Search Results (60)

In this work, we propose a knowledge-aware approach for Arabic automatic question generation (QG) that leverages the multilingual T5 (mT5) transformer augmented with a pre-trained Arabic question-answering model to address challenges posed by Arabic’s morphological richness and limited QG resources. Our system generates both subjective questions and multiple-choice questions (MCQs) with contextually relevant distractors through a dual-model pipeline that tailors the decoding strategy to each subtask: the question generator employs beam search to maximize semantic fidelity and lexical precision, while the distractor generator uses top-k sampling to enhance diversity and contextual plausibility. The QG model is fine-tuned on Arabic SQuAD, and the distractor model is trained on a curated combination of ARCD and Qudrat. Experimental results show that beam search significantly outperforms top-k sampling for fact-based question generation, achieving a BLEU-4 score of 27.49 and a METEOR score of 25.18, surpassing fine-tuned AraT5 and translated English–Arabic baselines. In contrast, top-k sampling is more effective for distractor generation, yielding higher BLEU scores and producing distractors that are more diverse yet remain pedagogically valid, with a BLEU-1 score of 20.28 establishing a strong baseline in the absence of prior Arabic benchmarks. Human evaluation further confirms the quality of the generated questions. This work advances Arabic QG by providing a scalable, knowledge-aware solution with applications in educational technology, while demonstrating the critical role of task-specific decoding strategies and setting a foundation for future research in automated assessment. Full article

The present study investigates the extent and spatial distribution of metal concentration in stream sediments that flow into Keban Dam Lake, Turkey. Sediment samples were analysed for trace and potentially toxic elements (PTEs), including V, Cr, Co, Ni, Cu, Zn, Pb, Tl, Th, and U. Enrichment Factor (EF), Contamination Factor (CF), Geo-accumulation Index (Igeo), and Pollution Load Index (PLI) were employed to assess contamination levels. Results reveal that Cr exhibited very high enrichment (EF = 15.95) in downstream urban samples, while Cu and Zn showed high enrichment in samples collected from the middle to lower reaches of the stream, probably indicating anthropogenic contributions. Most other elements, such as Pb, Tl, Th, and U, were within natural background levels. Sediment Quality Guidelines (SQGs) indicate that Cr, Ni, and Cu may pose potential ecological risks, especially in samples from urban-influenced and downstream areas where concentrations exceed the Probable Effect Levels (PEL; Cr: 160 mg/kg, Ni: 42.8 mg/kg, Cu: 108 mg/kg). Multivariate statistical analyses, including Pearson correlation and hierarchical clustering, reveal three distinct geochemical groupings. Among these, the most contaminated cluster—corresponding to midstream and downstream regions—is characterized by elevated Cu and Zn concentrations. Strong correlations among Cu–Zn, Ni–Cu, and Th–U suggest there is a combination of anthropogenic and lithogenic sources for most metals. While most sites showed low to moderate pollution, urban downstream locations exhibited significant metal accumulation, necessitating the region’s continued environmental monitoring and management strategies. Full article

The question generation system (QGS) for information technology (IT) education, designed to create, evaluate, and improve Multiple-Choice Questions (MCQs) using knowledge graphs (KGs) and large language models (LLMs), encounters three major needs: ensuring the generation of contextually relevant and accurate distractors, enhancing the diversity of generated questions, and balancing the higher-order thinking of questions to match various learning levels. To address these needs, we proposed a multi-agent system named Multi-Examiner, which integrates KGs, domain-specific search tools, and local knowledge bases, categorized according to Bloom’s taxonomy, to enhance the contextual relevance, diversity, and higher-order thinking of automatically generated information technology MCQs. Our methodology employed a mixed-methods approach combining system development with experimental evaluation. We first constructed a specialized architecture combining knowledge graphs with LLMs, then implemented a comparative study generating questions across six knowledge points from K-12 Computer Science Standard. We designed a multidimensional evaluation rubric to assess the semantic coherence, answer correctness, question validity, distractor relevance, question diversity, and higher-order thinking, and conducted a statistical analysis of ratings provided by 30 high school IT teachers. Results showed statistically significant improvements (p < 0.01) with Multi-Examiner outperforming GPT-4 by an average of 0.87 points (on a 5-point scale) for evaluation-level questions and 1.12 points for creation-level questions. The results demonstrated that: (i) overall, questions generated by the Multi-Examiner system outperformed those generated by GPT-4 across all dimensions and closely matched the quality of human-crafted questions in several dimensions; (ii) domain-specific search tools significantly enhanced the diversity of questions generated by Multi-Examiner; and (iii) GPT-4 generated better questions for knowledge points at the “remembering” and “understanding” levels, while Multi-Examiner significantly improved the higher-order thinking of questions for the “evaluating” and “creating” levels. This study contributes to the growing body of research on AI-supported educational assessment by demonstrating how specialized knowledge structures can enhance automated generation of higher-order thinking questions beyond what general-purpose language models can achieve. Full article

This study evaluated heavy metal (HM) contamination in sediments from the Malbasag River in the Ormoc City port, Leyte, Philippines. A total of thirty sediment samples were collected randomly from ten locations along the river using an Ekman grab sampler. Atomic absorption spectrophotometry revealed HM concentrations in the order of Mn > Zn > Cu > Ni > Pb > Cd. All HMs exceeded their sediment quality guideline (SQG) thresholds except for Mn. Contamination was assessed using indices such as the contamination factor (CF), pollution load index (PLI), geo-accumulation index (I_geo), and enrichment factor (EF). The CF values indicated “moderate to considerable” contamination for Zn, Ni, and Cd, while Cu and Pb showed “very high” contamination levels. The PLI results indicated severe sediment degradation in 20% of samples. The I_geo analysis classified 60% of the samples as “heavily to extremely polluted” for Cd, Cu, and Pb. EF analysis suggested that anthropogenic sources contributed to elevated HM levels, including port activities and agricultural runoff. Ecological risk index (RI) analysis revealed moderate risk in 40% and considerable risk in 20% of sampling locations. Multivariate analyses suggested significant anthropogenic contributions to HM contamination, highlighting the need for further studies to assess the ecological impacts. Full article

The hourly L2-level chlorophyll-a (CHL-a) concentration spatial energy spectra of GOCI-II from 2021 to 2023 are employed to investigate the characteristics of the CHL-a spatial energy spectrum slopes in three regions of the East China Sea, namely nearshore, offshore, and open ocean. The seasonal trends of the spatial energy spectrum slopes are also examined for the nearshore and offshore regions. It is observed that the slopes of the CHL-a spatial energy spectrum are −2 at scales larger than 5 km, whereas at smaller scales, they are −5/3, −1, and −0.3 from the nearshore region to the open sea, respectively. On the larger scales, the spatial energy spectrum slopes are consistent with surface quasi-geostrophic (sQG) theory, but this is not the case on smaller scales. An insufficient regional CHL-a concentration leads to a flattening of the slope at the smaller scales. On the submesoscale, the slope of the nearshore CHL-a concentration spatial energy spectrum is steeper in summer and flatter in winter, a pattern that contrasts with changes observed offshore. This seasonal variation is attributed to the southward flow of ZheMin Coastal Current (ZMCC) during winter, which carries freshwater and enhances the horizontal buoyancy gradient in the nearshore region. Full article

Heavy metal contamination in soil is a global issue threatening human health and ecosystems. Accurate spatial maps of heavy metals (HMs) are vital to mitigating the adverse effects on the ecosystem. This study utilizes GIS and multivariate analysis to evaluate HMs in agricultural soils from Al Ghat Governorate, Saudi Arabia, analyzing Al, As, Co, Cr, Cu, Fe, Mn, Ni, Pb, V, and Zn using ICP-AES in 35 soil samples. Methods included contamination factor (CF), enrichment factor (EF), risk index (RI), geoaccumulation index (Igeo), pollution load index (PLI), soil quality guidelines (SQGs), and multivariate analysis. The soils, characterized by sandy texture, low organic matter, and alkalinity due to arid conditions and high calcium carbonate, had the following HM concentrations (mg/kg) in descending order: Fe (11,480) ˃ Al (7786) ˃ Mn (278) ˃ Zn (72.37) ˃ Ni (28.66) ˃ V (21.80) ˃ Cr (19.89) ˃ Co (19.00) ˃ Cu (12.46) ˃ Pb (5.46) ˃ As (2.69). EF, CF, and Igeo suggest natural sources for most HMs, predominantly from the sedimentary sequence, with localized Zn, Pb, Co, Mn, and Cu enrichment linked to mixed natural and agricultural influences. PLI and RI indicated acceptable contamination levels, posing no ecological risk. All samples fell below SQG thresholds for As, Cu, Pb, and Cr, confirming minimal ecological threat. Statistical analysis highlighted sedimentary cover as the primary HM source, with agricultural activities contributing to Co, Cu, Ni, and Pb levels. Full article

In this paper, we used Fourier Neural Operator (FNO) networks to solve reaction–diffusion equations. The FNO is a novel framework designed to solve partial differential equations by learning mappings between infinite-dimensional functional spaces. We applied the FNO to the Surface Quasi-Geostrophic (SQG) equation, and we tested the model with two significantly different initial conditions: Vortex Initial Conditions and Sinusoidal Initial Conditions. Furthermore, we explored the generalization ability of the model by evaluating its performance when trained on Vortex Initial Conditions and applied to Sinusoidal Initial Conditions. Additionally, we investigated the modes (frequency parameters) used during training, analyzing their impact on the experimental results, and we determined the most suitable modes for this study. Next, we conducted experiments on the number of convolutional layers. The results showed that the performance of the models did not differ significantly when using two, three, or four layers, with the performance of two or three layers even slightly surpassing that of four layers. However, as the number of layers increased to five, the performance improved significantly. Beyond 10 layers, overfitting became evident. Based on these observations, we selected the optimal number of layers to ensure the best model performance. Given the autoregressive nature of the FNO, we also applied it to solve the Gray–Scott (GS) model, analyzing the impact of different input time steps on the performance of the model during recursive solving. The results indicated that the FNO requires sufficient information to capture the long-term evolution of the equations. However, compared to traditional methods, the FNO offers a significant advantage by requiring almost no additional computation time when predicting with new initial conditions. Full article

Baiyangdian Lake, recognized as the largest freshwater body in northern China, plays a vital role in maintaining the regional eco-environment. Prior studies have pointed out the contamination of sediments with heavy metals, raising concerns about eco-environmental challenges. Therefore, it is imperative to evaluate the current pollution levels and ecological threats related to heavy metals found in the sediments of Baiyangdian Lake as well as in its inflow rivers. In May 2022, surface sediments with a depth of less than 20 cm were analyzed for Cu, Zn, Pb, Cr, Ni, As, Cd, and Hg to determine the pollution status, identify sources of pollution, and evaluate potential ecological risks. A range of evaluation methods used by predecessors such as geo-accumulation index (I_geo), enrichment factor (EF), ecological risk index (RI), sediment quality guidelines (SQGs), positive matrix factorization (PMF), absolute principal component score-multiple linear regression model (APCS-MLR), chemical mass balance (CMB), and UNMIX model were analyzed. After comparison, multi-methods including the geo-accumulation index (Igeo), absolute principal component score-multiple linear regression model (APCS-MLR), ecological risk index (RI), and sediment quality guidelines (SQGs) were utilized this time, leading to a better result. Findings reveal that pollution levels are generally low or non-existent, with only 1.64% of sampling sites showing close to moderate pollution levels for Cu, Pb, and Zn, and 4.92% and 1.64% of sites exhibiting close to moderate and moderate pollution levels for Cd, respectively. The main contributors to heavy metal presence are pinpointed as industrial wastewater discharge, particularly Cu, Zn, Pb, Cd, and Hg. The ecological risks are also relatively low, with 4.92%, 1.64%, and 1.64% of sampling sites demonstrating close to moderate, moderate, and strong risks in the inflow rivers, respectively. Additionally, only one site shows moderate potential biological toxicity, while the rest display non-toxicity. These findings will update our cognition and offer a scientific basis for pollution treatment and ecosystem enhancement for government management. Full article

Improving the production capacity of natural gas hydrates (NGHs) is crucial for their commercial development. Based on the data of the first on-site testing production of NGHs in the Shenhu Sea area, numerical methods were used to analyze the production behavior of radial lateral well (RLW) and horizontal snake well (HSW) with different completion lengths when they deployed at different layers of the Class-1 type hydrate reservoir (with a fixed pressure difference of 6 MPa and continuous production for 360 days). The results indicate that compared with the single vertical well production, RLW and HSW can effectively increase production capacity by enlarging drainage area and the productivity is directly proportional to the total completion length. The RLW and HSW deployed at the three-phase layer (TPL) have optimal mining performance within a 360-day production period. Different to the previous research findings, during a short-term production period of 360 days, regardless of the deployment layer, the overall production capacity of HSW is better than RLW’s. The total gas production of HSW-2 circles well type is about four times that of a single vertical well, reaching 1.554 × 10⁷ ST m³. Moreover, the HSW-1 lateral well type stands out with an average Q_g of 3.63 × 10⁴ ST m³/d and a specific production index J of 16.93; it has the highest J-index among all well types, which means the best mining efficiency. It is recommended to choose the HSW-1 circle well type, if the coiled tubing drilling technique is used for on-site testing production of NGHs in the future. The research results provide insights into the potential applications of RLW and HSW in this sea area. Full article

Enhancing the production capacity of natural gas hydrates (NGHs) is critical for its commercial development. Complex structure wells may efficiently increase drainage areas while enhancing exploitation efficiency. Based on the field data of China’s first offshore NGH test production, the numerical method was used to analyze the production performance of different complex structure well types by continuous depressurization production for 360 days under the preconditions of fixed effective completion length of 300 m and a pressure difference of 6 MPa. Results indicated that the complex structure well types deployed at the three-phase layer demonstrated superior production performance within 240 days of production; the DLW2 and HW2 well types stood out, with an average gas production rate Q_g reaching 43,333 m³/d and a specific production index J of 24.1. After 360 days of production, benefiting from multi-layer combined production, the Cluster vertical well deployed at the multi-layer had the best production performance, with an average Q_g of 34,444 m³/d and a J-index of 19.1. The research results provided insights into the complex structure well-type selection strategy for NGH depressurization in this sea area. Full article

Protein tyrosine phosphatases (PTPs) are pivotal contributors to the development of type 2 diabetes (T2DM). Hence, directing interventions towards PTPs emerges as a valuable therapeutic approach for managing type 2 diabetes. In particular, PTPN6 and PTPN9 are targets for anti-diabetic effects. Through high-throughput drug screening, quercetagitrin (QG) was recognized as a dual-target inhibitor of PTPN6 and PTPN9. We observed that QG suppressed the catalytic activity of PTPN6 (IC₅₀ = 1 μM) and PTPN9 (IC₅₀ = 1.7 μM) in vitro and enhanced glucose uptake by mature C2C12 myoblasts. Additionally, QG increased the phosphorylation of adenosine monophosphate-activated protein kinase (AMPK) and insulin-dependent phosphorylation of Akt in mature C2C12 myoblasts. It further promoted the phosphorylation of Akt in the presence of palmitic acid, suggesting the attenuation of insulin resistance. In summary, our results indicate QG’s role as a potent inhibitor targeting both PTPN6 and PTPN9, showcasing its potential as a promising treatment avenue for T2DM. Full article

Eighteen organochlorine pesticides (OCPs) in soil samples from the Changchun central urban area, Northeast China were analyzed using accelerated solvent extraction combined with gas chromatography/mass spectrometry (ASE-GC/MS) for the purpose of elucidating their contamination status, distribution characteristics, influencing factors, and feasible dangers in this city region. The complete concentrations of OCPs ranged from 15.63 to 92.79 ng/g, with a geomean of 36.46 ng/g. Hexachlorocyclohexane(HCHs), dichlorodiphenyltrichoroethane (DDTs), and chlordanes were the most dominant OCPs, with γ-HCH and p,p′-DDT being the predominant isomers. Higher concentrations of OCPs often centered to the northeast and southwest of the Changchun metropolis, and these artificial influences contributed to the destiny of OCPs in the soils. The residues of OCPs were derived from the historic utility of the technological DDT, dicofol, and lindane. A Pearson’s correlation evaluation indicated that TOC was once a key factor controlling OCP accumulation. The ecological risk evaluation based on the soil quality guidelines (SQGs) advises that the presence of DDTs, lindane, and heptachlor may additionally pose a poisonous ecological danger to soil organisms. The contrast outcomes of the incremental lifetime cancer risk (ILCR) confirmed that the highest cancer risk of OCPs to the posed populace was once low, whilst some unique areas with excessive OCP residues ought to be given attention. The research results provide basic information for evaluating the extent of OCP pollution in the soil of major cities in Northeast China and can help authorities establish environmental protection regulations and soil remediation techniques. Full article

In surficial sediments of Lake Piediluco, a small, riverine, regulated and heavily modified water body in the Central Italian Apennines, contamination by persistent organochlorine pollutants (POPs) was assessed. During spring and autumn, six representative points were investigated. Reflecting a substantial zonation of pollution within this aquatic ecosystem, concentrations were found to vary from site to site. OCPs, particularly DDT and its metabolites DDE and DDD, were detected at varying frequencies and concentrations from 0.301 to 8.185 ng/g d.w., whilst total PCBs (Σ50 congeners) were from 0.570 to 10.206 ng/g d.w. Although both PCB congener-specific and homolog patterns suggest a prevalent presence of Aroclors 1254 and 1260, a more limited likely contribution of 1248 technical mixture is not to be excluded. In the western area of the lake, affected daily by continuous basin water remixing for hydroelectricity production, major seasonal differences in OCP concentrations were found. Conversely, the eastern area was typified by low seasonal fluctuation and small variation among sites. Regardless of either collection site or seasonality, polychlorinated-p-dioxin and furan (PCDD/Fs) contamination were below 8.3 pg WHO-TEQ/g. In contrast to the present study, POP pollution from PCBs, PCDD/Fs and some DDT-derived pollutants has not been investigated so far. Nevertheless, the concentrations are typical of low-polluted or pristine area lakes and are consistently lower than those of other Italian lakes of greater size and depth (e.g., Como, Garda and Maggiore). The physical and chemical properties of investigated analytes are more consistent with probable diffuse point source contamination originating from the catchment area, rather than from atmospheric depositions by regional or long-range transports. Finally, according to the international sediment quality guidelines (SQGs), Piediluco sediments pose a low risk to sediment-dwelling organisms and, more generally, to the wildlife of such aquatic ecosystems. Full article

This study examined the spatio-temporality of heavy metal concentrations (Al, Cd, Co, Cr, Fe, Mn, Ni, Pb and Zn) in the sediments of Lake Bafa, one of the most important wetlands of Turkey’s Aegean region. The study evaluated sediment quality according to threshold effect concentration (TEC) and probable effect concentration (PEC) values based on sediment quality guidelines (SQG), and provided a potential ecological risk assessment (PERI) along with indices such as geoaccumulation index (NI_geo), enrichment factor (EF), contamination factor (CF), and pollution load index (PLI). For this purpose, surface sediment from 10 different points and core samples from three different points were seasonally collected and the concentrations of nine heavy metals were determined by ICP-MS. The findings indicated the following accumulation order of heavy metals in the sediment: Fe > Al > Mn > Ni > Cr > Zn > Pb > Co > Cd, with concentrations of Al, Mn, and Ni being high in the surface sediment samples. According to the NI_geo, surface sediment and core samples were very slightly polluted with Cr, Mn, and Co at most stations, while five stations were slightly polluted with Cd. Regarding EF, the lake was at risk in terms of Al and Pb accumulation. The CF results indicated that the lake was under pressure in terms of heavy metal pollution. The PLI results indicated a significant pollution hazard at all stations, while the PERI analysis indicated moderate risk of heavy metal pollution at some stations. As one of the most comprehensive studies applying such indices to Lake Bafa, the results are very significant in terms of evaluating the lake’s ecological sustainability. Full article

Studying and understanding the complexity and interactions of different factors influencing stream sediment quality is necessary for the development of successful water quality management strategies. This study aims to evaluate the level of contamination by potentially toxic elements (PTEs) (As, Co, Cr, Cu, Mn, Ni, Pb, V, Zn) of the stream sediments of the Nile River. During the spring of 2019, river sediments were sampled at 23 sites along the Nile River. For each sample, one aliquot was digested in aqua regia and analyzed by ICP-MS for pseudo-total concentration, while for another aliquot, sequential extraction procedures were applied to determine chemical speciation. Compositional data analysis (CoDa) and k-means were applied to recognize the contribution of natural and anthropogenic sources, while pollution indices (EF, RAC) and sediment quality guidelines (SQGs) were applied to assess the ecological risk to biotic species. The results reveal that elements such as Cr, Mn, V and Fe, found in high concentrations in almost all samples (Cr up to 739 mg/kg, Mn up to 1942 mg/kg, V up to 507 mg/kg, Fe up to 98,519 mg/kg), have a natural origin, while the concentrations of Cu (up to 69 mg/kg), Ni (up to 88 mg/kg), Co (up to 42 mg/kg) and As (up to 9.8 mg/kg) are linked to both natural and anthropogenic processes. Sequential extraction shows that Mn, Co, Ni and, in some sites, Cu and Zn, are the most bioavailable elements. These elements present a high risk of toxicity, while the remaining elements imply a low-to-moderate risk. Full article