ponds to control floods in urban drainage systems (UDS). The framework comprises a portfolio of simulation tools coupled with evolutionary optimisation and multi‐criteria decision analysis models. Hydraulic simulation of UDS is first modelled using SWMM and GIS tools. A multi‐objective optimisation model was used to find the optimal location and design for detention ponds. The compromise programming (CP) multi‐criteria decision‐making method was then used to prioritise potential best management solutions for detention ponds based on several sustainability criteria comprising economic, environmental, physiographic and social factors. The results identified the key features of potential detention ponds appearing in all multi‐objective optimal solutions that are useful for decision‐makers/designers when planning/designing for new detention ponds. The selected optimal pond strategies can significantly improve the UDS performance by decreasing flood damage between 66% and 90% at the cost of between $50,000 and $160,000.

The paper presents prominent Nordic contributions to stochastic methods in hydrology and water resources during the previous 50 years. The development in methods from analysis of stationary and independent hydrological events to include non-stationarity, risk analysis, big data, operational research and climate change impacts is hereby demonstrated. The paper is divided into four main sections covering flood frequency and drought analyses, assessment of rainfall extremes, stochastic approaches to water resources management and approaches to climate change and adaptation efforts. It is intended as a review paper referring to a rich selection of internationally published papers authored by Nordic hydrologists or hydrologists from abroad working in a Nordic country or in cooperation with Nordic hydrologists. Emerging trends in needs and methodologies are highlighted in the conclusions. HIGHLIGHTS Historical development in use of stochastic methods.; From stationarity to climate change impacts.; From univariate to multivariate problems.; From local to regional problems.;

The change in the global energy production mix towards variable renewable energy sources requires efficient utilization of regulated rivers to optimise hydropower operations meet the needs of a changing energy market. However, the flexible operation of hydropower plants causes non-natural, sub-daily fluctuating flows in the receiving water bodies, often referred to as ‘hydropeaking’. Drastic changes in sub-daily flow regimes undermine attempts to improve river system health. Environmental decision makers, including permitting authorities and river basin managers facing the intense and increasing pressure on river environments, should consider ecosystem services and biodiversity issues more thoroughly. The need for research innovations in hydropeaking operation design to fulfil both the water and energy security responsibilities of hydropower is highlighted. Our paper outlines optimized hydropeaking design as a future research direction to help researchers, managers, and decision-makers prioritize actions that could enable better integration of river science and energy system planning. The goal of this is to find a balanced hydropower operation strategy.

Study region: Iran Study focus: This study evaluated three satellite precipitation products, including PERSIANN-CCS and TRMM-3B42RT V7 (near real-time satellites) and CMOROH (post real-time satellite), on hourly, daily, monthly, and annual time scales in 52 synoptic stations over Iran. This study aims to evaluate the accuracy of satellite- precipitation products over different return periods and durations as well as their performance in different climates and altitudes. The Pearson’s correlation coefficient (Rp), Relative Root Mean Square Error (RRMSE), and Relative Bias (RBias) as well as three probability indices including Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were applied to evaluate the accuracy of these products. In addition, the sub-daily IDF curves (6, 12, 18, and 24 h) were derived to evaluate the studied satellites precipitation for 5, 10-, 20-, 50-, and 100-year return periods. New hydrological insights for the region: The results showed that the modification method could significantly improve all satellites' performance in precipitation estimation. The IDF curves derived from the CMORPH satellite as post real-time satellite precipitation product, showed the highest accuracy compared to synoptic stations. The TRMM and CMORPH underestimated precipitation by 56% and 8%, respectively, while PERSIANN-CCS overestimated precipitation by 143%. However, PERSIANN-CCS performed better in detecting the occurrence and non-occurrence of precipitation than other products. For Northeastern and Southwestern Iran, all products showed the same performance in accurately detecting occurrence and precipitation.

Background: Influenza vaccines based on conserved proteins are being developed persistently. The conserved protein vaccines based on Nucleoprotein (NP) are highly protected vaccines against influenza viruses that can be used as a Universal vaccine. Aluminum hydroxide (Alum) is the most common adjuvant used in vaccine formulation to improve immunization by altering the epitopes’ folds. However, due to its toxic effects on the nervous system, especially in infants and young children exposed to multiple vaccine injections during brain development, it is better to use more desirable options such as carbohydrate-based adjuvants. Sucrose ester (SE) is a carbohydrate and non-ionic surfactant that is compatible with the human body and environmentally friendly. This study evaluated the immunogenicity of recombinant NP molecule prepared in a prokaryotic with the accompaniment of sucrose ester adjuvant against lethal influenza virus challenge in a Balb/c mice model. Methods: The recombinant vector of PET-28a-NP was used to produce NP molecule. The vaccines containing an NP with or without Alum or sucrose ester adjuvants were injected into the mice. The Effectiveness and immunogenicity were examined by evaluating the humeral immunity induction by Immunoglobulin G (IgG), and its subunits production, and cellular immunity induction by Interferon-Gamma (IFN-γ) and Interleukin-4 (IL-4) production by ELISA Method and also animal’s surveillance was documented. The study took part at the Influenza and other respiratory viruses department of Pasteur institute of Iran in November 2018. Results: The animals’ surveillance in the Np group was 57.1%, NP+SE was (71.4%), and NP+SE was 64.28%. Also, IgG and its subunits, IL4, and IFN-γ production in both Alum and SE combined vaccines compared to NP alone were significant. Conclusion: In combination with the carbohydrate adjuvant containing sucrose ester compared to the formulation with alum adjuvant, the NP could provide proper and considerable protection and immunity against the homologous strain (H1N1) of the Influenza A virus. It is recommended that SE usage as an adjuvant results in an adequate immune response and less toxic effect.

In this study, the effect of antibiotic wastewater containing 20 common pharmaceuticals (14 antibiotics and 6 non-steroidal anti-inflammatory drugs (NSAIDs)) individually as well as their combination was investigated on activatedsludge in batch reactors. The chemical oxygen demand (COD), the ammonium concentration, the inhibition rate and toxicity index of COD and ammonium were investigated in wastewater. The inhabitation for COD and ammonium removal was variable for each drug so that the pharmaceuticals are applied simultaneously had such a greater adverse effect on inhibition rate than individual compounds. The pretreatment of wastewaters containing drugs was performed by powdered activated carbon PAC to reduce the adverse effect of these drugs on activated sludge. The appropriate method for separation of PAC from wastewater before introducing to activated sludge process and the optimized adsorption and contact time during the pretreatment process were studied. The pretreatment of pharmaceuticals wastewater with activated carbon improved well COD and NH4+ removal to 71 % and 55 %, respectively, that demonstrate the activated carbon can be considered as a suitable pretreatment option for the activated sludge.

Restoration and water table control on peatlands to limit fire risk are national priorities in Indonesia. The present study was initiated at Padang Island, Sumatra, to increase understanding on peatland hydrology in the tropic. At the pilot site, water table and precipitation were monitored at different stations. The results show variation in water table depths (WTDs) over time and space due to spatial and temporal variability in rain intensity and drainage networks. In part of the island, large-scale drainage for plantations led to deep WTD (−1.8 m) and high WTD recession rates (up to 3.5 cm/day). Around villages, farm-scale drainages had a smaller impact with a lower recession rate (up to 1.8 cm/day) and shallow WTD, typically below −0.4 m, the threshold for sustainable peatland management in Indonesia. The recession rates levelled off at 1.0 cm/day near the drained forest/plantation and at 0.5 cm/day near the farm. Deeper layers had much lower specific yield (Sy), 0.1 at −1.5 m depth, compared with top peat soils with Sy up to 0.3. Proximity to drainages extended discharge flow to deeper layers. The results highlighted the severity of peatland drainage impact on most coastal zones of Padang Island, which have intensive drainage networks. HIGHLIGHTS High spatial and temporal variability of water table was observed in Padang Island.; The variability was partially driven by variation in land use and farm drainages.; Recession rate near pulp plantations remained high (0.01 m/day) at −1.5 m depth.;

In recent years, the development of submerged membrane systems has led to the significant development of ultrafiltration/water purification markets. The study aimed to investigate the efficiency of Poly-Aluminum Chloride coagulant in removing turbidity using a submerged membrane reactor for simultaneous coagulation and flocculation of filtration and determine the optimal values of its performance parameters. In this study, the Poly-Aluminum Chloride coagulant along with lime and polyelectrolyte for water coagulation and flocculation was firstly evaluated by the Jar test in different turbidities. Also, pH (5-10), Poly-Aluminum Chloride (1-50 mg/L), and coagulant aids of lime (0.5-15 mg/L) and polyelectrolyte (0.1 to 2 mg/L) were examined. Then, a pilot-scale submerged membrane reactor was designed for coagulation, flocculation, and membrane filtration processes. Pilot experiments were used as closed systems, and then different parameters of flux, aluminum concentration in the treated water, and membrane fouling were investigated. Jar test results showed that Poly-Aluminum Chloride had a great performance in removing turbidity. In addition, the use of lime and polyelectrolyte coagulant aids improved the turbidity removal process by 3%. Furthermore, pH=8 was selected as the optimal range, and the best flux performance was obtained at turbidity less than 100NTU in a submerged membrane pilot. The flux reduction in eight hours of operation time was only 5% while this increased to 50% in turbidity above 200NTU. The turbidity removal percentages were reported to be constant and higher than 99.5%. The removal rate of total aluminum by the membrane process has been over 99%, and the type of membrane fouling is surface sediment and is reversible. Results indicated that the submerged membrane reactor along with coagulation and flocculation could be applied as an efficient method in water treatment with different turbidity.

Abstract Background Epilepsy is a neurological disorder from which almost 50 million people have been suffering. These statistics indicate the importance of epilepsy diagnosis. Electroencephalogram (EEG) signals analysis is one of the most common methods for epilepsy characterization; hence, various strategies were applied to classify epileptic EEGs. Methods In this paper, four different nonlinear features such as Fractal dimensions including Higuchi method (HFD) and Katz method (KFD), Hurst exponent, and L-Z complexity measure were extracted from EEGs and their frequency sub-bands. The features were ranked later by implementing Relieff algorithm. The ranked features were applied sequentially to three different classifiers (MLPNN, Linear SVM, and RBF SVM). Results According to the dataset used for this study, there are five classification problems named ABCD/E, AB/CD/E, A/D/E, A/E, and D/E. In all cases, MLPNN was the most accurate classifier. Its performances for mentioned classification problems were 99.91%, 98.19%, 98.5%, 100% and 99.84%, respectively. Conclusion The results demonstrate that KFD is the highest-ranking feature; In addition, beta and theta sub-bands are the most important frequency bands because, for all cases, the top features were KFDs extracted from beta and theta sub-bands. Moreover, high levels of accuracy have been obtained just by using these two features which reduce the complexity of the classification.

Arctic charr is one of the fish species most sensitive to climate change but studies on their freshwater habitat preferences are limited, especially in the fluvial environment. Machine learning methods offer automatic and objective models for ecohydrological processes based on observed data. However, i) the number of ecological records is often much smaller than hydrological observations, and ii) ecological measurements over the long-term are costly. Consequently, ecohydrological datasets are scarce and imbalanced. To address these problems, we propose jittered binary genetic programming (JBGP) to detect the most dominant ecohydrological parameters affecting the occurrence of Arctic charr across tributaries within the large subarctic Teno River catchment, in northernmost Finland and Norway. We quantitatively assessed the accuracy of the proposed model and compared its performance with that of classic genetic programming (GP), decision tree (DT) and state-of-the-art jittered-DT methods. The JBGP achieves the highest total classification accuracy of 90% and a Heidke skill score of 78%, showing its superiority over its counterparts. Our results showed that the dominant factors contributing to the presence of Arctic charr in Teno River tributaries include i) a higher density of macroinvertebrates, ii) a lower percentage of mires in the catchment and iii) a milder stream channel slope.

The aerobic wastewater treatments depend on the aeration. Hence, the size of the bubbles used in the aeration system may play a crucial role in this regard. This study attempted to investigate the effects of aeration bubble size on wastewater treatment efficiency of a “sequence batch reactor” (SBR) system at a laboratory scale using a novel designed fine/nanobubble forming instrumentation system. Based on the presence of microorganisms in the stationary phase, chemical oxygen demand removal efficiency on the 15th day (80.0 and 95.0%) was majorly better than on the 10th and 15th days in fine and nanobubble aeration systems. Moreover, with increasing sludge age, the “sludge volumetric index” (SVI) increased up to 170.0 ml g−1 on the 15th day. In addition, sludge rate and F/M ratio were much higher and expressively less in the nanobubble system rather than in the fine-bubbles system in which sludge was majorly denser. Therefore, the sludge was more easily deposited and the percentage of dry sludge was higher compared with the fine-bubble system. Thus, oxygen and specific oxygen uptake rate consumption were significantly reduced. The efficiency of the phosphorus removal was estimated to be between 54.0–60.0% for nanobubble aeration, compared to the general systems such as the SBR (10–20%) under similar conditions. In addition, the efficiency of the nitrogen removal in the nanobubble aeration system with different densities of 40.0, 50.0, and 60.0 ml g−1 was found as 99.0%, relatively higher compared to fine bubble with 96.0% nitrogen efficiency. In conclusion, a nanobubble aeration system could give considerably promoted efficiencies in all terms of the tested treatment effective parameters.