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Background: Impaired cognitive function following exposure to heavy metals has emerged as a significant global health concern. Nevertheless, the impact of combined exposure to multiple heavy metals on cognitive impairment remains unclear. Objective: This study aimed to explore the association between multiple heavy metals exposure and cognitive function to provide theoretical evidence to guide prevention strategies. Methods: The blood levels of lead (Pb), cadmium (Cd), mercury (Hg), selenium (Se), copper (Cu) and zinc (Zn) and the results of the cognitive function tests were extracted from 811 elderly Americans who completed the NHANES between 2011 and 2014. Quantile regression (QR), restricted cubic splines (RCS), and Bayesian kernel machine regression (BKMR) were used to explore the individual and joint association between heavy metals exposure and performance in 4 standardized cognitive tests; Item Response Theory (IRT), Delayed Recall Test (DRT), Animal Fluency Test (AFT) and Digit Symbol Substitution Test (DSST). Results: A negative association was noted between Cd levels and IRT (p = 0.048, 95%CI: -2.7, -0.1). Se concentrations ranging between 2.197 µg/L (95%CI: 0.004, 0.15) to 2.29 µg/L (95%CI: 2.56, 7.64) (log10Se) was postively associated with DSST (p = 0.001). Cu was negatively associated with DSST (p = 0.049, 95%CI: -37.75, -0.09), while Zn was positively associated with IRT (p = 0.022, 95%CI: 0.55, 11.73). Exposure to the 6 heavy metals combined showed a positive linear association with IRT, DRT, and a negative linear association with DSST. An interaction between Cd and the other heavy metals (excepted for Pb). Conclusion: Exposure to Pb, Cd, Hg, Se, Cu, and Zn was associated with cognitive function. Joint exposure to the 6 heavy metals showed a positive linear association with IRT, DRT, contrarily, a negative linear association with DSST. [ABSTRACT FROM AUTHOR]

Abstract: This squib makes the observation that inverse linking readings are dependent on extraposition of the embedded quantifier to a higher position within the nominal. Evidence comes from cases where there is an additional modifier in the nominal, which indicates whether or not extraposition has taken place; when the PP containing the second quantifier is not extraposed, it does not take wide scope of the embedding quantifier. [ABSTRACT FROM AUTHOR]

Massive MIMO (mMIMO) is the essential technique for attaining the exponential increase in the data rate needed for future communication systems. These advancements have been significantly supported by progress in VLSI technology, which enables the integration of an enormous number of antennas and the complex signal processing essential for massive MIMO systems on a single chip. This work conducts a comprehensive analysis of the intricacy of seven matrix decomposition techniques for symbol detection in future mMIMO communication systems: ADMM-based infinity norm (ADMIN), Neumann series (NS), Newton iteration (NI), Jacobi iteration (Ja), improved Gauss-Seidel (IGS), conjugate gradient (CG), and QR decomposition (QR), against linear and near-optimal minimum mean square error (MMSE). QR, GS, Ja, and CG belong to linear algebraic methods based on matrix decomposition. MMSE and ADMIN are nonlinear optimization methods; NS and NI are iterative methods. The analysis examines into the complexity of these detection algorithms, considering the symbol error rate, the convergence rate, the initial solution vector, and the correlation factor. Performance evaluations are conducted on 8 and 16-user mMIMO systems with 64 and 128 base station antennas, modulation schemes (32-QAM and 64-QAM), iteration counts (p = 1, 2, 3, 4), correlation factors (α = 0.2, 0.4, and 0.6), and initial solution vectors (zero vector, D−1 and W2−1yMF). The result clearly shows that if the initial solution and number of iterations are chosen properly, the IGS-based linear detector achieves near-optimal performance with a lower computational complexity of O(K2) compared to the nonlinear MMSE-based detector with a computational complexity of O(K3). [ABSTRACT FROM AUTHOR]

significant impact on global trade in the modern era. This has given rise to a new industry known as "electronic commerce," or "E-commerce," which is the use of smart devices and the internet for the exchange and display of goods and products. The need for a means of transferring money between people and businesses globally led to the creation of the so-called electronic payment, which is the foundation of electronic commerce and involves using computers and other smart devices to transfer money between the bank accounts of the relevant parties. This paper reviewed the most important electronic payment methods currently available and the security features of each method, as the adoption of any method depends on the availability of service by the responsible authorities in a particular region and the living level of that region. But, in general, mobile wallet applications that use NFC technology are considered one of the most adopted methods worldwide due to their ease of use and the availability of NFC service in most modern smartphones.

The study aims to assess the marine environmental hazards resulting from some industrial activities areas being found at the Suez Bay. The survey was done to select five industrial locations along the studied areas where different water and sediment samples were collected during September 2020. The study methods showed that different concentrations were measured in the collected water and sediment samples, such as; Al, Fe, Mn, Hg, Cd, Cr, Co, Mo, V, Pb, Ni, Cu, Zn, where the digested samples were measured by using Inductively Coupled Argon Plasma spectroscopy (ICAP 6500 Duo), while the natural radioactivity concentrations of the selected radio-nuclides such as 238U, 226Ra, 232Th, 40K, were measured in both water and sediments samples by using Hyper germanium detector, as the radiological risk assessment of different samples was detected by using ERICA modeling software. The study results showed that the concentrations of the measured trace elements in the selected five industrial sites were slightly higher than the standard limits, while the measured radioactivity concentrations of the selected radio-nuclides in both water and sediment samples were below the standard limits. The results showed that the calculated distribution coefficient of the selected trace elements was (Kd Metal Pollution Index < 3), which indicated that the measured trace elements were more dissolved in the aqueous than the sediment medium. The study used the mean probable effect Level (m-PEL-Q) for estimating the metal concentration hazards in the sediment samples at the selected sites, where these values were ranged from 0.04 to 0.1, indicating that the combined concentration effects for these metals were caused 9% toxic probability. The study showed that both the calculated quotient risk (QR) and dose rate values of the marine organisms which were being calculated by the ERICA model were below the recommended limits. [ABSTRACT FROM AUTHOR]

This article aims to support students, employees, and the general public by leveraging document scanning, optical character recognition (OCR), QR code generation, and QR code reading. With the growing prevalence of digitalization in educational institutions, offices, and governments, there is a consistent demand for efficient tools to fulfill these tasks. To address this need, we advocate for a dependable scanning application equipped with essential features like PDF manipulation tools, QR code generation, and QR code reading capabilities. While numerous online applications exist, they often fall short in terms of quality and functionality, sometimes necessitating payment for advanced features. However, the "Documents World App" stands out as a viable solution, offering high-quality scanning, PDF tools for modifying existing documents, and editing features for adding signatures and watermarks, streamlining these processes. Noteworthy are its advanced functionalities, including text extraction facilitated by the itext library, a feature not commonly found in widely used tools such as "Adobe Scan" and "iLove PDF." Crucially, our objective is to provide this service to all users without any charges and intrusive advertisements, ensuring accessibility and affordability for everyone. [ABSTRACT FROM AUTHOR]

Counterfeit protection is a serious concern for businesses, as it can compromise consumer safety and damage a company's reputation. To address this issue, researchers have conducted a review of available technologies and found that blockchain-based solutions offer several advantages over traditional methods. The use of REST APIs enables secure and transparent tracking of products through the supply chain, while smart contracts facilitate automatic ownership transfers. The traceability provided by blockchain technology allows stakeholders to track a product's origin and journey, improving security and transparency. Implementing a blockchain-based supply chain management system can also improve efficiency and reduce costs associated with lost or misplaced items. This research paper advocates for businesses to invest in advanced technologies like blockchain to protect their supply chains and ensure the safety and authenticity of their products. The system described in the paper involves generating unique identification numbers (UIDs) and associating them with products during the manufacturing process with QR codes and scratchable film for consumer access, while also emphasizing the need for businesses to adopt innovative technologies to maintain competitiveness and customer trust. [ABSTRACT FROM AUTHOR]

This paper describes a course designed to introduce students to mathematical thinking and a variety of lower level mathematics topics using baseball while satisfying the goals of quantitative reasoning. We give suggestions for sources, topics, techniques, and examples so any mathematics teacher can design such a course to fit their needs. The course assumes no previous college level mathematics and includes statistics, linear functions, modeling, and simulation. [ABSTRACT FROM AUTHOR]

The different commercial and open-source LMSs do not support pre-built activities for students in Augmented Reality (AR). To solve this challenge, this work combines AR technology and the Moodle platform to enhance the capabilities to motivate students during the learning process. For this, we developed and configured an AR app to receive and solve a Moodle pre-built quiz by communication (using message swap) between Moodle, Vuforia, and Unity. The post-quiz questionnaire results show the satisfaction level of 40 students in higher education after taking a quiz via AR. A descriptive statistical analysis indicated that students’ satisfaction was 4.6 on a 5-point Likert Scale. The research offers empirical evidence that taking quizzes through AR helps motivate students and improve Technology-Mediated Learning (TML) processes. [ABSTRACT FROM AUTHOR]

Bomb disposal squads who identify and test improvised explosives devices and ordnance mostly use dogs, metal detectors, traditional detectors of trace particles and portable X-ray devices. Magnetometers and ground-penetrating radar devices are used to find ordnance under the ground, and sonar is used to find ordnance under water. In some cases, however, it would also be appropriate to make use of certain advanced methods of detecting explosives, such as quadrupole resonance, neutron in - gamma out, and optical methods of stand-off detection.

Effective prediction of wind power output intervals can capture the trend of uncertain wind output power in the form of probability, which not only can avoid the impact of randomness and volatility on grid security, but also can provide supportable information for grid dispatching and grid planning. To address the problem of the low accuracy of traditional wind power interval prediction, a new interval prediction method of wind power is proposed based on PSR-BLS-QR with adaptive rolling error correction. First, one-dimensional wind power data are mapped to high-dimensional space by phase space reconstruction (PSR) to achieve data reconstruction and the input and output of the broad learning system (BLS) model are constructed. Second, the training set and the test set are divided according to the input and output data. The BLS model is trained by the training set and the initial power interval of training data is constructed by quantile regression (QR). Then, the error distribution of nonparametric kernel density estimation is constructed at different power interval segments of the interval upper and lower boundaries, respectively, and the corresponding error-corrected power is found. Next, the optimal correction index is used as the objective function to determine the optimal error correction power for different power interval segments of the interval upper and lower boundaries. Finally, a test set is used for testing the performance of the proposed method. Three wind power datasets from different regions are used to prove that the proposed method can improve the average prediction accuracy by about 6–14% with the narrower interval width compared with the traditional interval prediction methods. [ABSTRACT FROM AUTHOR]

Computed Tomography (CT) scan and Magnetic Resonance Imaging (MRI) technologies are widely used in medical field. Within the last few months, due to the increased use of CT scans, millions of patients have had their CT scans done. So, as a result, images showing the Corona Virus for diagnostic purposes were digitally transmitted over the internet. The major problem for the world health care system is a multitude of attacks that affect copyright protection and other ethical issues as images are transmitted over the internet. As a result, it is important to apply a robust and secure watermarking technique to these images. Notably, watermarking schemes have been developed for various image formats, including .jpg, .bmp, and .png, but their impact on NIfTI (Neuroimaging Informatics Technology Initiative) images is not noteworthy. A watermarking scheme based on the Lifting Wavelet Transform (LWT) and QR factorization is presented in this paper. When LWT and QR are combined, the NIfTI image maintains its inherent sensitivity and mitigates the watermarking scheme's robustness. Multiple watermarks are added to the host image in this approach. Measuring the performance of the graphics card is done by using PSNR, SSIM, Q (a formula which measures image quality), SNR, and Normalized correlation. The watermarking scheme withstands a variety of noise attacks and conversions, including image compression and decompression. [ABSTRACT FROM AUTHOR]

In this work, we develop a fast hierarchical solver for solving large, sparse least squares problems. We build upon the algorithm, spaQR (sparsified QR Gnanasekaran and Darve in SIAM J Matrix Anal Appl 43(1):94–123, 2022), that was developed by the authors to solve large sparse linear systems. Our algorithm is built on top of a Nested Dissection based multifrontal QR approach. We use low-rank approximations on the frontal matrices to sparsify the vertex separators at every level in the elimination tree. Using a two-step sparsification scheme, we reduce the number of columns and maintain the ratio of rows to columns in each front without introducing any additional fill-in. With this improvised scheme, we show that the runtime of the algorithm scales as O (M log N) and uses O (M) memory to store the factorization. This is achieved at the expense of a small and controllable approximation error. The end result is an approximate factorization of the matrix stored as a sequence of sparse orthogonal and upper-triangular factors and hence easy to apply/solve with a vector. Numerical experiments compare the performance of the spaQR algorithm with direct multifrontal QR, an inner-outer iterative method, and CGLS iterative method with a diagonal preconditioner and Robust Incomplete Factorization (RIF) preconditioner. [ABSTRACT FROM AUTHOR]

The present investigation was proposed to mitigate the falsification of certificates when presented within the curriculums and to generate confidence in the company due to the official validity of the smart certificate. It was developed under the Moodle online teaching platform, so that all students who complete their course or technical career can download their certificate and be verified by means of a QR code that will be read by the mobile application and / or by the website to check the existence and originality of the aforementioned certificate. With a quantitative approach and cross-sectional nonexperimental research design, a prototype was obtained with the Moodle-based platform, where the certificates obtained by the enrolled student at the conclusion of a course are generated. Likewise, the design of the web and mobile application for the android operating system was carried out, obtaining as results, the aforementioned final applications, which by means of a QR code, verify the information presented by the certificate in the Moodle database, obtaining in response, the official validity of the certificate issued by the educational institution. [ABSTRACT FROM AUTHOR]

This paper shows that adverbial particles are divided into the "strong" and "weak" types depending on how they behave in the context of argument ellipsis. In the argument ellipsis construction, the strong type of adverbial particle (dake 'only') does not allow a null argument to include its adverbial meaning, while the weak type of adverbial particle (sae 'even') allows a null argument to include the adverbial meaning optionally. We argue that the adverbial particle dake 'only' (which belongs to the strong type) projects to its maximal projection taking its host DP as a complement after QR, while the particle sae 'even' (belonging to the weak type) is adjoined to its host DP by QR without projecting any further. The divergence in the behavior of adverbial particles can be accounted for only if null arguments are interpreted with reference to the LF structures of their antecedent arguments. The data regarding the two types of adverbial particles provide substantial evidence that allows us to choose the LF copying analysis over the other alternative syntactic analyses. [ABSTRACT FROM AUTHOR]

We present efficient and scalable parallel algorithms for performing mathematical operations for low-rank tensors represented in the tensor train (TT) format. We consider algorithms for addition, elementwise multiplication, computing norms and inner products, orthonormalization, and rounding (rank truncation). These are the kernel operations for applications such as iterative Krylov solvers that exploit the TT structure. The parallel algorithms are designed for distributedmemory computation, and we propose a data distribution and strategy that parallelizes computations for individual cores within the TT format. We analyze the computation and communication costs of the proposed algorithms to show their scalability, and we present numerical experiments that demonstrate their efficiency on both shared-memory and distributed-memory parallel systems. For example, we observe better single-core performance than the existing MATLAB TT-Toolbox in rounding a 2GB TT tensor, and our implementation achieves a 34× speedup using all 40 cores of a single node. We also show nearly linear parallel scaling on larger TT tensors up to over 10,000 cores for all mathematical operations. [ABSTRACT FROM AUTHOR]

Real-time object tracking is an important step of many modern image processing applications. The efficient hardware design of real-time object tracker must achieve the desired accuracy while satisfying the frame rate requirements for a variety of image sizes. The existing methods of visual tracking employ sophisticated algorithms and challenge the capabilities of most embedded architectures. Discriminative scale space tracking is one algorithm that is capable of demonstrating good performance with affordable complexity. It has a high degree of parallelism which can be exploited for efficient implementation of reconfigurable hardware architectures. This paper proposes a real-time implementation of the discriminative scale-space tracker on FPGA for the major blocks. A careful design exploration of core mathematical operations of the tracking algorithm is performed to improve their hardware utilization and timing performance. Among the core functional units optimized in this work, the discrete Fourier transform achieves a computational time improvement of 92% relative to existing works, QR factorization achieves a 2.3 × reduction in resource utilization, and singular value decomposition yields a 3.8 × improvement in processing time. The proposed data path architecture is designed using Vivado HLS tool set and implemented for Zync Zed Board (xc7z020clg484-1). For an input image size of 320 × 240, the proposed architecture achieves a mean 25.38 fps. [ABSTRACT FROM AUTHOR]

IntroductionAugmented reality (AR) is a modern technology by which the recipient is really re-living the experience, as if they are a part in his home environment. The user opens up virtual 3D shapes by adding multimedia content (such as the texts, images, graphics, audio files, video clips, and 3D shapes) "that are not supported by printing. This makes the user take note of new information and data, whether they are textual or visual ones. That the user becomes an important part of it. This is either through advertisements that take the reader to online links via QR codes, or through applications that use Detection techniques, so that a specific application identifies a character in a newspaper or in a paper, and then moves the character through the programmed applicationso that the AR in Ads is not only an ideal for promoting sales, but also it is dedicated for building the company's reputation.Research Problem:- Products in the paper print are always seen as static and motionless, and there is no much interaction between them and the body senses that we can touch, see, and sometimes taste or even smell, however, it remains static. The question is how can we take advantage of the modern and innovative RA techniques and its applications in the printed ads to attract the customer's awareness?Objectives:-- Use AR to create Creative Print Ads that are free from traditional methodsResults:-- RA Technology is easy to apply on the ground, especially in the print ads, since the recipient has no longer needed to use 3D VR Virtual Reality Glasses to actually experience the RA.-RA Technology may be considered one of the most advanced technologies is expected and most likely to shape the future of advertising.Keys: -1- Augmented reality (AR) is an interactive experience of a real-world environment where the objects that reside in the real-world are "augmented" by computer-generated perceptual information" to provide additional information or serve as a router.2. Printed ads : anything written in the print media to attract the attention of the targeted audience by what is known as the printed ads.

Barcodes are playing a significant role in different industries in the recent years and among the two most popular 2D barcodes, the QR code has grown exponentially. The QR-DN1.0 dataset includes 5 categories of QR codes that will cover low to high density levels. Each group has 15 QR codes: 5 images for testing and 10 images for training. After embedding the QRs into 30 color images using blind watermarking techniques and then extracting the QRs from the images taken with the mobile phone camera with three different methods, we will have three groups of 2250 extracted QR images, which provides a total of 6750 distorted and noisy QR images. In each of the mentioned three categories, the data is divided into two parts: testing, with 750 images, and training, with 2250 images. For every distorted QR in the dataset, a non-distorted instance of it is placed as a ground truth. One of the advantages of this data set is that it is real. Because no simulated noise has been added to the images and this dataset is completely derived from the real word challenge of extracting embedded QRs in color images captured from the watermarked image on the screen. It also includes various types of QRs such as single character, short sentence, long sentence, URL and location.

The problem of the study is to identify the role of the communicator with government banking institutions in strengthening and disseminating the use of the QR Code in financial transactions for individuals from small traders, through a qualitative study to identify the persuasive methods used by the communicator and the luring used and the disclosure of the most used industrial sectors, and the sources through which the contact obtains information about the use of the QR code in the financial transactions of individuals from small traders, the directions of the contact of government banking institutions towards the use of the QR code and the extent of their actual use of the QR code in their own financial transactions, and the disclosure of the procedures they followed government banking institutions to qualify the caller to carry out this task and know the factors affecting the adoption of the rapid response code in financial transactions by individuals, as well as identifying the obstacles that stand in the way of publishing and using the rapid response code in financial transactions for individuals from small traders, and finally monitoring the proposals of the caller to banking institutions towards how activate more technology for you in the future. [ABSTRACT FROM AUTHOR]

We consider the computation of roots of polynomials expressed in the Chebyshev basis. We extend the QR iteration presented in [Y. Eidelman, L. Gemignani, and I. Gohberg, Nu-mer. Algorithms, 47 (2008), pp. 253-273] introducing an aggressive early deflation strategy, and showing that the rank-structure allows one to parallelize the algorithm, avoiding data dependencies which would be present in the unstructured QR. We exploit the particular structure of the colleague linearization to achieve quadratic complexity and linear storage requirements. The (unbalanced) QR iteration used for Chebyshev rootfinding does not guarantee backward stability on the polynomial coefficients, unless the vector of coefficients satisfy ||p|| ≈ 1, a hypothesis which is almost never verified for polynomials approximating smooth functions. Even though the presented method is mathematically equivalent to the unbalanced QR algorithm, we show that exploiting the rank structure allows one to guarantee a small backward error on the polynomial, up to an explicitly computable amplification factor 71(p), which depends on the polynomial under consideration. We show that this parameter is almost always of moderate size, making the method accurate on several numerical tests, in contrast with what happens in the unstructured unbalanced QR. [ABSTRACT FROM AUTHOR]

Abuse is not only done to copy or distribute data but also to the digital copyright labels. There is a way to protect data by inserting or hiding a piece of certain information, namely a watermarking technique. In this paper, we propose audio watermarking with Quantization Index Modulation (QIM) method as an embedding process combined with Compressive Sampling (CS), Discrete Sine Transform (DST) and QR decomposition. Binary image is used as a watermark inserted in host audio. DST is used for transformation process from time domain to frequency domain, while QR is used to decompose onedimension matrix into two-dimension matrix. Meanwhile, CS is used to obtain the compressed watermark file which is done before the embedding process. QIM method is used to embed the watermark file to the audio host file. Simulation results indicated that the proposed audio watermarking technique has good robustness against some attacks such as Low Pass Filter (LPF), resampling and linear speed change. In addition, it provides good performance in terms of imperceptibility with Signal to Noise Ratio (SNR) > 20 dB and capacity C = 689 bps.

The technology of creating and recognizing QR codes has been widely used in domestic business, marketing, social projects, and has become an innovative tool for disseminating and retrieving information in the educational environment. The article analyzes the degree of study of QR codes in the scientific literature, identifies historical features, uses, highlights the content of information encoding, points out the difference between static and dynamic submission of output data, examines the forms of organization of learning activities using two-dimensional bar codes, and also describes and presents examples of the use of this tool in the educational process by teachers of higher education institutions. The survey found that students have experience in using QR-codes in the banking or tourism sector as an opportunity to obtain comprehensive information about goods and services. Unfortunately, only 9% of respondents used QR codes in their educational activities. The pedagogical purpose of using the technology of QR-codes is determined by the possibility of implementing intensive forms and methods of vocational training, increasing the motivation of educational activities through the use of modern means of reading, processing, reproduction of information, raising the level of theoretical basis of perception of the data, formation of skills to implement various forms of independent activity in collecting and processing the necessary content. In the process of pedagogical experiment, which was conducted among the students of the direction of training «014.09 Secondary education. Informatics» Pavlo Tychyna Uman State Pedagogical University found that the technology of using QR-codes have sufficient potential during the activation of educational activities, allowing to increase the level of professional competences of the future teacher of informatics, ensuring the efficiency and quality of the educational process.

Effective prediction of wind power output intervals can capture the trend of uncertain wind output power in the form of probability, which not only can avoid the impact of randomness and volatility on grid security, but also can provide supportable information for grid dispatching and grid planning. To address the problem of the low accuracy of traditional wind power interval prediction, a new interval prediction method of wind power is proposed based on PSR-BLS-QR with adaptive rolling error correction. First, one-dimensional wind power data are mapped to high-dimensional space by phase space reconstruction (PSR) to achieve data reconstruction and the input and output of the broad learning system (BLS) model are constructed. Second, the training set and the test set are divided according to the input and output data. The BLS model is trained by the training set and the initial power interval of training data is constructed by quantile regression (QR). Then, the error distribution of nonparametric kernel density estimation is constructed at different power interval segments of the interval upper and lower boundaries, respectively, and the corresponding error-corrected power is found. Next, the optimal correction index is used as the objective function to determine the optimal error correction power for different power interval segments of the interval upper and lower boundaries. Finally, a test set is used for testing the performance of the proposed method. Three wind power datasets from different regions are used to prove that the proposed method can improve the average prediction accuracy by about 6–14% with the narrower interval width compared with the traditional interval prediction methods.

Purpose: Attempts at engaging relatives of glaucoma patients in education and screening have had limited success. This study explores the feasibility of an electronic intervention to facilitate direct yet reliable glaucoma risk communication between open-angle glaucoma patients (probands) and their first-degree relatives (FDRs)., Design: Prospective survey and assessment of intervention., Participants: Fifty adult probands, engaging 140 FDRs., Methods: Phase I was an iterative process involving creating a customized website and Quick Response (QR)-code-based intervention designed with input from probands, FDRs of patients, community members, and researchers. In phase II, the intervention was deployed in a clinical setting; this involved recruiting probands who had a smartphone and were willing to use the QR-code to message their FDRs a standard message, including a website link about glaucoma risk in FDRs and the importance of getting examined. Follow-up interviews were conducted with probands 1 to 2 weeks after their clinic visit to assess the impact of the intervention. Demographic data, website analytics, and participant feedback were collected and analyzed., Main Outcome Measures: Increased awareness of glaucoma risk among FDRs and enhanced discussions., Results: At the time of the first interview, probands reported that 70% of the FDRs were aware of the probands' glaucoma diagnosis, but only 26% had undergone glaucoma screening. Ninety percent of probands had no issues using the QR-codes. Website analytics recorded 73 visits from 51 distinct internet protocol addresses (IPs). After receiving the standard message, 95% of FDRs followed up with the probands, actively discussing glaucoma. Of the probands, 84% completed the follow-up interview 1 to 2 weeks after enrollment. Fifty-nine percent of the FDRs were reported to have scheduled screening appointments. The collected feedback revealed that 96% of probands found the intervention helpful, fostering glaucoma discussions with their FDRs and improving probands' comfort level in discussing health issues with FDRs from baseline (very comfortable: 88%, comfortable: 8%, neutral: 2%, and very uncomfortable: 2%) to the follow-up interview (very comfortable: 98% and comfortable: 2%)., Conclusions: This innovative online method of communicating the risk of glaucoma to FDRs of probands prompted and increased the comfort level of familial discussions of glaucoma. More than half of FDRs reported making an appointment to get screened for glaucoma., Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article., (Copyright © 2023 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)

A novel adaptive gray scale image watermarking approach based on the combination of machine learning (ML) algorithms in wavelet domain is presented. Based upon fuzzy entropy information, non-overlapping and significant regions are selected. Lifting wavelet transform (LWT) is performed on selected significant regions in order to obtain low frequency sub band and underwent through the QR factorization. Prominent low frequency features of each region are supplied as input features for the training purpose of Lagrangian twin support vector regression (LTSVR) model. Then the optimal value of watermark scaling factor (strength) obtained using genetic algorithm (GA) is used to embed the watermark in the test data of output wavelet coefficient obtained by trained LTSVR. Arnold transformation is performed for the security of watermark along with the imperceptibility and robustness. The experimental results as well as the comparison between traditional methods and the proposed one showed a significant improvement in robustness in terms of image processing attacks which makes it suitable for implementing copyright protection applications. [ABSTRACT FROM AUTHOR]

Objective: Although cholesterol transported through the blood in the human body has many benefits, it can cause many diseases when it exceeds the normal level. The aim of this study is to determine the factors affecting the total cholesterol level by using classical regression and quantile regression (KR) methods, which have been interested in recent years, and to compare their results. Material-Method: The Power analysis performed in this study was made by the GPower program. Totally 403 patients were enrolled in the study. The descriptive statistics were calculated and the classical regression model was created by the SPSS program. However, the assumptions of the Ordinary Least Squares (OLS) method were not met. Therefore, three quantile regression (QR) models were established by Eviews 9.0 program. Results: According to the results of the model in 0.25 quantile; second diastolic blood pressure (BP_2D), cholesterol/HDL ratio (RATIO), and HDL were observed to have a positive effect. In the 0.50 quantile model; variables BP_2D, RATIO, and HDL has a positive effect, and HEIGHT has a negative effect. In the last model, which was made with 0.75 quantile value, it was observed that RATIO and HDL variables had a positive effect. Conclusions: According to the models established for all 3 quantile values, factors having a common effect on cholesterol are RATIO and HDL. Thus, it can be said that the results of two different regression methods are consistent with each other. [ABSTRACT FROM AUTHOR]

Many patients with atopic dermatitis and cholinergic urticaria display an immediate-type allergy to autologous sweat. Although the histamine release test (HRT) using semi-purified sweat antigen (QR) was available for the detection of immediate sweat allergy, the existence of HRT low responders could not be disregarded. Furthermore, it has not been established whether the results of the HRT are consistent with the autologous sweat skin test (ASwST). We aimed to compare the HRT and basophil activation test (BAT) for the diagnosis of immediate sweat allergy. The HRT and BAT were performed on 47 subjects (35 ASwST positive, 12 negative) whose symptoms had worsened on sweating. For the BAT, blood was incubated with QR or crude sweat and CD203c upregulation was assessed. A commercial HRT was performed and histamine release induced by QR was quantified. When excluding non-responders for anti-IgE antibody, the BAT using QR and the HRT had a sensitivity of 100% and 44% and specificity of 75% and 100%, respectively. The BAT and HRT had a positive predictive value of 91.3% and 100% and negative predictive value of 100% and 30%, respectively. The BAT detected 0% non-responders, whereas the HRT identified 22.5%. When using crude sweat for the BAT, the false-positives observed when using QR were not detected. The BAT using QR displayed a higher sensitivity and negative predictive value and a lower number of non-responders compared with the HRT. Furthermore, the BAT using crude sweat can also be an alternative tool for the ASwST. [ABSTRACT FROM AUTHOR]

In this paper, a quasi-resonant (QR) flyback primary-side regulation (PSR) converter with adaptive frequency control is proposed. The converter adopts the PSR scheme to detect load information through the auxiliary winding. The converter employs the QR control scheme to switch in the valley mode either in CV or CC operation, which greatly reduces the switching loss. In addition, according to the load condition, the converter adaptively reduces the switching frequency and realize valley switching, which achieves better light-load efficiency in the CV mode. The proposed QR converter was implemented using the HHGRACE 0.35 μm BCD process and verified in a 5 V/1A circuit prototype. Experimental results show that the light-load power efficiency of the proposed converter is improved by up to 4.0% when compared to the conventional QR controller. In addition, the valley switching is realized under different load conditions, which improves the system efficiency in the entire range of output load. [ABSTRACT FROM AUTHOR]