University of Mohaghegh Ardabili

The temporal changes in river flow patterns are crucial for understanding how environmental, climatic, and human factors influence water availability and ecosystem health. The role of regulating dams in influencing river flow regimes is particularly significant, as dams can alter natural flow patterns, affecting downstream ecosystems and communities. The objective of this study was to investigate the impacts of dam construction on temporal changes in river flow patterns in the permanent rivers of the Urmia Lake Watershed using Colwell’s Indices (CIs). To achieve this, the daily flow data of the rivers have been utilized and Colwell’s Indices (Predictability, Constancy, and Contingency) have been calculated and statistically compared using paired t-test at monthly and seasonal scales. Analysis of the daily flow data before and after the construction of the dam revealed a decrease in both the maximum and mean daily flow rates. The Band Urmia station experienced the most significant reduction in average flow after the construction of the Shahrchai dam, with a notable difference of 2.71 cm. Comparing the post-dam construction showed an increase in most of Colwell’s Indices on a monthly and seasonal scales. The Predictability and Constancy indices showed an increase across all river gauge stations. Among the stations analyzed, the Yalghuz Aghaj station exhibited the most significant increase in Predictability and Constancy. Specifically, there was a remarkable increase in Predictability from 0.263 to 0.575, and in Constancy from 0.091 to 0.423. Furthermore, the Contingency index increased at almost all stations after dam construction. The paired t-test results showed significant increases in predictability and constancy post-dam, especially at Nazar Abad and Yalquz Aghaj. Predictability and constancy increased most at Yalquz Aghaj (mean difference 0.39, and 0.46 respectively, P < 0.000), and contingency showed modest changes. As a concluding remark, Colwell’s Indices provide a means to measure and analyze various components of modified patterns of permanent river regimes. Therefore, it is crucial to make management decisions that consider the fluctuations in the river flow regime, with a specific focus on preserving the sustaining river flow. This study suggests a comprehensive analysis of dam impacts on flow indices, enhancing understanding of river hydrology and extending previous methods using Colwell’s indices.

A wide range of catalytic techniques have been explored for the use of biomass components. For example, the electrocatalytic oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA) can be performed...

Pulses and legumes are essential crops in global agriculture and human nutrition for their high protein and fiber content. Pulses, like chickpeas, lentils, and beans, are rich in plant-based nutrition. They are becoming more widely recognized for their grant to robust and nourishing food systems. Gene editing holds significant promise for improving seed quality in pulses by precisely modifying genes associated with key agronomic traits, nutritional composition, and stress tolerance. Gene editing can improve the protein content of legume seeds by altering genes involved in protein synthesis and accumulation, thereby optimizing nutritional quality and addressing specific dietary requirements. It can also increase yield potential by improving plant architecture, flowering time, pod development, and seed size. Gene editing can maximize nitrogen fixation efficiency and decrease dependency on synthetic fertilizers. It can also enhance plant defense mechanisms, reduce yield losses due to diseases and insect pests, and develop stress-tolerant legume varieties.

With the increase in population and the increase in demand for food, increasing the yield of crops is one of the biggest challenges facing mankind. More production of crops requires more use of fertilizers and pesticides, which leads to increased production costs, reduction of soil quality toward acidity and salinity, environmental damage by leaching of nutrients and accumulation in surface water and changing the ecosystem, as well as pollution of the air. Therefore, increasing the production of crops in the limited resources of land currently used for agriculture requires innovative methods to produce a healthier crop for human consumption and safer for the environment on the one hand, and on the other hand, by reducing water and energy consumption and cost. Many transcription factors and regulatory gene networks collaborate during nutritional deprivation to uphold nutrient homeostasis. Enhancing the Nutrient Use Efficiency (NUE) is crucial for achieving sustainable output with improved quality. This review presents prospective targets appropriate for genome editing to improve our understanding and the performance of NUE. The various techniques for utilizing essential negative and positive regulators in genome editing are also explained. Potential targets for genome editing are negative regulators of nutrient signaling, which can enhance nutrient absorption and stress signaling in resource-limited settings. The CRISPR/dCas9 method provides an additional benefit by utilizing transcriptional activators and repressors to increase the expression of specific genes of interest selectively. Utilizing CRISPR/Cas technology to generate nutrient-efficient plants would accelerate the genetic enhancement of crop tolerance to nutrient stress and promote the sustainability of agricultures.

Diagnosing cancer as one of the main causes of death in the world in its early stages can be very effective in its treatment. Photonic crystal-based biosensors are optical sensors that have recently attracted attention due to their many advantages. In this paper, a ternary photonic crystal-based biosensor is designed and investigated considering the practical limitations. The sensing mechanism of the cancer sensor in the proposed structure is based on the change in the analyte’s refractive index, which leads to a change in the transmission spectrum. Incident light with transverse electric polarization was used. The sensor’s performance was checked by changing the number of periods and the angle of the incident light. The optimal values were selected to have the maximum efficiency of the sensor. Finally, for this sensor, sensitivity equal to 692.8 nm ⁄RIU, full width at half maximum equal to 0.271 nm, figure of merit equal to 2561.5 RIU− 1, and quality factor more than 5870 were obtained, which showed a significant improvement compared to similar works. This work establishes a benchmark for ternary photonic crystal-based biosensors, offering a robust, cost-effective, and precise solution for cancer detection and potential applications in broader diagnostic fields.

The current systematic review aimed to analyse studies on the concurrent validity and reliability of microelectromechanical devices for measuring intense running and peak speed performance. A systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, using EBSCO, PubMed, Scielo, Scopus, SPORTDiscus and Web of Science. Keywords and synonyms were entered in various combinations in the title, abstract, or keywords: (“Global positioning system” OR “Global Navigation Satellite System” OR “GPS”) AND (Validity OR Accuracy OR Reliability OR Precision OR Repeatability OR Reproducibility OR Consistency) AND (“sprint” OR “peak speed” “top seed” OR “maximal speed”). The risk of bias was assessed using the Appraisal tool for Cross-Sectional Studies. From 839 studies, 20 were systematically analysed. It was found that 16 global positioning system (GPS) models were considered valid and 12 were considered reliable for measuring intense running and/or peak speed performance. Intense running performance in GPS with lower sampling rate (e.g. ≤ 5 Hz) acquisition demonstrated reduced validity and reliability in nonlinear movement patterns as well as movement intensity increases. Some limitations of the evidence, including the conditions associated with exercise testing and the benchmark and device used, varied between studies. In addition, the data of the algorithms used by GPS can affect the interpretation of the results. Thus it would be advisable to use higher sampling rates.

Background: Today, computer games have become one of the most popular forms of entertainment, especially among teenagers. While games may have various benefits, video games are shown to have different consequences for players, especially those who are younger, and can be highly addictive. The present research investigated the effect of computer game addiction on anxiety and depression in adolescents with the mediating role of social support. Methods: Overall, 304 adolescents aged 12–18 years old living in Tehran were included in the research through a convenient method. The required data were collected using the Trait-state Anxiety Questionnaire, Depression Scale, Social Support Questionnaire, and Computer Game Addiction Questionnaire and then analyzed using the structural equation model in AMOS software. Results: The results revealed that addiction to computer games had a significant effect on anxiety and depression. In addition, social support could act as a mediator in this relationship and reduce the harmful effects of computer game addiction on anxiety and depression. Discussion: According to the findings, to reduce anxiety and depression related to computer game addiction, it is necessary to pay attention to the improvement of social support for people through providing appropriate treatment plans, informing family and friends, and strengthening social connections and support networks. Conclusion: It is suggested that appropriate treatment programs be designed and implemented to reduce anxiety and depression in individuals with computer game addiction. These programs could include time management, behavior modification, enhancement of communication and social skills, and the provision of adequate social support through families, friends, and professional communities.

This paper presents the design of a multi-beam reflectarray antenna sensor for medical and biosensing applications. The design incorporates a microstrip antenna with a rectangular graphene patch to feed the reflectarray antenna. This array antenna includes 76 rectangular graphene sheets placed beneath a ${{\rm SiO}_2}$ substrate and atop an analyte substrate layer for environmental sensing. The key innovation lies in the creation of a directional multi-beam antenna. By adjusting the graphene’s chemical potential, the antenna can radiate in multiple directions, enhancing channel capacity. The reflection spectra are obtained for several graphene chemical potentials, and the refractive index of the structure’s sensing layer is in the range of 1.1–1.6. The antenna operates at a specific frequency band between 1.03 and 2.38 THz, at best, equal to 79% of the fractional bandwidth. It is shown that a sensitivity of 0.18 THz/RIU is achieved at a refractive index of 1.5 and a chemical potential of state 2.

Identifying the optimal formulation is essential for achieving health benefits, preserving texture, and enhancing the flavor of baked goods. This study examined the effects of aqueous cinnamon extract (Cinnamomum zeylanicum) at concentrations of 0.05%, 0.10%, 0.15%, 0.20%, and 0.25% (W/V) on the antioxidant activity, physicochemical, textural, and sensory properties of oil cakes enriched with these extracts. HPLC analysis of the aqueous extract identified cinnamaldehyde as the dominant compound (30.5%), along with significant amounts of eugenol, cinnamic acid, and coumarin. The results showed that increasing the cinnamon extract concentration enhanced TPC, TTC, %RSA, and %FRAP values. The pH of the cake samples did not significantly differ across concentrations (p < 0.05). The moisture content was higher than the control, but water activity decreased with higher extract concentrations. The 0.25% sample showed significant differences in protein content compared to the control, 0.05%, and 0.10% samples (p < 0.05). Fat and carbohydrate contents were generally lower than the control. TPA results showed decreased hardness, cohesiveness, resilience, and fracturability with higher cinnamon extract levels. Additionally, increased extract levels improved the springiness of the cakes. The 0.20% and 0.25% samples had the highest overall consumer acceptability. The study found that samples containing 0.20% and 0.25% cinnamon extract were the most effective concentrations for oil cakes. This indicates that aqueous cinnamon extract, with its antioxidant properties, can serve as a beneficial additive to enhance the quality of oil cakes.

In this study, 60 cherry samples with native varieties were selected from the Hir region in Ardabil province. They were classified into four growth stages, including before the optimal harvest date, the day before the optimal harvest time, the optimal harvest time, and after the optimal harvest date, by a panel of human experts. Next, by combining the feature selection method (relief) and the spectrometry method (vis-NIR), the effective wavelengths were extracted to estimate the soluble solid content (SSC) values and firmness of the cherry product. In the continuation of the process of this method, a list of inputs was formed, and by applying the life cycle assessment method, the environmental effects of the process of estimating SSC values and cherry hardness in the presence of tests and obtained data was performed. In the final stage, with the help of the radial basis function neural network method, a relationship was established between the reflection intensity values in the effective wavelengths and the endpoint effects of the life cycle assessment to estimate the environmental effects. It was found that the radial basis function neural network could estimate the environmental effects of the experimental process with an acceptable accuracy (over 95% on average).

Alpha-fetoprotein (AFP) is an important early-stage biomarker for hepatocellular carcinoma. However, detecting low concentrations of AFP remains challenging using conventional techniques. This work reports a highly sensitive plasmonic biosensor platform leveraging emerging two-dimensional (2D) materials to improve surface plasmon resonance (SPR) detection limits. The biosensor consists of black phosphorus (BP) and silicon heterostructures on Al-Ni metal layers, supporting the propagation of surface plasmon polariton waves. Using an optimized Kretschmann configuration and thickness tuning of the BP-Si-metal stack, a high bulk refractive index sensitivity of 480 deg/RIU and FOM of 96 is achieved. The three-dimensional finite-difference time-domain (FDTD) numerical approach was used to validate the results. Testing with AFP concentrations, in sensing medium, from 25 to 100 ng/ml shows the sensor can reliably detect ultra-low concentrations, highlighting the potential for early diagnosis of hepatocellular carcinoma. Additionally, the 2D BP-enabled sensor provides > 86.7% better sensitivity than graphene-based SPR platforms.

A green synthetic method has been developed for producing novel rhodanine-based hybrid derivatives. Initially, rapid synthesis of 5-alkoxycarbonylmethylidene-1,3-thiazolidine-4-one derivatives 1a-1d was achieved by reacting N,N-disubstituted thioureas with dialkyl acetylene dicarboxylates under catalyst-free conditions at room temperature, resulting in excellent yields (90–95%). Subsequently, the reaction between compounds 1a-1d and primary amines 2a-2e in the presence of carbon disulfide was carried out under similar catalyst-free conditions, yielding novel imidazolidinone-rhodanine hybrid derivatives 4a-4h with good to excellent yields (72–92%). Graphical abstract

Nanofertilizersplay a keyrole in augmenting plant’s stress-tolerance. As an integral part of contemporary agricultural practices, nanofertilizers exhibit unique properties at the nanoscale, influencing plant responses to diverse stressors such as drought, salinity, and nutrient deficiencies. Nanofertilizers have the ability to improve plant uptake and utilization of nutrients, as well as their ability to withstand abiotic stressors. They can also act as a carrier for the delivery of other beneficial compounds, such as pesticides and fungicides. Through a comprehensive exploration of the current state of research and practical applications, this chapter elucidates the underlying mechanisms by which nanofertilizers enhance stress tolerance. The discussion encompasses molecular and physiological changes, shedding light on nanofertilizers’ potential to optimize nutrient utilization efficiency, fortify antioxidant defenses, and modulate stress-responsive gene expression. Furthermore, the chapter evaluates the environmental implications and sustainability considerations associated with nanofertilizer deployment, offering insights into the future trajectory of this innovative approach in promoting resilient crop production.

In this work, the optoelectronic response of Al/p‐Si photodiodes (PDs) with and without (PVP:Gr‐ZnTiO3) composite interlayer is investigated in dark and under various light intensities (P). The manufacturing/surface preparation is thoroughly explained. The electric/optic parameters including leakage/saturation current (I0), series/shunt resistances (Rs/Rsh), barrier height (BH), ideality factor (n), energy‐dependent density distribution of surface/interface levels (Nss), photoinduced current (Iph), photosensitivity (S), optical responsivity (R), and specific detectivity (D*) are calculated from the I–V data in dark and under illumination intensities. Raising the light intensity results in a drop in ΦB0 and Rs quantities while increasing the I0 and n values due to photogenerated electron–hole pairs under illumination. The ΦB0‐P and ΦB0‐n graphs are used to calculate the illumination factor and the ΦB0 in the ideal form. An acceptable linear behavior appears in the Iph–P profiles for the negative‐bias region, where the illumination dependence of photocurrent is explored. It is found that the (PVP:Gr‐ZnTiO3) interlayer leads to an increase in the S, R, and D* values of the PD to ≈1200, 400 mA W⁻¹, and 1.14 × 10¹⁴ Jones, respectively. These results show that the used (PVP:ZnTiO3) interlayer displays an excellent photoresponse and may effectively replace conventional PDs for applications in optoelectronic and photovoltaic devices.

A new technique has been developed to identify ACL tears in sports injuries. This method utilizes a Convolutional Neural Network (CNN) in combination with a modified Political Optimizer (IPO) algorithm, resulting in a major breakthrough in detecting ACL tears. The study provides an innovative approach to detecting this type of injury. The CNN/IPO approach surpasses traditional optimization techniques, ensuring precise and timely detection of ACL tears. This breakthrough has the potential to significantly improve treatment results, enabling clinicians to intervene promptly and effectively, leading to enhanced recovery and rehabilitation for athletes. The integration of the CNN and IPO algorithm provides clinicians with an unparalleled level of accuracy and efficiency in identifying ACL tears, facilitating more precise and tailored treatment strategies for sports-related injuries. The findings have the potential to revolutionize the way medical professionals approach musculoskeletal injuries, enhancing overall well-being and athletic performance. The research’s significance extends beyond sports medicine, illuminating new avenues for the detection and management of ACL tears, and paving the way for advancements in sports injury diagnosis and treatment.

In this paper, we will study some thermodynamic features and phase structure of charged AdS black holes in deformed Jackiw–Teitelboim (dJT) gravity. We find the values of temperature, entropy and electric charge at the critical inflection points of the corresponding solutions. In addition, we compute the heat capacity as thermal stability parameter along with the expansion coefficient and isothermal compressibility as thermodynamic response functions in dJT model. It is shown that they are divergent at the critical points of the isocharge curves and satisfy the Ehrenfest’s equations which discloses this fact that the phase transition at the critical points is of second order. In the context of thermodynamic geometry, we also compute the state scalar curvature, R, of these black holes following three practical methods; Weinhold, Ruppeiner and New thermodynamic geometry. This provides more insights into the behavior and significance of the scalar curvature near the critical points of charged AdS black holes in dJT theory, analogous to that for conventional critical phenomena.

This study investigates the synergistic implementation of nanophotonic and plasmonic structures to enhance the efficiency of perovskite solar cells (PSCs). The research focuses on integrating periodic grating nanostructures and plasmonic nanoparticles (NPs) to improve light harvesting in ultra-thin PSCs. Finite-difference time-domain (FDTD) simulations were employed to optimize the geometric parameters of circular and square gratings and silver core–shell nanoparticles. The results demonstrate that combining optimized gratings and plasmonic NPs significantly increases light absorption and photocurrent generation. The proposed structure, incorporating circular gratings and Ag@SiO2 core–shell NPs, achieved a remarkable photocurrent of 25.24 mA/cm², compared to 18.8 mA/cm² for the bare structure. This substantial improvement is attributed to the synergistic effects of extended optical path length from grating-induced light trapping and localized surface plasmon resonances from the NPs. The study provides valuable insights into designing and optimizing high-efficiency, ultra-thin perovskite solar cells, paving the way for their commercial viability and contributing to sustainable energy solutions.

This study presents a novel pseudospin-polarized waveguide with closed boundaries, designed using complementary metasurfaces with dual surface impedances. By enforcing electromagnetic duality, the proposed structure establishes mirror reflection symmetry, significantly reducing backscattering and ensuring robust one-way wave propagation. The waveguide effectively suppresses backward-propagating modes, even in the presence of bends and structural discontinuities, making it a highly stable and efficient platform for guided-wave applications. With an ultra-wide operating bandwidth spanning 7–350 GHz, the waveguide exhibits exceptional isolation levels exceeding − 0.5 dB, ensuring minimal signal loss. To achieve precise performance predictions, we employ a rigorous variational method to calculate the surface impedance of the metasurfaces, enhancing the accuracy of analytical and numerical results. Leveraging these unique propagation characteristics, we design a high-performance ultra-wideband filter based on complementary split-ring resonators. It offers strong stopband attenuation with minimal insertion loss. This makes the proposed filter an excellent candidate for next-generation microwave and millimeter-wave systems, including wireless communications, radar, and high-frequency signal processing. By integrating pseudospin physics with electromagnetic duality, this work establishes a new paradigm in waveguide design, demonstrating how complementary metasurfaces can enable low-loss, broadband, and highly efficient unidirectional wave propagation for advanced electromagnetic applications.

Deforestation is a significant environmental concern of the present century. This issue has received serious attention from global and regional communities due to its relationship with various environmental issues such as climate change, erosion, water quality, and biodiversity. Concerns about deforestation in arid and semi-arid countries, such as Iran, are quite tangible since it confronted with a shortage of forest resources on the one hand and acute issues caused by flood and erosion hazards on the other hand. The Talesh forests in the north of Iran, which are a manifestation of the ancient Hyrcanian forests with huge ecological reserves, is exposed to forest loss due to the expansion of human activities such as agriculture, wood harvesting, livestock grazing, and mining, despite the implementation of watershed management plans and forest conservation. The conservation and restoration of these forest ecosystems necessitate knowledge of the location and rate of deforestation, as well as its driving factors, through a systemic and interdisciplinary approach that has not yet been taken into account. By using an ecogeomorphic approach to model the deforestation event, we attempted to investigate the link between the ecological process of deforestation and geomorphological processes by combining the spatial terrain analysis with the statistical logistic regression. Given the approach in deforestation modeling, we were able to explain the effects of both physical and anthropogenic factors on deforestation only by incorporating physical variables (geomorphology), which can easily be derived from available digital elevation models (DEMs). First, we succeeded in mapping deforestation points in 12 catchments over 32 years using Landsat images acquired in 1991 and 2022 through change detection technique. The results of the assessment of negative changes in forest cover from 1991 to 2022 showed that about 90 km² (4.5% of the total area of catchments) has been deforested. The percentage of deforestation area varied from 7.7% in Haviq catchment to 1.8% in Dinachal catchment. We used the spatial logistic regression model to explain the relationship between geomorphological variables and deforestation probability, since the model is the most efficient predictive model to gather a group of independent variables of different natures without the need for their normal distribution. Geomorphologically independent variables included altitude, slope, topographic position index (TPI), northness, eastness, plan curvature, profile curvature, length of slope (LS) factor, slope length, topographic wetness index (TWI), contributing area, distance to stream, and terrain ruggedness index. The results of logistic regression analysis by revealing the direction of multivariate relationships showed that the probability of forest loss is higher in such places: low altitude and valleys, low slopes, divergent flow points, convex surface, downstream section, flat areas with homogeneous, and dry zones with low moisture. In addition, determining the intensity of the relationships between the independent variables and the dependent variable through regression test showed that the variables of slope, altitude, and ruggedness index with coefficients of β equal to − 2.82, − 2.1, and 1.92, respectively, are among the most important variables explaining deforestation. In contrast, the variables of eastness, northness, distance from the river, and slope length with coefficients of β equal to − 0.000017, − 0.000031, and − 0.000124, respectively, were identified as the insignificant variables in explaining the deforestation and were excluded from the final prediction model. Furthermore, the results of evaluating the efficiency of the logistic regression model through pseudo-R² (0.19) and relative operating characteristic (0.75) statistics indicated a good fit and an acceptable agreement between the actual map and the predictive map of deforestation. However, the use of more accurate and high-quality DEMs with different spatial resolutions was recommended for future studies. Regional, urban, and rural policymakers and planners should pay attention to the geomorphic environments that have a high probability of deforestation based on the results of this study. The need for more care and protection is evident in these areas, and any human interference in them must be done consciously and in accordance with environmental sustainability principles. Graphical Abstract