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Synergism of enzymes and molecularly imprinted polymers in electrochemical sensors
No full textMolecularly imprinted polymers (MIPs) have been established as effective specifiers in clinical diagnostics and environmental analysis for a large spectrum of analytes spanning from low-molecular-weight substances to proteins, including enzymes. The synergism of MIP technology and enzyme technique is mirrored on the one hand by the high affinity, which results in an excellent analytical performance for the determination of enzymes by MIP-sensors, and on the other hand, in the improvement of preparation and readout of MIPs by using enzymes as tools. In addition, the creation of catalytically active MIP has been derived from the transition state concept of enzymatic substrate conversion. The integration of MIPs for enzymes in electrochemical sensors offers distinct benefits, e.g., the direct readout of the catalytic activity or the direct electron transfer with redox-active groups ensures excellent specificity. On the other hand, enzymes simplify the MIPs synthesis and improve the signal processing of electrochemical sensors
Synthesis of New Quinoline Substituted Zinc Phthalocyanine and Revealing Its Potential for Photodynamic Therapy
No full textA fast approach for flood mapping over a large region using Sentinel-2 imagery
No full textFloods impact millions globally, necessitating rapid mapping techniques for effective disaster management response. This study introduces a novel patch-wise classification framework and the ChangeSEN2-FL dataset, comprising 701 flood and 1216 non-flood multispectral bitemporal patch pairs from diverse global regions using Sentinel-2 imagery. Each 5km×5km patch includes 12 pre-event and 12 post-event bands. Using the ChangeSEN2-FL dataset, we developed a classification framework with improved generalization, utilizing multiple normalized difference indices (NDIs) for reliable flood detection. To address flood variability, we introduce a multiple thresholding approach (MTA) for NDIs within a dual-input ResNet50-based architecture. This setup utilizes false-colour (FC) and true-colour (TC) RGB composites to improve flood detection generalizability. The proposed framework is tested on a held-out set and three case studies from Madagascar, Pakistan, and Australia. The case studies test the global applicability of the model framework, comparing performance across regular RGB and dual-input configurations of single and multiple thresholded false-colour RGB. The held-out test results show a 3% improvement over TC RGB-based model, achieving 97% accuracy. Case studies further confirm adaptability, with 7.5% and 55% improvement over TC RGB-based model in Madagascar and Pakistan, respectively, demonstrating strong generalization across diverse flood scenarios.</p
Measurement of the Drell–Yan forward-backward asymmetry and of the effective leptonic weak mixing angle in proton-proton collisions at s=13TeV
No full textThe forward-backward asymmetry in Drell–Yan production and the effective leptonic electroweak mixing angle are measured in proton-proton collisions at s=13 TeV, collected by the CMS experiment and corresponding to an integrated luminosity of 138fb−1. The measurement uses both dimuon and dielectron events, and is performed as a function of the dilepton mass and rapidity. The unfolded angular coefficient A4 is also extracted, as a function of the dilepton mass and rapidity. Using the CT18Z set of parton distribution functions, we obtain sin2θeffℓ=0.23152±0.00031, where the uncertainty includes the experimental and theoretical contributions. The measured value agrees with the standard model fit result to global experimental data. This is the most precise sin2θeffℓ measurement at a hadron collider, with a precision comparable to the results obtained at LEP and SLD
A Methodology Developed for Assessing the Potential Drivers of Water Losses in Natural Lakes at Country-Scale: Status of Türkiye
No full textThis study examines key features of natural lakes within a Lake Information Database (LID) and develops a lake assessment methodology (LAM) to identify the primary drivers of temporal water surface area (WSA) changes across Türkiye. The dominating driver for WSA changes is attributed either to natural factors or to human activities through harmonised analysis utilising LAM, which brings novelty to this study. Three lakes among the 27 with surface area over 2000 ha are displayed and discussed to show the applicability and performance of LAM that utilises remote sensing (RS) and geographical information system (GIS). The dominating factor on WSA decrease in the lakes was seen as climatic conditions in the higher altitude lakes, and human activities in the lower altitude lakes pointing out the key strength of the research. Thus, LAM offers a globally applicable and flexible methodology that produces fast results regarding the main drivers of WSA.</p
KAFA-Merge: Model Merging Method With Layer-Based Bayes+Linear Search
No full textIn this paper, we consider the model merging process for large language models (LLMs) under a two-stage optimization framework. Traditional merging methods usually apply fixed blending rates to all layers, which ignores the different levels of contribution of layers to the output. To overcome this limitation, we first group layers with similar functionality and use Bayesian optimization to determine the optimal blending rates for each group. Bayesian optimization offers a globally effective discovery strategy in high-dimensional and computationally expensive search spaces. However, an approach based solely on global search can lead to local artifacts being missed. Therefore, in the second stage, we perform Linear Search by applying controlled variations around the ratios obtained with Bayesian optimization and obtain more precise, locally optimized results. Extensive experiments on the Turkish versions of the Arc, Hellaswag, MMLU and GSM8K datasets show that our proposed Bayes+Linear strategy outperforms existing methods such as SLERP, Linear, Ties and Breadcrumbs. In addition to improving model accuracy and generalization capacity, the KAFA approach works without any additional fine-tuning, making it possible to effectively reuse large language models in different tasks
Fracture resistance of fixed partial dentures: the influence of restoration geometry and material in additive manufacturing
No full textPURPOSE. The location of the edentulous area in the dental arch can influence the design of the bridge prosthesis in the surrounding region and the forces it will encounter. This study assessed the fracture strength of restorations with various geometric designs produced using different additive and subtractive manufacturing methods. MATERIALS AND METHODS. Co-Cr metal and zirconia fixed partial denture (FPD) frameworks were designed in both linear and curved geometries. The Co-Cr metal frameworks were produced through casting (C) and laser sintering (L), while the zirconia (Z) frameworks were obtained through milling (n = 10). After veneering the frameworks, a four-point bending test was conducted on the specimens to assess their fracture strength. All obtained values were statistically analyzed (P <.05). RESULTS. In both linear and curved groups, Z group showed the lowest fracture resistance values followed by C and L groups and the differences between the groups were found statistically significant (P <.05). In L group, curved FPDs showed statistically significantly higher fracture resistance values than linear FPDs (P <.05). In both Z and C groups, curved FPDs showed statistically significantly lower fracture resistance values than linear FPDs (P <.05). CONCLUSION. The geometric configuration of the restoration and manufacturing technique affects the fracture resistance of different framework materials in FPDs