Reading Accuracy Research Articles

Crowd Density Level Classification for Service Waiting Room Based on Head Detection to Enhance Visitor Experience

The crowd within a confined space can potentially lead to air stagnation in waiting areas. Constantly running air conditioning throughout the day to balance air circulation may result in excessive energy consumption by the building. To address this issue, Heating, Ventilating, and Air-Conditioning (HVAC) systems are employed to manage and regulate indoor energy usage. However, sensor-based detection often fails to capture human variables promptly, resulting in less accurate density readings. Camera footage proves to be more reliable than sensors in accurately detecting crowds. This research utilizes You Only Look Once version 8 (YOLOv8), a robust algorithm for object detection, particularly effective in crowd detection for images, along with Convolutional Vision Transformer (CvT) for crowd density level classification into "Normal" and "Crowded" levels. CvT enhances classification accuracy by incorporating function from Convolutional Neural Network (CNN) in model training, including receptive field, shared weights, etc. By integrating YOLOv8 and CvT, this method focuses on accurately classifying crowd density levels after identifying human presence in the waiting area (indoor). Evaluation metrics include mean Average Precision (mAP) for YOLOv8, and accuracy, precision, recall, and f1-score for CvT. This approach directly influences the management of HVAC systems.

Genetic neurodevelopmental clustering and dyslexia.

Dyslexia is a learning difficulty with neurodevelopmental origins, manifesting as reduced accuracy and speed in reading and spelling. It is substantially heritable and frequently co-occurs with other neurodevelopmental conditions, particularly attention deficit-hyperactivity disorder (ADHD). Here, we investigate the genetic structure underlying dyslexia and a range of psychiatric traits using results from genome-wide association studies of dyslexia, ADHD, autism, anorexia nervosa, anxiety, bipolar disorder, major depressive disorder, obsessive compulsive disorder, schizophrenia, and Tourette syndrome. Genomic Structural Equation Modelling (GenomicSEM) showed heightened support for a model consisting of five correlated latent genomic factors described as: F1) compulsive disorders (including obsessive-compulsive disorder, anorexia nervosa, Tourette syndrome), F2) psychotic disorders (including bipolar disorder, schizophrenia), F3) internalising disorders (including anxiety disorder, major depressive disorder), F4) neurodevelopmental traits (including autism, ADHD), and F5) attention and learning difficulties (including ADHD, dyslexia). ADHD loaded more strongly on the attention and learning difficulties latent factor (F5) than on the neurodevelopmental traits latent factor (F4). The attention and learning difficulties latent factor (F5) was positively correlated with internalising disorders (.40), neurodevelopmental traits (.25) and psychotic disorders (.17) latent factors, and negatively correlated with the compulsive disorders (-.16) latent factor. These factor correlations are mirrored in genetic correlations observed between the attention and learning difficulties latent factor and other cognitive, psychological and wellbeing traits. We further investigated genetic variants underlying both dyslexia and ADHD, which implicated 49 loci (40 not previously found in GWAS of the individual traits) mapping to 174 genes (121 not found in GWAS of individual traits) as potential pleiotropic variants. Our study confirms the increased genetic relation between dyslexia and ADHD versus other psychiatric traits and uncovers novel pleiotropic variants affecting both traits. In future, analyses including additional co-occurring traits such as dyscalculia and dyspraxia will allow a clearer definition of the attention and learning difficulties latent factor, yielding further insights into factor structure and pleiotropic effects.

IoT-Based Rainfall Monitoring System to Detect Rainy Flood for Coastal Areas of Bangladesh

Flood disasters in Bangladesh’s coastal regions have been a major source of worry due to their damaging effects on both the natural world and people. For this natural disaster to be tracked and efficiently controlled, rainfall measurement must be precise and trustworthy. The rain gauge, which has acquired global acceptability, is the most commonly used instrument for measuring rainfall. This study presents the design and experimental evaluation of a cloud-based sensor-based rain gauge for the real determination of total rainfall and rate. An ultrasonic sensor is connected to a round water container, a round rainwater acquisition, a Bluetooth module, and a data processing unit for data collecting and processing in the proposed recommendation sensor-based rain gauge. Improved rainfall evaluation and detection methods have been created using cutting-edge sensor data processing techniques. Throughout a local rainfall event, the performance of the electronic sensor-based rain gauge is assessed and contrasted with that of a hand-made rain gauge. The experimental results show that the suggested system offers an accurate reading of rainfall quantity and rate per unit of time and area, real-time rainfall monitoring, and reliable and consistent analysis. The created method is made to maintain rainy floods in Bangladesh’s coastal regions by storing rainfall data. The system is anticipated to help the region establish an efficient rainy flood monitoring system. Overall, the suggested digital sensor-based rain gauge offers a useful and trustworthy instrument for managing and monitoring rainfall in Bangladesh’s coastal regions in real-time. GUB JOURNAL OF SCIENCE AND ENGINEERING, Vol 9(1), 2022 P 52-57

Analysis and Development of an IoT System for an Agrivoltaics Plant

This article illustrates the development of SolarFertigation (SF), an IoT (Internet of Things) solution for precision agriculture. Contrary to similar systems on the market, SolarFertigation can monitor and optimize fertigation autonomously, based on the analysis of data collected through the cloud. The system is made up of two main components: the central unit, which enables the precise deployment and distribution of water and fertilizers in different areas of the agricultural field, and the sensor node, which oversees collecting environmental and soil data. This article delves into the evolution of the system, focusing on structural and architectural changes to develop an infrastructure suitable for implementing a predictive model based on artificial intelligence and big data. Aspects concerning both the sensor node, such as energy management, accuracy of solar radiation readings, and qualitative soil moisture measurements, as well as implementations to the hydraulic system and the control and monitoring system of the central unit, are explored. This article provides an overview of the results obtained from solar radiation and soil moisture measurements. In addition, the results of an experimental campaign, in which 300 salad plants were grown using the SolarFertigation system in a photovoltaic field, are presented. This study demonstrated the effectiveness and applicability of the system under real-world conditions and highlighted its potential in optimizing resources and increasing agricultural productivity, especially in agrivoltaic settings.

Polymorphism analysis of tri- and tetranucleotide repeat microsatellite markers in Hanwoo cattle.

The Hanwoo traceability system currently utilizes 11 dinucleotide repeat microsatellite (MS) markers. However, dinucleotide repeat markers are known to have a high incidence of polymerase chain reaction (PCR) artifacts, such as stutter bands, which can complicate the accurate reading of alleles. In this study, we examined the polymorphisms of the 11 dinucleotide repeat MS markers currently employed in traceability systems. Additionally, we explored four trinucleotide repeat MS markers and one tetranucleotide repeat MS marker in a sample of 1,106 Hanwoo cattle. We also assessed the potential utility of the tri- and tetranucleotide repeat MS markers. The polymorphic information content (PIC) of the five tri- and tetranucleotide repeat markers ranged from 0.663 to 0.767 (mean: 0.722), sufficiently polymorphic and slightly higher than the mean (0.716) of the current 11 dinucleotide repeat markers. Using all 16 markers, the mean PIC was 0.718. The estimated probability of identity (PI) was 3.13 × 10-12 using the 11 dinucleotide repeat markers, 7.03 × 10-6 using the five tri- and tetranucleotide repeat markers, and 2.39 × 10-17 using all 16 markers; the respective PIhalf-sibs values were 2.69 × 10-9, 1.29 × 10-4, and 3.42 × 10-13; and the respective PIsibs values were 3.89 × 10-5, 9.6 × 10-3, and 3.69 × 10-7. The probability of exclusion1 (PE1) was 0.999864 for the 11 dinucleotide repeat markers, 0.981141 for five of the tri- and tetranucleotide repeat markers, and > 0.99 for all 16 markers; the respective PE2 values were 0.994632, 0.901369, and > 0.99; and the respective PE3 values were 0.998702, > 0.99, and > 0.99. The five investigated tri- and tetranucleotide repeat MS markers can be used in combination with the 11 existing MS markers to improve the accuracy of individual identification and paternity testing in Hanwoo.

The Analysis of the Influence of Ambiguity Tolerance on the Understanding and Inspiration of English Reading

Ambiguity tolerance has a significant impact on English reading, specifically affecting students' reading styles, speed, and accuracy. Students with high ambiguity tolerance tend to adopt holistic reading strategies, achieving faster reading speeds but potentially overlooking crucial details. Conversely, those with low ambiguity tolerance prefer detailed, analytical reading methods, focusing excessively on specifics, which may lead to inefficient reading and potential deviations from the original meaning. Therefore, understanding students' actual ambiguity tolerance and taking measures to cultivate it, while guiding them towards more flexible and efficient reading styles, is crucial for enhancing their reading abilities and comprehensive literacy.

Longitudinal Observation of Text Reading Fluency in 1st Graders with and without Dyslexia

Objectives: Text reading fluency is an important skill for students using Korean which has a transparent orthography system. This study longitudinally observed text reading fluency in Korean first-grade students with and without dyslexia over 3 semesters. Methods: Forty children with dyslexia and forty typically developing children participated in the study. They were grouped based on their performance at the beginning of the second grade. All students exhibited normal levels of listening comprehension and nonverbal intelligence. Over the three semesters, participants read six texts at various decoding levels. We then analyzed the number of correctly read syllables per 10 seconds, text reading accuracy, and speed. Results: Both the dyslexia and typically developing group showed significant differences in the number of syllables read per 10 seconds at all time points. Text reading accuracy improved significantly from first to second semester of first grade for both the dyslexia and typically developing group. By first semester of second grade, students with dyslexia achieved approximately 80% accuracy. While dyslexic students’ reading speed significantly improved from second semester of first grade to the first semester of second grade, they remained slower than typically developing students. Typically developing students showed consistent improvements in reading speed across all time points. Conclusion: When intervening with lower-grade students with dyslexia in Korea, it’s crucial to conduct not only decoding but also text-level fluency activities. Providing individualized texts that are decodable for dyslexic children seems to be essential.

Teaching IELTS Reading Skills

This research describes the teaching of IELTS Reading for students. This research is library research. The analysis shows that the IELTS reading test evaluates participants' understanding of information and language, requiring them to synthesize, interpret, and respond to information. The test consists of 14 types of questions, including Choosing a Title, True False Not Given / Yes No Not Given, Matching Features, Matching Headings, Matching Paragraph Information, Matching Sentence Endings, Sentence Completion, List Selection, Multiple Choice, Short Answer, Summary Completion, Flow Chart Completion, Diagram Completion, and Table Completion. The resulting test is graded on a band scale from range from 0 (did not take the test) to 9 (proficient in English) which indicates students' understanding and ability to read in English. Understanding the types of questions on the IELTS is crucial for students to prepare for the test. However, the test requires precise abilities for success. Teachers can create lesson plans for teaching Reading IELTS to help students prepare for the test and prepare them for the test. To answer IELTS Reading questions, students need fast and accurate reading skills and the right strategy. Teaching reading skills for the IELTS test can be challenging, but several strategies can help teachers structure effective teaching. These include understanding the test format, analyzing previous questions, building academic vocabulary, teaching active reading, practicing explaining the main idea, teaching skimming and scanning techniques, managing class discussion and analysis, practicing with varied reading material, using an integrated approach, giving constructive feedback, simulating reading tests, giving homework, training students to compose an outline, and promoting flexibility in learning.

Ice growth detection and the de-icing using dual functional capacitive sensor

Ice detectors are vital for ice mitigation systems, ensuring accurate ice growth measurements across multiple icing-de-icing cycles. Residue ice on the sensor can lead to erroneous readings in subsequent cycles, so its removal is critical to obtain accurate readings. This article presents a novel capacitive ice detector with self-deicing functionality employing nichrome electrodes for both sensing and de-icing. The sensor underwent testing in a cooling chamber for validation. The results confirm the developed ice detector’s ability to quantify ice within 1 to 4 mm with up to 7.5 % error, while the de-icing unit consumes 35 W to remove a 2 mm ice layer in 60 s. Capacitive sensor de-icing can significantly enhance the performance of ice mitigation systems. This research significantly advances ice detection technology by providing a reliable method for accurate ice measurement and removal, offering a valuable foundation for future improvements in the field of ice mitigation systems.

Neural Network Signal Integration from Thermogas-Dynamic Parameter Sensors for Helicopters Turboshaft Engines at Flight Operation Conditions.

The article's main provisions are the development and application of a neural network method for helicopter turboshaft engine thermogas-dynamic parameter integrating signals. This allows you to effectively correct sensor data in real time, ensuring high accuracy and reliability of readings. A neural network has been developed that integrates closed loops for the helicopter turboshaft engine parameters, which are regulated based on the filtering method. This made achieving almost 100% (0.995 or 99.5%) accuracy possible and reduced the loss function to 0.005 (0.5%) after 280 training epochs. An algorithm has been developed for neural network training based on the errors in backpropagation for closed loops, integrating the helicopter turboshaft engine parameters regulated based on the filtering method. It combines increasing the validation set accuracy and controlling overfitting, considering error dynamics, which preserves the model generalization ability. The adaptive training rate improves adaptation to the data changes and training conditions, improving performance. It has been mathematically proven that the helicopter turboshaft engine parameters regulating neural network closed-loop integration using the filtering method, in comparison with traditional filters (median-recursive, recursive and median), significantly improve efficiency. Moreover, that enables reduction of the errors of the 1st and 2nd types: 2.11 times compared to the median-recursive filter, 2.89 times compared to the recursive filter, and 4.18 times compared to the median filter. The achieved results significantly increase the helicopter turboshaft engine sensor readings accuracy (up to 99.5%) and reliability, ensuring aircraft efficient and safe operations thanks to improved filtering methods and neural network data integration. These advances open up new prospects for the aviation industry, improving operational efficiency and overall helicopter flight safety through advanced data processing technologies.

Preschool Morphological Awareness and Developmental Change in Early Reading Ability

ABSTRACT Purpose This longitudinal study examined the contribution of preschool morphological awareness to word reading skills and reading comprehension, as well as to the developmental change of reading ability beyond other well-established oral language and cognitive predictors. A distinction was made between the domains of inflectional and derivational morphology. Method Two hundred and fifty-nine Norwegian-speaking children (46% female) with a mean age of 5.5 years were assessed in preschool on language measures and again in Grades 1 and 3 on measures of word reading accuracy and fluency and in Grades 3 and 4 on reading comprehension. We fit latent change score models with preschool predictors using parceling to control for measurement error. Results We found a unique contribution of preschool morphological awareness to reading comprehension in Grade 3, but no unique contribution to Grade 1 decoding. Neither awareness of inflections nor awareness of derivations predicted developmental change in word reading fluency between Grades 1 and 3 or change in reading comprehension between Grades 3 and 4 beyond the effect of control variables. Conclusion Our findings confirm the relevance of morphological awareness only for early attainment in reading comprehension and highlight the importance of accounting for measurement error in studying associations among variables aiming to discover specific contributions.

Examining the developmental trade-off between phonology and morphology in Hebrew reading acquisition

AbstractThe relative importance of phonological versus morphological processes in reading varies depending on the writing system's orthographic consistency and morphological complexity. This study investigated the interplay between phonology and morphology in Hebrew reading acquisition, a language offering a unique opportunity for such examination with its rich, complex Semitic morphological system and dual writing versions differing in orthographic consistency—transparent-pointed and deep-unpointed versions. Ninety-eight second graders and 81 fourth graders participated in pseudoword-reading tasks designed to distinguish between the different processes: pointed morphologically based pseudowords (pointed MPW), reflecting phonological and morphological processing; unpointed morphologically based pseudowords (unpointed MPW), reflecting only morphological processing; and pointed non-words (pointed NW), with no internal morphological structure, reflecting only phonological processing. Real pointed-word reading accuracy and fluency were also assessed. Results showed the highest accuracy in reading unpointed MPW, with a similar accuracy level observed between unpointed MPW and pointed MPW in second grade, while a significant difference emerged in fourth grade. An age-by-processing type interaction revealed decreasing accuracy in pointed MPW and increasing accuracy in unpointed MPW with age. Additionally, morphological processing significantly enhanced the accuracy and fluency of reading pointed words beyond phonological processing, despite the comprehensive phonological information provided by the transparent, pointed script. These findings suggest that the contribution of morphology exceeds that of phonology as early as second grade, with this trend strengthening through fourth grade, emphasizing children's early prioritization of morphological transparency over orthographic consistency in learning to read Hebrew Semitic orthography.

Enhanced drift self-calibration of low-cost sensor networks based on cluster and advanced statistical tools

The escalating use of low-cost sensors in environmental monitoring demands effective management of sensor drift and errors. To tackle this challenge, lightweight calibration techniques are essential for accurate sensor readings. This paper presents a novel calibration method for low-cost sensors, prioritizing the detection and correction of sensor drifts. The approach incorporates clustering for efficient task distribution and leverages Inverse Distance Weighting (IDW) for calibration precision. Also, advanced statistical tools, including the Two-Sample Kolmogorov–Smirnov test (TSKS test) and Exponential Moving Average (EMA), assess and enhance sensor data stability based on historical measurements. Additionally, the Root Update Estimator (RUE) is utilized to adjust predicted values and improve the model’s adaptability to changes in the underlying data distribution. Extensive simulation experiments using an Intel Berkeley Research Laboratory (IBRL) dataset affirm the method’s effectiveness in swiftly addressing sensor drifts. These findings advance low-cost sensor calibration, boosting reliability and precision in environmental monitoring.

Assessing Reading Texts for Non-Native Arabic Speaking Students at the University of Jordan in Light of the Common European Framework of Reference for Languages From the Students' Perspective

This study aims to assess the extent to which reading texts for non-native Arabic-speaking students at the University of Jordan align with the CEFR (Common European Framework of Reference for Languages) criteria from the students' perspective. The study sample consisted of 64 students from the University of Jordan for the academic year 2021/2022. They were divided into 25 students from the first preparatory level and 39 students from the second preparatory level. A questionnaire was used as a data collection tool, and it included three areas: reading speed, linguistic richness, and accurate reading. The results indicated that all areas appeared to be moderate from the students' perspective, and there was no significant impact on the results attributed to demographic variables. Based on these results, the study demonstrates the importance of incorporating elements of CEFR in teaching language skills in Arabic for non-native speakers.

Analisis Kemampuan Membaca Lancar Level 2 Siswa SD

Fluent reading is the ability to master codes consisting of words by paying attention to the following factors: the ability to identify words automatically, the speed at which words move from one word to another, the procedures or expressions used in oral reading and accuracy. in translating the code to ensure the decoding process and understanding of the text being read. Therefore, the aim of this research is to analyze students' fluent reading abilities at level 2 in terms of reading accuracy and speed as well as fluency in reading texts with appropriate pauses, intonation and expression. The method used is a case study method through a reading test which is designed to assess the three main components of pauses, intonation and expression. The research subjects consisted of 3 2nd grade elementary school students|

Are Poor Readers Also Poor Spellers: An Investigation Into the Malay and English Languages Among Young Multilingual Malaysians

Children with reading difficulties typically experience difficulties in both reading and spelling. Little is known about the use of spelling for identifying reading difficulties across languages that possess different orthographic depths, among multilingual readers. In the current study, we investigated whether multilingual Primary 1 poor readers were also poor spellers in two different orthographies, namely Malay and English. The sample comprised 866 Primary 1 Malaysian public school students from diverse backgrounds. A cut-off point of 25th percentile and below was used to operationalise students with deficits in word reading accuracy and spelling across both languages. A majority of the students who were poor readers in Malay and English, correspondingly, were also poor spellers in both languages. Spelling and word reading accuracy were highly correlated and considered as good indicators for identifying struggling young multilingual readers. These results indicate the importance of assessing spelling in both Malay and English for identifying reading difficulties, especially among young multilingual Malaysian learners. Implications for practice and future directions are addressed.

Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study.

We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024;96:476-487.

Alouette-R normative data for French-speaking school-aged children living in Quebec.

The Alouette-R (2005) by Lefavrais is one of the most widely used tools to assess reading skills in French. However, this instrument does not have normative data specific to the French-speaking population of Quebec, Canada. The validity of an assessment being strongly compromised when using inappropriate norms, the first objective of this study was to establish local norms for the Alouette-R. The second objective was to provide sensitivity and specificity data for each Alouette-R measure in the French-speaking Quebec population. The third objective was to compare Quebec and French normative data and their sensitivity to better understand the applicability and effectiveness of the Alouette-R test at the regional level. A total of 347 fluent readers and 48 children with dyslexia from 3rd to 6th grades were recruited from different regions in Quebec. Participants had to read aloud the 265-word text of the Alouette-R in a maximum of 3 min. Norms (means, standard deviations and percentiles) by school grades were created for each test measure: reading time, number of words read, number of errors, number of words correctly read, reading accuracy index and reading fluency index. The sensitivity (i.e., the ability to correctly identify children with dyslexia) and specificity (i.e., the ability to correctly identify children without dyslexia) of these measurements were also documented. The norms and their sensitivity were then compared with those of the original French study by Lefavrais in 2005. The presence of differences between European and Quebec norms supports the importance of using local norms when assessing language skills. The reading accuracy and fluency indexes are the measurements that best discriminated children with dyslexia from those without a reading disorder in our study. This study will allow clinicians working in Quebec to have a better interpretation of the Alouette-R measurements and ultimately avoid erroneous conclusions resulting from the use of foreign normative data. What is already known on this subject The Alouette-R is a reading test validated and standardized in France to screen for dyslexia in children. The validity of existing norms with the Quebec population in Canada is questionable due to socio-linguistic differences with the population of France. What this study adds to existing knowledge This study provides for the first time normative and sensitivity/specificity data of the Alouette-R for French-speaking school-aged children living in Quebec. Differences were noted with the normative data from France, which supports the importance of using local normative data when administering reading tests in Quebec. What are the potential or actual clinical implications of this work? When administering the Alouette-R, clinicians in Quebec will now be able to use normative data adapted to the local population, which will limit erroneous conclusions resulting from the use of foreign normative data. In addition, the sensitivity and specificity values reported in the article will allow these clinicians to better interpret their results when screening for a developmental reading disorder.

Improving diagnostic precision in amyloid brain PET imaging through data-driven motion correction

BackgroundHead motion during brain positron emission tomography (PET)/computed tomography (CT) imaging degrades image quality, resulting in reduced reading accuracy. We evaluated the performance of a head motion correction algorithm using 18F-flutemetamol (FMM) brain PET/CT images.MethodsFMM brain PET/CT images were retrospectively included, and PET images were reconstructed using a motion correction algorithm: (1) motion estimation through 3D time-domain signal analysis, signal smoothing, and calculation of motion-free intervals using a Merging Adjacent Clustering method; (2) estimation of 3D motion transformations using the Summing Tree Structural algorithm; and (3) calculation of the final motion-corrected images using the 3D motion transformations during the iterative reconstruction process. All conventional and motion-corrected PET images were visually reviewed by two readers. Image quality was evaluated using a 3-point scale, and the presence of amyloid deposition was interpreted as negative, positive, or equivocal. For quantitative analysis, we calculated the uptake ratio (UR) of 5 specific brain regions, with the cerebellar cortex as a reference region. The results of the conventional and motion-corrected PET images were statistically compared.ResultsIn total, 108 sets of FMM brain PET images from 108 patients (34 men and 74 women; median age, 78 years) were included. After motion correction, image quality significantly improved (p < 0.001), and there were no images of poor quality. In the visual analysis of amyloid deposition, higher interobserver agreements were observed in motion-corrected PET images for all specific regions. In the quantitative analysis, the UR difference between the conventional and motion-corrected PET images was significantly higher in the group with head motion than in the group without head motion (p = 0.016).ConclusionsThe motion correction algorithm provided better image quality and higher interobserver agreement. Therefore, we suggest that this algorithm be adopted as a routine post-processing protocol in amyloid brain PET/CT imaging and applied to brain PET scans with other radiotracers.

Music training influences online temporal order processing during reading comprehension

Numerous studies have demonstrated the influence of musical expertise on spoken language processing; however, its effects on reading comprehension remain largely unexplored. This study aims to investigate the role of musical expertise in sentence comprehension, particularly concerning the processing of temporal order. Using two self-paced reading experiments, we examined individuals' responses to two-clause sentences connected by the temporal connectives “before” or “after”. “After” sentences consistently presented events in their actual order of temporal occurrence, while “before” sentences described events in reverse temporal order. In both experiments, our analyses of reading times consistently uncovered a significant temporal order effect, with words immediately following the temporal connectives being processed slower in “before” sentences compared to “after” sentences. This suggests the presence of immediate online processing costs associated with “before” sentences. Notably, these processing costs were found to be attenuated in individuals with musical expertise compared to those without. However, analyses of comprehension accuracy showed no advantage of musicians over non-musicians. Specifically, in Experiment 1, the two groups showed no difference in comprehension accuracy, while in Experiment 2, musicians exhibited lower accuracy rates compared to non-musicians in both “before” and “after” sentences. These results suggest that musical expertise may attenuate online processing costs associated with complex linguistic constructs, but could not promote reading accuracy. We concluded that music training is associated with a restricted effect on written sentence comprehension.