This study aims to develop an adaptable home energy management system capable of integrating the bidirectional smart charging of electric vehicles. The final goal is to achieve a user-defined objectives such as cost minimization or maximizing renewable self-consumption. Industrialwise, the present work yields valuable outcomes in identifying operational frameworks and boundary conditions. Optimal scheduling benefits both users and the electric network, thus enhancing grid utilization and increasing renewable energy integration. By coordinating power interactions with dynamic time-of-use tariffs, the energy management system minimizes user costs and aids the grid by cutting peak hour energy consumption. Charging and discharging operations in electric vehicles comply with energy level constraints outlined by bidirectional charging protocols. The proposed approach ensures the scheduling of cycles that minimize detrimental effects on battery health when evaluating an economically ageing mechanism. Compared to uncontrolled charging, optimal scheduling resulted in a significant reduction in the total operational cost of the dwelling. Trade-off conditions between renewable integration and potential savings are identified and numerically evaluated by means of multiobjective optimization. In contrast to scheduling-based models, the proposed architecture possesses the ability to iteratively adapt decision variables in response to system changes, thus responding effectively to external stochastic uncertainty. Full article

As a crucial basic natural resource, water resources are the cornerstone for sustainable national economic development. This paper takes the 2014 pilot water rights trading policy (WRT) as an entry point and uses a difference-in-differences (DID) model to test the policy effect of WRT on water-use efficiency (WUE) based on data for 30 Chinese provinces from 2005 to 2021. The study shows that WRT can significantly improve the regional WUE, and these results remain valid after a series of robustness tests, such as the parallel trend test, placebo test, and PSM-DID. Mechanistic analysis revealed that WRT can produce the Porter effect, which affects the WUE through technological innovation. The results of the heterogeneity analysis based on the synthetic control method (SCM) showed that WRT effectively improved WUE in Jiangxi, Henan, Ningxia, Hubei, and Guangdong, but did not achieve the expected effect in Inner Mongolia or Gansu. This paper provides solid empirical support for assessing the effectiveness of WRT and accelerating the process of establishing a unified national WRT market in China by 2025. Full article

In breeding programs, the demand for high-throughput phenotyping is substantial as it serves as a crucial tool for enhancing technological sophistication and efficiency. This advanced approach to phenotyping enables the rapid and precise measurement of complex traits. Therefore, the objective of this study was to estimate the correlation between vegetation indices (VIs) and grain yield and to identify the optimal timing for accurately estimating yield. Furthermore, this study aims to employ photographic quantification to measure the characteristics of corn ears and establish their correlation with corn grain yield. Ten corn hybrids were evaluated in a Complete Randomized Block (CRB) design with three replications across three locations. Vegetation and green leaf area indices were estimated throughout the growing cycle using an unmanned aerial vehicle (UAV) and were subsequently correlated with grain yield. The experiments consistently exhibited high levels of experimental quality across different locations, characterized by both high accuracy and low coefficients of variation. The experimental quality was consistently significant across all sites, with accuracy ranging from 79.07% to 95.94%. UAV flights conducted at the beginning of the crop cycle revealed a positive correlation between grain yield and the evaluated vegetation indices. However, a positive correlation with yield was observed at the V5 vegetative growth stage in Lavras and Ijaci, as well as at the V8 stage in Nazareno. In terms of corn ear phenotyping, the regression coefficients for ear width, length, and total number of grains (TNG) were 0.92, 0.88, and 0.62, respectively, demonstrating a strong association with manual measurements. The use of imaging for ear phenotyping is promising as a method for measuring corn components. It also enables the identification of the optimal timing to accurately estimate corn grain yield, leading to advancements in the agricultural imaging sector by streamlining the process of estimating corn production. Full article

This article presents the results of tests carried out to assess the condition of PP-modified concrete. The tests were carried out on samples previously stored at ambient temperature and exposed to temperatures corresponding to fire conditions—300 °C, 450 °C, and 600 °C. Axial compression tests of cube-shaped samples and three-point bending of beams were carried out. During strength tests, acoustic emission (AE) signals were recorded and the force and deformation were measured. Recorded AE events were clustered using the k-means algorithm. The analysis of the test results allowed for the identification of signals characteristic of the individual stages of the material destruction process. Differences in the methods of destruction of samples stored in ambient conditions and those exposed to fire temperatures were also indicated. While loading the samples, measurements were carried out using the digital image correlation (DIC) method, which enabled the determination of displacements. Based on the results of the laboratory tests, a numerical model was developed. The results obtained using different research methods (DIC and FEM) were compared. Tomographic examinations and observations of the microstructure of the tested materials were also carried out. The analyses carried out allowed for a reliable assessment of the possibility of using the acoustic emission method to detect destructive processes and assess the technical condition of PP-modified concrete. It was confirmed that the acoustic emission method, due to differences at low load levels, can be a useful technique for assessing the condition of PP-modified concrete after exposure to fire temperatures. So far, no research directions in a similar field have been identified. Full article

With the increasing concern about antimony (Sb) pollution and remediation in aquatic ecosystems, more and more feasible technologies have been developed. Adsorption has been extensively studied due to the simplicity of its operation and its minimal environmental effects, but the lack of cheap and stable adsorbents has limited its application in Sb treatment. In this study, pseudo-boehmite (PB) was successfully synthesized via aluminum isopropylate hydrolysis, and its potential for removing Sb(V) from wastewater was explored. The removal efficiency of Sb(V) was 92.50%, and the maximum adsorption capacity was 75.25 mg/g under optimal conditions (pH 5.0, 2 g·L⁻¹ PB, and 10 mg·L⁻¹ Sb(V)). In addition, better performance could be obtained at acidic conditions (pH 3.0–5.0). Surface complexation, electrostatic attraction, and hydrogen bonding were identified as potential major processes for Sb(V) elimination by PB based on experimental and characterization data. This study presents a promising approach for the efficient removal of Sb(V) from wastewater, offering a new insight into the application of aluminum-based materials for heavy metal removal. Full article

The measurement of the longitudinal rail profile is relevant to the condition monitoring of the rail infrastructure. The running surface is recognizable as a shiny metallic area on top of the rail head. The detection of the running surface is crucial for vehicle-based rail profile measurements, as well as for defect detection. This paper presents a methodology for the automatic detection of the running surface based on a laser profilometer. The detection of the running surface is performed based on the light reflected from the rail surface. Three rail surfaces with different surface conditions are considered. Supervised machine learning is applied to classify individual surface elements as part of the running surface. Detection by a linear support vector machine is performed with accuracy of >$90\%$. The lateral position of the running surface and its width are calculated. The average deviation from the labeled widths varies between $-1.2$$\mathrm{m}$$\mathrm{m}$ and $5.6$$\mathrm{m}$$\mathrm{m}$. The proposed measurement approach could be installed on a train for the future onboard monitoring of the rail network. Full article

This systematic review critically evaluates the impact of systemic treatments on outcomes and quality of life (QoL) in patients with RAS-positive stage IV colorectal cancer, with studies published up to December 2023 across PubMed, Scopus, and Web of Science. From an initial pool of 1345 articles, 11 relevant studies were selected for inclusion, encompassing a diverse range of systemic treatments, including panitumumab combined with FOLFOX4 and FOLFIRI, irinotecan paired with panitumumab, regorafenib followed by cetuximab ± irinotecan and vice versa, and panitumumab as a maintenance therapy post-induction. Patient demographics predominantly included middle-aged to elderly individuals, with a slight male predominance. Racial composition, where reported, showed a majority of Caucasian participants, highlighting the need for broader demographic inclusivity in future research. Key findings revealed that the addition of panitumumab to chemotherapy (FOLFOX4 or FOLFIRI) did not significantly compromise QoL while notably improving disease-free survival, with baseline EQ-5D HSI mean scores ranging from 0.76 to 0.78 and VAS mean scores from 70.1 to 74.1. Improvements in FACT-C scores and EQ-5D Index scores particularly favored panitumumab plus best supportive care in KRAS wild-type mCRC, with early dropout rates of 38–42% for panitumumab + BSC. Notably, cetuximab + FOLFIRI was associated with a median survival of 25.7 months versus 16.4 months for FOLFIRI alone, emphasizing the potential benefits of integrating targeted therapies with chemotherapy. In conclusion, the review underscores the significant impact of systemic treatments, particularly targeted therapies and their combinations with chemotherapy, on survival outcomes and QoL in patients with RAS-positive stage IV colorectal cancer, and the need for personalized treatment. Full article

Over the years, the tourism sector has constantly been a driving force in strengthening the Greek economy. Therefore, being capable of leveraging a tourism business’s performance can be of great importance in many aspects for destinations and destination management and marketing organizations (DMMOs). For this very purpose, this study’s methodology consists of a combined application of the key performance indicators and data envelopment analysis. The research conducted is quantitative, aiming to analyze the efficiency of the Greek hotels by region and determine the effective ones, as well as the strategic and managerial changes which should be considered by the non-effective. As a result, it shall become possible for each set of hotels to know the ideal turnover and the tourism nights spent that they should achieve, based on their current capacity in terms of beds and employees. Ultimately, this process could play a pivotal role in a region’s strategic planning, both from a resource management perspective, as well as in establishing an effective, measurable strategy that can be implemented by regional policy makers and destination managers in a real-time benchmarking process. Full article

This study delves into the integration of analytic hierarchy process (AHP) and geographic information system (GIS) techniques to identify suitable areas for urban development in six districts within the Mersin Metropolitan Area of Turkey. The specific aim is to generate an urban land use suitability map, in order to facilitate informed decision-making for urban development. Drawing on open Landsat satellite imagery and employing the random forest (RF) algorithm, the study spans a fifteen-year period, over which land use/land cover (LULC) changes are measured. Furthermore, a novel approach is introduced by incorporating the urban land use suitability map into an urban growth simulation model developed using a logistic regression (LR) algorithm. This simulation forecasts urban growth up to 2027, enabling planners to evaluate potential development areas against suitability criteria. Findings reveal spatial patterns of land suitability and projected urban growth, aiding decision-makers in selecting optimal areas for development while preserving ecological integrity. Notably, the study emphasizes the importance of considering various factors such as topography, accessibility, soil capability, and geology in urban planning processes. The results showcase significant proportions of the study area as being moderately to highly suitable for urban development, alongside notable shifts in LULC classes over the years. Additionally, the overlay analysis of simulated urban growth and land suitability maps highlights areas with contrasting suitability levels, offering valuable insights for sustainable urban growth strategies. By overlaying the urban land suitability map with a simulated LULC map for 2027, it is revealed that 2247.3 hectares of potential new urbanization areas demonstrate very high suitability for settlement, while 7440.12 hectares exhibit very low suitability. By providing a comprehensive framework for assessing urban land suitability and projecting future growth, this research offers practical implications for policymakers, urban planners, and stakeholders involved in Mersin’s development trajectory, ultimately fostering more sustainable and resilient urban landscapes. Full article

Environmental flow assessment is an essential tool in water resource management. This study employs a holistic approach to evaluate the environmental flow in the Yen Basin, Thanh Hoa, Vietnam. Based on information gathered from a field survey, the Yen River system is divided into five reaches, and environmental objectives and ecological assets are identified in each reach. Hydrological and hydraulic mathematical models are applied to simulate the flow regime in the river, demonstrating their potential to assess environmental flow, especially in basins with limited data. The detailed results from the mathematical model facilitate selecting environmental flow components to address specific objectives for each river reach. By analyzing and selecting the flow regime, this study aims to ensure environmental protection while also considering basin development requirements, laying the groundwork for defining prescribed flow regimes in basin water management. Full article

The Pressure Swing Adsorption (PSA) technique is a widely embraced automated method for gas separation within the industrial sector, prized for its operational simplicity and substantial economic benefits. In practice, the process typically involves the use of multiple towers to facilitate the completion of the PSA cycle. However, with the increasing number of towers in a PSA system, the intricacies of the cyclic process tend to amplify, posing challenges for novices attempting to grasp the mechanics of a six-tower PSA cycle. Utilizing animation can facilitate the process of comprehending these complex techniques by presenting them in a simplified and visually engaging format. Therefore, our research group has designed an animated depiction of a six-tower PSA device, predicated on the prototype established in our laboratory. This animation furnishes an inclusive demonstration of a complete cycle, encompassing twelve steps, pertaining to the operation of a six-tower PSA. It is our aspiration that this tool will prove advantageous for those who are embarking on the journey of understanding multi-tower PSA, as well as for seasoned professionals engaged in the field of pressure swing adsorption. Full article

The vast potential of high-resolution satellite images, including Kompsat-3A, has been demonstrated across diverse applications, such as mapping and disaster monitoring. However, these images can only be utilized as reliable GIS (geographic information system) data when they possess precise geographical information. To achieve this, sensor model information, represented by RPCs (rational polynomial coefficients), requires bias compensation through GCPs (ground control points). Though having a substantial number of well-distributed GCPs across satellite images is ideal, the acquisition process is often restricted due to cost and inaccessibility. The uniform distribution of GCP chips is not guaranteed, necessitating an investigation into the impact of GCP distribution on the bias compensation process, which is the focus of this study. Experiments were meticulously conducted using Kompsat-3A data using dense GCP information. The dense GCP information was automatically generated from aerial orthoimages through a three-step process. Firstly, the GCP chips were extracted from the aerial images, focusing on feature points. Secondly, these chips were projected onto the target Kompsat-3A data to align them accurately. Lastly, precise satellite image coordinates of the chips were obtained through image matching between the chips and the target Kompsat-3A image. The dense GCPs enabled detailed bias analysis that exhibited skewness in most Kompsat-3A data. This necessitates the implementation of an affine model for proper bias compensation over the entire image space. Next, the study delved into the influence of GCP distribution on RPC bias compensation. To this end, each target satellite image space was divided into nine zones, with the dense GCPs assigned accordingly. The accuracy of bias compensation was analyzed across nine experimental cases, ranging from GCPs occupying only one zone to GCPs covering all nine zones. It was observed that GCPs covering at least four or five zones should be utilized for reliable RPC bias compensation of Kompsat-3A, especially when aiming for a high level of accuracy with an RMSE of one pixel. Finally, it was concluded that GCPs covering three zones yielded satisfactory results as a minimum GCP requirement, but this was contingent upon their distribution not following a straight zone pattern. Full article

This comprehensive review explores the application and impact of digital twin (DT) technology in bolstering the reliability of Floating Offshore Wind Turbines (FOWTs) and their supporting platforms. Within the burgeoning domain of offshore wind energy, this study contextualises the need for heightened reliability measures in FOWTs and elucidates how DT technology serves as a transformative tool to address these concerns. Analysing the existing scholarly literature, the review encompasses insights into the historical reliability landscape, DT deployment methodologies, and their influence on FOWT structures. Findings underscore the pivotal role of DT technology in enhancing FOWT reliability through real-time monitoring and predictive maintenance strategies, resulting in improved operational efficiency and reduced downtime. Highlighting the significance of DT technology as a potent mechanism for fortifying FOWT reliability, the review emphasises its potential to foster a robust operational framework while acknowledging the necessity for continued research to address technical intricacies and regulatory considerations in its integration within offshore wind energy systems. Challenges and opportunities related to the integration of DT technology in FOWTs are thoroughly analysed, providing valuable insights into the role of DTs in optimising FOWT reliability and performance, thereby offering a foundation for future research and industry implementation. Full article

In the Industry 4.0 era of smart grids, the real-world problem of blackouts and cascading failures due to cyberattacks is a significant concern and highly challenging because the existing Intrusion Detection System (IDS) falls behind in handling missing rates, response times, and detection accuracy. Addressing this problem with an early attack detection mechanism with a reduced missing rate and decreased response time is critical. The development of an Intelligent IDS is vital to the mission-critical infrastructure of a smart grid to prevent physical sabotage and processing downtime. This paper aims to develop a robust Anomaly-based IDS using a statistical approach with a machine learning classifier to discriminate cyberattacks from natural faults and man-made events to avoid blackouts and cascading failures. The novel mechanism of a statistical approach with a machine learning (SAML) classifier based on Neighborhood Component Analysis, ExtraTrees, and AdaBoost for feature extraction, bagging, and boosting, respectively, is proposed with optimal hyperparameter tuning for the early discrimination of cyberattacks from natural faults and man-made events. The proposed model is tested using the publicly available Industrial Control Systems Cyber Attack Power System (Triple Class) dataset with a three-bus/two-line transmission system from Mississippi State University and Oak Ridge National Laboratory. Furthermore, the proposed model is evaluated for scalability and generalization using the publicly accessible IEEE 14-bus and 57-bus system datasets of False Data Injection (FDI) attacks. The test results achieved higher detection accuracy, lower missing rates, decreased false alarm rates, and reduced response time compared to the existing approaches. Full article

C-terminal Src kinase (CSK) is the major inhibitory kinase for Src family kinases (SFKs) through the phosphorylation of their C-tail tyrosine sites, and it regulates various types of cellular activity in association with SFK function. As a cytoplasmic protein, CSK needs be recruited to the plasma membrane to regulate SFKs’ activity. The regulatory mechanism behind CSK activity and its subcellular localization remains largely unclear. In this work, we developed a genetically encoded biosensor based on fluorescence resonance energy transfer (FRET) to visualize the CSK activity in live cells. The biosensor, with an optimized substrate peptide, confirmed the crucial Arg¹⁰⁷ site in the CSK SH2 domain and displayed sensitivity and specificity to CSK activity, while showing minor responses to co-transfected Src and Fyn. FRET measurements showed that CSK had a relatively mild level of kinase activity in comparison to Src and Fyn in rat airway smooth muscle cells. The biosensor tagged with different submembrane-targeting signals detected CSK activity at both non-lipid raft and lipid raft microregions, while it showed a higher FRET level at non-lipid ones. Co-transfected receptor-type protein tyrosine phosphatase alpha (PTPα) had an inhibitory effect on the CSK FRET response. The biosensor did not detect obvious changes in CSK activity between metastatic cancer cells and normal ones. In conclusion, a novel FRET biosensor was generated to monitor CSK activity and demonstrated CSK activity existing in both non-lipid and lipid raft membrane microregions, being more present at non-lipid ones. Full article

The anterior maxilla is challenging regarding aesthetic rehabilitation. Current bone augmentation techniques are complex and 3D-printed bioceramic bone grafts can simplify the intervention. Aim: A four-teeth defect in the anterior maxilla was reconstructed with a 3D-printed synthetic patient-specific bone graft in a staged approach for dental implant delivery. Methods: The bone graft was designed using Cone-Beam Computed Tomography (CBCT) images. The bone graft was immobilized with fixation screws. Bone augmentation was measured on CBCT images at 11 days and 8 and 13 months post-surgery. A biopsy sample was retrieved at reentry (10 months post-augmentation) and evaluated by histological and micro-computed tomography assessments. The definitive prosthesis was delivered 5 months post-reentry and the patient attended a visit 1-year post-loading. Results: A total bone width of 8 mm was achieved (3.7 mm horizontal bone gain). The reconstructed bone remained stable during the healing period and was sufficient for placing two dental implants (with an insertion torque > 35 N·cm). The fractions of new bone, bone graft, and soft tissue in the biopsy were 40.77%, 41.51%, and 17.72%, respectively. The histological assessment showed no signs of encapsulation, and mature bone was found in close contact with the graft, indicating adequate biocompatibility and suggesting osteoconductive properties of the graft. At 1-year post-loading, the soft tissues were healthy, and the dental implants were stable. Conclusions: The anterior maxilla’s horizontal ridge can be reconstructed using a synthetic patient-specific 3D-printed bone graft in a staged approach for implant placement. The dental implants were stable and successful 1-year post-loading. Full article

Strong-flavor Daqu, as a fermentation agent, plays a significant role in shaping the quality of strong-flavor baijius, and fungal species in Daqu are important factors affecting the quality of Daqu. Therefore, we selected strong-flavor Daqu from seven different origins to study the fungal composition and the effects of the fungal composition on the physicochemical properties and volatile organic compounds (VOCs). It was found that the fungal composition influences the physicochemical properties of Daqu. Specifically, there was a positive link between Rhizomucor, Rhizopus, Thermomyces, and liquefying activity and a positive correlation between Aspergillus and fermenting activity. Furthermore, the relationships between esterifying activity and Thermomyces, Rhizomucor, Aspergillus, Pichia, and Saccharomycopsis were found to be positive. The VOCs in Daqu were affected by Aspergillus, Issatchenkia, Pichia, and Thermoascus. Issatchenkia was significantly positively correlated with benzeneethanol as well as Aspergillus and pentadecanoic acid ethyl ester, ethyl myristate. Pichia and Thermoascus were significantly negatively correlated with benzaldehyde and 2-furaldehyde. This study deepens our understanding of the relationship between VOCs, the physicochemical properties with microbial communities, and reference significance for the production of better-quality strong-flavor Daqu. Full article

The goal of this study was to apply the principles of analytical quality by design (AQbD) to the analytical method for determining the radiochemical purity (PQR) of the radiopharmaceutical sodium iodide ¹³¹I oral solution, utilizing thin-layer chromatography (TLC) with a radio–TLC scanner, which also enables the evaluation of product quality. For AQbD, the analytical target profile (ATP), critical quality attributes (CQA), risk management, and the method operable design region (MODR) were defined through response surface methodology to optimize the method using MINITAB^® 19 software. This study encompassed the establishment of a control strategy and the validation of the method, including the assessment of selectivity, linearity, precision, robustness, detection limit, quantification limit, range, and the stability of the sample solution. Under the experimental conditions, the method parameters of the TLC scanner were experimentally demonstrated and optimized with an injection volume of 3 µL, a radioactive concentration of 10 mCi/mL, and a carrier volume of 40 µL. Statistical analysis confirmed the method’s selectivity for the ¹³¹I iodide band Rf of 0.8, a radiochemical impurity IO₃⁻ Rf of 0.6, a linearity from 6.0 to 22.0 mCi/mL, and an intermediate precision with a global relative standard deviation (RSD) of 0.624%. The method also exhibited robustness, with a global RSD of 0.101%, a detection limit of 0.09 mCi/mL, and a quantification limit of 0.53 Ci/mL, meeting the prescribed range and displaying stability over time (at 0, 2, and 20 h) with a global RSD of 0.362%, resulting in consistent outcomes. The development of a method based on AQbD facilitated the creation of a design space and an operational space, with comprehensive knowledge of the method’s characteristics and limitations. Additionally, throughout all operations, compliance with the acceptance criteria was verified. The method’s validity was confirmed under the established conditions, making it suitable for use in the manufacturing process of sodium iodide ¹³¹I and application in nuclear medicine services. Full article

An energy-intensive industry such as cement manufacturing requires a constant supply of high amounts of traditional fossil fuels, such as coal or gas, for the calcination process. A way to overcome this fuel need is the usage of solid waste or Alternative Fuel Resources (AFRs), such as wood or paper. An advantage of using such waste is that their combustion byproduct, “ash”, can be used as a raw material alternative in the cement manufacturing process. However, for structural reasons, only bucket elevator technology is feasible to convey the fuel vertically for feeding the calciner in most cement plants. During the fuel feeding process, the inhomogeneous characteristics of AFRs lead to discharge parabolas of these materials varying over the infeed sample. Hence, a need arises to observe these trajectories and estimate a method for their optimal discharge. Thus, the purpose of this study is to develop an intelligent high-performance bucket elevator system. As such, a vision-based reinforcement learning algorithm is proposed in this study to monitor and control the speed of the elevator depending on the material properties observed at the inlet. These inlet materials properties include the type of material used in the simulation, and the particle size distribution within the infeed sample. A relationship is established between the inlet material properties and the speed of the bucket elevator. The best possible scenario is then deduced using a reward function. Here, the reward function is formulated via the deep learning image segmentation algorithm, a novel approach. After observing the test simulation conducted with a random-parameters setup, it was noted that the optimum speed for a given infeed sample was predicted correctly. As such, it can be concluded that the goal of developing an intelligent bucket elevator system was achieved. Full article

Anthropogenic climate change is increasing the occurrence of wildfires, especially in northern high latitudes, leading to a shift in land surface climate. This study aims to determine the predominant climatic effects of fires in boreal forests to assess their impact on vegetation composition, surface albedo, and snow dynamics. The influence of fire-induced changes on Earth’s radiative forcing is investigated, while considering variations in burn severity and postfire vegetation structure. Six burn sites are explored in central Alaska’s boreal region, alongside six control sites, by utilizing Moderate Resolution Imaging Spectroradiometer (MODIS)-derived albedo, Leaf Area Index (LAI), snowmelt timing data, AmeriFlux radiation, National Land Cover Database (NLCD) land cover, and Monitoring Trends in Burn Severity (MTBS) data. Key findings reveal significant postfire shifts in land cover at each site, mainly from high- to low-stature vegetation. A continuous increase in postfire surface albedo and negative surface shortwave forcing was noted even after 12 years postfire, particularly during the spring and at high-severity burn areas. Results indicate that the cooling effect from increased albedo during the snow season may surpass the warming effects of earlier snowmelt. The overall climate impact of fires depends on burn severity and vegetation composition. Full article

Theranostics define diagnostic evaluations directing patient-specific therapeutic decisions. Molecular theranostics involves genomic, transcriptomic, proteomic, metabolomic and finally phenonic definitions thyroid cancer differentiation. It is the functional differentiation that determines the sensitivity and accuracy of RAI imaging as well as the effectiveness of RAI treatment. Total thyroidectomy is performed to empower an anticipated RAI treatment. A preoperative determination of the genomic and transcriptomic profile of the tumor is a strong predictor of response to therapeutic interventions. This article discusses the oncopathophysiologic basis of the theranostic risk stratification approach. Full article

Nitrate pollution is a major environmental problem threatening rivers, and nitrogen and oxygen isotopes have proved to be an effective means of analyzing the sources and transformations of nitrate in rivers. However, a low monitoring frequency cannot accurately reflect the changes in nitrate. In this study, the sources and transformations of nitrate in the middle reaches of the Yellow River and its tributaries during the dry season and the wet season were analyzed based on water quality parameters and nitrate isotopes. Stable isotope analysis conducted using the R (SIAR) model was used to estimate the proportions of different nitrate sources. The results showed that the main nitrate sources in the main stream were soil nitrogen (40.95–45.83%) and domestic sewage and manure (30.93–32.60%), respectively, with little variation between the dry season and wet season because of the large flow of the Yellow River. During the dry season, the nitrate sources of the two tributaries were mainly domestic sewage and manure (45.23–47.40%), followed by soil nitrogen (31.35–34.00%). However, the primary nitrate source of T2 (Qin River) became soil nitrogen (40.05%) during the wet season, a phenomenon that was mainly caused by the significant increase in river discharge and in soil erosion in the basin. During the wet season, the concentrations of total nitrogen (TN) and nitrate (NO₃⁻) significantly decreased in the main stream and tributaries, and nitrification and denitrification processes occurred in both the main stream and tributaries of the Yellow River. In addition, the T2 tributary (Qin River) was also significantly affected by mixed dilution. High-frequency sampling can reflect the isotopic information of nitrate in the river more comprehensively, which helps us to understand the conversion process of nitrate more accurately. Full article