Correct Approach Research Articles

QC Speller: User Interface Design of a Hands-Free Touch-Free Speller with Brain Electroencephalogram Sensory Rhythm

Nowadays, brain-computer interfaces (BCIs) are being extensively explored by researchers to recover the abilities of motor-impaired individuals and improve their communication. Text entry is one of the most important regular tasks in communication, and BCI has high application potential to develop a speller. Although BCI has been a growing research topic for the last decade, more progress is yet to be made for BCI-based spellers. Two challenges are there in BCI speller development: designing an effective graphical user interface with an optimal arrangement of symbols enabling a minimum number of control commands and reducing users’ efforts in error correction following an efficient error-correction policy. With this scope in mind, this work proposes a novel BCI speller paradigm with an efficient symbol arrangement to improve the text entry rate. Additionally, it provides a user-friendly error correction approach through six text-cursor navigation keys to enhance the accuracy of text entry. The proposed speller includes 36 target symbols and is operated with two control commands obtained from electroencephalogram motor-imagery signals. The experimental results revealed that the proposed speller outperforms the existing motor imagery-based BCI spellers when tested on ten motor-impaired users. This speller achieved a mean performance of 5.20 characters per minute without any typing error and 6.04 characters per minute with a 2.9 percent mean error. The mean correction efficiency was 0.69; that is, users corrected 69 percent of incorrect inputs with a single correction key pressed.

Testing the Ce Limit of Mass Bias Correction Using 145Nd/142Nd as Normalizing Ratio in Radiogenic Neodymium Isotope Analysis by MC-ICP-MS.

Neodymium isotopes are a powerful geochemical tool that has widely been used in terrestrial and extraterrestrial studies. Modern multicollector inductively coupled plasma mass spectrometers (MC-ICP-MS) allow fast, accurate, and precise analysis of the radiogenic Nd isotope ratio 143Nd/144Nd. These analyses comprise relatively high instrumental mass bias that is typically corrected for using the stable 146Nd/144Nd of 0.7219 and an exponential law. The instrument is usually tuned to optimize the operating conditions for isotope analysis, but this tuning is a trade-off primarily between signal intensity, stability, and accuracy. Alternative, more effective approaches for mass bias correction have been proposed that use 145Nd/142Nd as normalizing ratio. However, one drawback of using this ratio is that the efficient removal of Ce from Nd is required to minimize the effect of isobaric interference of 142Ce on 142Nd. Here, we analyzed international Nd and rock reference materials using a Thermo Scientific Neptune Plus MC-ICP-MS to evaluate the sensitivity of 145Nd/142Nd-based mass bias correction to varying Ce/Nd and in comparison with the commonly used 146Nd/144Nd-based correction. Our results show that the corrected 143Nd/144Nd of Ce-doped JNdi-1 and Ce-containing USGS BCR-2, NOD-A-1, and NOD-P-1 reference materials are insensitive to Ce/Nd of up ~1. The correction of instrumental mass bias with 145Nd/142Nd as a normalizing ratio yields, as previously suggested, improved trueness and precision of 143Nd/144Nd data in comparison with 146Nd/144Nd-based corrections, even under high Ce/Nd of to ~1. This allows improved optimization of signal intensity during instrument tuning, which is particularly useful for natural samples with low Nd content.

An improved empirical quantile mapping approach for bias correction of extreme values in climate model simulations

Abstract Quantifying and correcting biases in modeling simulations is crucial for deriving meaningful findings across various scientific disciplines. Climate model simulations, in particular, often exhibit systemic biases when compared to observations. These biases may persist in future climate simulations, affecting the results of many climate change impact assessment studies. Empirical Quantile Mapping (QM) is a widely used method to correct such biases, mapping quantiles between observed and simulated Cumulative Distribution Functions (CDFs). However, empirical QM faces a fundamental challenge when the CDF of future simulations differs from historical simulations, potentially leading to extreme values falling outside the historical CDF range. To address this issue, our study introduces a novel approach to extrapolate future extreme values for bias correction, preserving the rank order of simulated future extremes. By construction, our approach ensures that bias corrected values are not exaggerated and retain the rank structure of the original simulated data, while preserving climate change signals in the bias corrected outputs. Additionally, our approach includes a technique to adjust the wet-day frequency for precipitation by preserving the ratio of wet-day frequency between observations and historical model simulations.

Dynamic B0 field shimming for improving pseudo-continuous arterial spin labeling at 7 T.

B0 field inhomogeneity within the brain-feeding arteries is a major issue for pseudo-continuous arterial spin labeling (PCASL) at 7 T because it reduces the labeling efficiency and leads to a loss of perfusion signal. This study aimed to develop a vessel-specific dynamic B0 field shimming method for 7 T PCASL to improve the labeling efficiency by correcting off-resonance within the arteries in the labeling region. We implemented a PCASL sequence with dynamic B0 shimming at 7 T that compensates for B0 field offsets in the brain-feeding arteries by updating linear shimming terms and adding a phase increment to the PCASL RF pulses. Rapidly acquired vessel-specific B0 field maps were used to calculate dynamic B0 shimming parameters. We evaluated both 2D and 3D variants of our method, comparing their performance against the established global frequency offset and optimal encoding scheme-based corrections. Cerebral blood flow (CBF) maps were quantified before and after corrections, and CBF values from different methods were compared across the whole brain, white matter, and gray matter regions. All off-resonance correction methods significantly recovered perfusion signals across the brain. The proposed vessel-specific dynamic B0 shimming method improved the labeling efficiency while maintaining optimal static shimming in the imaging region. Perfusion-weighted images demonstrated the superiority of the 3D dynamic B0 shimming method compared to global or 2D-based correction approaches. CBF analysis revealed that 3D dynamic B0 shimming significantly increased CBF values relative to the other methods. Our proposed dynamic B0 shimming method offers a significant advancement in PCASL robustness and effectiveness, enabling full utilization of 7 T ASL high sensitivity and spatial resolution.

Hardware simulation of real-time wavelength corrected phase projection

We demonstrate the real-time signal processing operation of a dispersion-free phase projection algorithm intended for atmospheric correction of multi-aperture optical phased arrays. It uses interferometric phase measurements at multiple sensing wavelengths, offset by 50 GHz, to compute a phase correction at a third, remote wavelength. This is useful where phase sensing cannot be implemented at the wavelength of interest, enabling interferometric level control from wavelength offset targeting beacons or guidestars. The digital signal processing implementation we demonstrate has a residual temporal phase error of 4×10−4rad/Hz while being capable of 100 MHz throughput with 0.53 µs latency, making it a viable approach for either feedback or feed-forward atmospheric correction in segmented piston-phase control systems.

Surgery first approach for dentofacial deformity correction of a patient with achondroplasia: a case report

Surgery first approach for dentofacial deformity correction of a patient with achondroplasia: a case report

Complementary to Multiple Labels: A Correlation-Aware Correction Approach.

Complementary label learning (CLL) requires annotators to give irrelevant labels instead of relevant labels for instances. Currently, CLL has shown its promising performance on multi-class data by estimating a transition matrix. However, current multi-class CLL techniques cannot work well on multi-labeled data since they assume each instance is associated with one label while each multi-labeled instance is relevant to multiple labels. Here, we show theoretically how the estimated transition matrix in multi-class CLL could be distorted in multi-labeled cases as they ignore co-existing relevant labels. Moreover, theoretical findings reveal that calculating a transition matrix from label correlations in multi-labeled CLL (ML-CLL) needs multi-labeled data, while this is unavailable for ML-CLL. To solve this issue, we propose a two-step method to estimate the transition matrix from candidate labels. Specifically, we first estimate an initial transition matrix by decomposing the multi-label problem into a series of binary classification problems, then the initial transition matrix is corrected by label correlations to enforce the addition of relationships among labels. We further show that the proposal is classifier-consistent, and additionally introduce an MSE-based regularizer to alleviate the tendency of BCE loss overfitting to noises. Experimental results have demonstrated the effectiveness of the proposed method.

The Impact of Foreign Aid and Domestic Revenue on Government Expenditure in Nepal: An Error Correction Approach

The Impact of Foreign Aid and Domestic Revenue on Government Expenditure in Nepal: An Error Correction Approach

Adopting Additive Manufacturing in After‐Sales: Developing a Typology of Corrective, Preventive, and Anticipatory Approaches

Adopting Additive Manufacturing in After‐Sales: Developing a Typology of Corrective, Preventive, and Anticipatory Approaches

Reflecting on IPEF’s impact and charting the future: a perspective of US domestic politics

AbstractThe Indo-Pacific Economic Framework (IPEF), a key economic component of the Biden administration’s strategy for the Indo-Pacific, was launched to serve both economic and geopolitical purposes. At the heart of these objectives is the aim to undermine China’s growing influence in the Asia–Pacific region. If well implemented, it is expected to pose a series of challenges to China. The Biden administration’s strategic project, however, is very likely to fall short of its ambitious goals due to the constraints imposed by the US domestic politics, which significantly influences the content of the IPEF and the overall negotiation process. Both the Democratic and Republican parties have been embracing protectionism more than ever, which has greatly undercut the concessional space for any free trade move. In areas such as supply chain resilience, clean economy and fair economy, where the IPEF member states have come to consensus, the Biden administration has chosen to take a pro-workers approach notwithstanding the divergent interest pursuits by different interest groups within the US. This politically correct approach, however, is likely to face challenges in its implementation, as it largely conflicts with the interests of major corporations. Additionally, the Republican-controlled House of Representatives holds the purse strings, adding another layer of complexity to the situation. Meanwhile, the tussles and uncertainties surrounding the domestic politics of the US is very likely to discourage other member states.

Social and political development: out of conceptual mazes and into political agenda-setting

The article presents the results of the analysis and systematization of discourses describing the dynamics and key areas of social development. The purpose of the study is to determine the guidelines and priorities in discussions on development that dominate the research and expert agenda, and to identify the ideas and meanings that are invested in this concept by actors participating in public discussions and political goal-setting. The research methodology is based on the structural and functional approach, and on a comparative evaluation of the target settings present in the current expert discussion and in public policymaking. A quantitative content analysis of a sample of EU documents defining priorities of interaction with third countries to achieve development goals is offered as an illustrative example. The conclusions are presented in the form of a conceptual tree constructed by correlating the main concepts that exist in the research and expert field dealing with social development discourses and their political implications. According to the results of the study, the ideological appeal of narratives circulating in the public space of the “developed world” and the normative projection of this agenda worldwide transform discursive power into discursive hegemony through “green colonialism” and other forms of “promoting development”. The authors take a critical approach to the monopolization of the expert and political field by the concept of “sustainable development” which is widely regarded as a politically correct approach and a universalist political attitude. An ambiguous understanding of “social development” beyond the progressive paradigm and purely normative approaches in the social sciences makes the need to clarify this concept all the more urgent. The paper proposes to interpret “political development” as a multidimensional process leading to the complication of political interactions and not limited to institutional change, and “politics of development” as a system of management practices correlated with the public demand for security and social well-being. The current research agenda in this field in Russia aims to promote the analysis of the subjective dimension of politics, with a focus on identity studies and on evaluating intangible development resources.

Detection and quantification of small and low-uptake lesions for differentiated thyroid carcinoma using non-time-of-flight iodine-124 PET/MRI.

124-iodine (124I) is used for positron emission tomography (PET) diagnostics and therapy planning in patients with differentiated thyroid cancer (DTC). Small lesion sizes(<10mm) and low 124I uptake are challenging conditions for the detection of DTC lymph node lesions. The aim of this study was to systematically investigate the lesion detectability and quantification performance under clinically challenging imaging conditions using non-time-of-flight (TOF) PET/magnetic resonance imaging (MRI) in the clinical context of radionuclide therapy planning of DTC patients. PET/MR measurements were performed on the Siemens Biograph mMR using a small lesion NEMA-like phantom (six glass spheres, diameters 3.7-9.7mm). 60 min list-mode data were acquired for nine activity concentrations (AC) ranging from 25kBq/mL to 0.25kBq/mL using a sphere-to-background ratio of 20:1. PET list-mode data were divided into five timeframes (60, 30, 16, 8, and 4min) and reconstructed using either ordered-subsets expectation maximization (OSEM) or OSEM+ point spread function (PSF) algorithm. For all reconstructions, the smallest detectable sphere size was investigated in a human observer study. Partial volume effect (PVE) corrected PET images (contour and oversize-based approach) were analyzed considering a±30% deviation range between imaged and true AC as acceptable. Clinical data of eight DTC patients with small lymph node lesions were evaluated to assess agreement between the PVE correction approaches. Longer PET acquisition times, higher ACs, and PSF reconstructions resulted in improved PET image quality and overall improved lesion detectability. The smallest 3.7mm sphere was only visible under the best imaging conditions. Using a typical clinical 124I whole-body PET/MRI protocol with an acquisition time of 8 min using OSEM reconstructions, all lesions of ≥6.5mm in diameter could be detected and the quantification provided reliable results approximately above 5.0kBq/mL. An accurate quantification of ACs in the 4.8mm sphere was not feasible in this study. In the clinical evaluation of 10 lesions, a good agreement between oversize- and contour-based PVE corrections was observed(<15% deviation). The results showed that a reliable quantification of 124I uptake with PET/MRI is feasible and, therefore, could be used to perform radioiodine pre-therapy lesion dosimetry and individualized therapy planning in DTC patients.

Insights on formation of oxide layers, corrosion, and hydrogen embrittlement on the Ti2AlNb (1 1 0) surface: Density functional theory study

Ti2AlNb alloys offer good mechanical qualities and promise for use in various applications, such as aero-engines and other industries. However, corrosion and hydrogen embrittlement remain important concerns and limitations for their use. In this work, first-principle density functional theory is used to investigate the adsorption of hydrogen, fluorine and oxygen on the surface of Ti2AlNb (110). The effects of the considered adsorbates on the surface were compared by analysing the adsorption energy, charge density differences, density of states, and work function. The current findings revealed that the adsorption behaviour of all the adsorbates is exothermic and spontaneous due to the negative adsorption energy. More importantly, the effect of Van der Waals forces and dispersion correction was considered, it was found that for all adsorbates the dispersion correction approach exhibited the most stable adsorption energies (EadsDFT-D) than the standard density functional theory (EadsDFT). Thus, the standard DFT underestimates the adsorption energy. Furthermore, it was shown that the adsorption energy strength is dependent on the surface adsorption site, with the Ti-Nb and Al-Nb bridge sites being the most preferred sites for hydrogen, fluorine and oxygen adsorption. Subsequently, it was discovered that oxygen adsorption on the surface of Ti2AlNb (110) was more thermodynamically stable than hydrogen and fluorine. This suggests that the Ti2AlNb surface will likely suffer from oxidation rather than corrosion and hydrogen embrittlement. In addition, surface atoms showed electron-charge depletion, while adsorbates showed charge accumulation. The adsorption caused charge density redistribution and altered the surface work function.

Deep learning approaches for bias correction in WRF model outputs for enhanced solar and wind energy estimation: A case study in East and West Malaysia

Accurate estimation of wind and solar energy potentials is crucial for successfully integrating renewable energy into power grids. Traditional numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model, often suffer from biases that lead to inaccurate energy forecasts. This study employs advanced deep learning (DL) techniques to correct these biases in WRF model outputs, specifically to enhance wind and solar energy estimations in East and West Malaysia. Unlike previous studies, this research integrates a diverse array of DL models: Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Convolutional Neural Networks (CNN), and Feedforward Neural Networks (FNN), to address both temporal and spatial prediction challenges. The models were trained and tested using historical weather data and ground-based measurements to improve the accuracy of wind speed and solar radiation predictions. Evaluation metrics, root mean square error (RMSE), mean bias error (MBE), and mean absolute error (MAE), demonstrate the better performance of CNN and FNN models over the sole WRF approach. The findings reveal that CNN achieved the lowest RMSE in wind speed estimation (0.91 in CEMACS and 0.97 in Kuching compared to WRF RMSEs of 1.92 and 1.39). At the same time, FNN significantly improved solar radiation prediction (RMSE of 86.86 in Kuching and 99.23 in CEMACS compared to WRF RMSEs of 154.44 and 370.66). Given the low wind speeds, the corrected data from CNN was used to estimate wind energy at 536 kWh at Kuching and 0 kWh at CEMACS. FNN-corrected data was also used to estimate solar energy at 19 kWh and 18 kWh at Kuching and CEMACS, respectively. This research not only shows the effectiveness of DL in mitigating biases in numerical weather prediction models but also contributes a novel methodology for reliable renewable energy assessments.

New nomenclature of allergic diseases and hypersensitivity reactions

The review presents a modern view on the mechanisms of initiation and development of hypersensitivity reactions in response to external triggers based on the new nomenclature of allergic diseases proposed in 2023 by EAACI. The new concept of hypersensitivity is considered in detail, which systematizes previous classifications and summarizes newly obtained data on the etiology and mechanisms of development of inflammatory reactions in comparison with various variants of the immune response, based on the concept of phenotypes and endotypes of the disease. The modern concept of allergic reactions includes several types - associated with antibody formation (I-III), cell-mediated (IVa-c) and the Pichler concept, tissue-dependent, caused by defects in the epithelial barrier and metabolically induced immune dysregulation (V-VI), as well as a direct immunoinflammatory reaction to chemicals (VII). In the updated classification of allergic reactions, the adaptive and innate immune responses take a part in the initiation and effector phase of hypersensitivity reactions. The role of regulatory and effector subpopulations of lymphocytes and ILCs in various types of hypersensitivity is outlined. The leading role of epithelial barrier dysfunction in many allergic diseases, as well as the influence of viral infection on their course, is noted. The significance of metabolic dysregulation and its impact on the immune response is indicated. From the updated nomenclature of allergic reactions, it follows that several pathophysiological mechanisms may underlie the development of the same disease. It is interesting that most cellular and humoral factors are involved in various mechanisms of hypersensitivity, which once again confirms the biological universality of the immune response. As a wide range of people become familiar with the new concept and clinical and experimental data accumulate, the updated classification of hypersensitivity types will contribute to a theoretically sound, correct practical approach to the prevention of allergic diseases, improving their diagnosis and treatment.

Towards an understanding of uncertainties in the Lagrangian analysis of moisture sources for tropical cyclone precipitation through a study case

Despite the increasing number of atmospheric moisture tracking tools, their validation is challenging due to the lack of observations. This work contributes to a better understanding of uncertainties in the moisture sources analysis for the precipitation of tropical cyclones (TCs) by assessing eight combinations of threshold values in tracking methods based on the Lagrangian water budget equation. We selected as a study case Hurricane Ida that formed in the North Atlantic basin in late August 2021 and extracted the air parcel trajectories from the global outputs of the Lagrangian FLEXPART model. Results indicate that the choice of relative humidity (RH) threshold for filtering precipitating parcels has a noticeable impact on the Lagrangian precipitation estimates. In addition, methods applying the atmospheric boundary layer restriction produce a weaker moisture source pattern than those accounting for moisture uptakes in the whole atmospheric column. In particular, methods imposing an RH restriction along the air parcel trajectories to filter out noise in moisture losses outperform the others, providing more reliable moisture source contributions. We also introduced a simple bias correction approach that further improves the reliability of moisture source representation.

The Bleeding Edge: Managing Coagulation and Bleeding Risk in Patients with Cirrhosis Undergoing Interventional Procedures.

This review addresses the peri-procedural bleeding risks in patients with cirrhosis, emphasizing the need for careful coagulation assessment and targeted correction strategies. Liver disease presents a unique hemostatic challenge, where traditional coagulation tests may not accurately predict bleeding risk, complicating the management of procedures like paracentesis, endoscopic therapy, and various interventional procedures. As such, this paper aims to provide a comprehensive analysis of current data, guidelines, and practices for managing coagulation in cirrhotic patients, with a focus on minimizing bleeding risk while avoiding unnecessary correction with blood products. The objectives of this review are threefold: first, to outline the existing evidence on bleeding risks associated with common invasive procedures in cirrhotic patients; second, to evaluate the efficacy and limitations of standard and advanced coagulation tests in predicting procedural bleeding; and third, to examine the role of blood product transfusions and other hemostatic interventions, considering potential risks and benefits in this delicate population. In doing so, this review highlights patient-specific and procedure-specific factors that influence bleeding risk and informs best practices to optimize patient outcomes. This review progresses through key procedures often performed in cirrhotic patients. The discussion begins with paracentesis, a low-risk procedure, followed by endoscopic therapy for varices, and concludes with high-risk interventions requiring advanced hemostatic considerations. Each chapter addresses procedural techniques, bleeding risk assessment, and evidence-based correction approaches. This comprehensive structure aims to guide clinicians in making informed, evidence-backed decisions in managing coagulation in cirrhosis, ultimately reducing procedural complications and improving care quality for this high-risk population.

Multi-physical fields prediction model for turbine cascades based on physical information neural networks

The flow field information within the cascade is crucial for turbine design. Currently, the physical field data in the cascade is mostly obtained through numerical simulation, which is accurate but time-consuming. To enable fast and accurate prediction of the physical fields within the cascade, this study proposes a Physics-Informed Fourier Neural Operator (PIFNO) model. Compared to pure data-driven surrogate models, PIFNO incorporates partial physical information into the modeling process through a physics-head correction approach during training, which not only improves prediction accuracy but also enhances model interpretability to some extent. To expand the applicability of PIFNO, this paper proposes a Transfer Learning-based multi-physics fields prediction model (TL-PIFNO) that can predict the physical fields within the cascade under different operating conditions using limited training data. Experiments show that PIFNO has relative errors within 2% for pressure and temperature field prediction, and maximum relative errors within 5% for velocity field prediction. TL-PIFNO can achieve similar accuracy to PIFNO using only 3/10 of the data volume and 1/10 of the training time, showing great potential for engineering applications.

A pigment dispersion syndrome case with concave iris and ocular hypertension managed through a phakic ICL implantation.

A concave iris configuration is a characteristic feature of pigment dispersion syndrome (PDS). Therapeutic strategies to modify this configuration may be considered as first-line options for the treatment of ocular hypertension in PDS patients. A 37-year-old male patient with myopic anisometropia presented bilateral PDS with concave iris, Krukenberg's spindle and iris transillumination defect in both eyes. The intraocular pressure (IOP) was 27 mmHg in both eyes. Optic nerve and visual field parameters were normal. The right eye was treated with a neodymium:YAG LPI. In the left eye, an implantable collamer lens (ICL) V4c model implantation for myopia correction was performed. Six-months postoperatively, both eyes evidenced an anteriorization of the iris, the morphology of the concave iris improved with the ICL V4c in place, becaming flattener in left eye. The IOP was 18 mmHg without treatment. This case report reinforces the idea that in myopic patients with a concave iris, the refractive correction approach through ICL V4c implantation might also improve the iris configuration, similarly to laser peripheral iridotomy (LPI). Therefore, in this specific patient profile, this surgical procedure might be considered as a prophylactic treatment alternative to prevent the complications associated with this iris configuration, although its invasive nature should be taken into consideration.

TEDA-RLS: A TinyML Incremental Learning Approach for Outlier Detection and Correction

TEDA-RLS: A TinyML Incremental Learning Approach for Outlier Detection and Correction