Index Measurements Research Articles

An integrated blockchain and fractional DCT based highly secured framework for storage and retrieval of retinal images

The digital image capability of storing large amount of data has resulted in it’s increased popularity. Images are used to transmit large amount of information across different geographical locations using different cloud services. Securing these digitally stored images has remained a challenging task for researchers as they are prone to cyber- attacks. A potential solution to this problem can be blockchain, which provide secure and unchangeable storage. However, securing images on blockchain has another challenge as the image size increases the associated cost involved in blockchain. Fractional Discrete Cosine Transform(fctDCT) has the capability to minimizes the amount of data necessary for expressing an image in a secure way. This paper presents a novel framework for securely storing and retrieving medical images by extracting feature maps from medical images by fctDCT, followed by encoding and storing the feature map on decentralized cloud and linking them on blockchain. The integration has been implemented by using four different α angles which are stored on blockchain and are needed to be same at storage and retrieval stage as only the authentic user would have access to unique α angles and number of coefficients that have been used in storing their medical images. The performance of proposed framework has been evaluated by employing image quality metric such as Mean Square Error (MSE), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and multi-SSIM by comparing it with correct and incorrect α values on four different values of α.

Prevalence and Risk Factors of Caries among Children of Moroccan Schools

Introduction: The purpose of this study is to describe the oral health status of schoolchildren, while focusing on the relationship between carious prevalence and the two risk factors which are obesity and passive smoking. Materials and Methods: A cross-sectional survey was conducted in primary school of Casablanca, Morocco. A total of 1003 schoolchildren aged between 6 to 12 years old were examined in their classrooms in daylight. The questionnaire was used to collect information about socio-demographic status, oral health practice consumption of sweets and passive smoking. Dental caries was assessed using the decayed, missing and filled teeth (dmft, DMFT) index, and oral hygiene status by the simplified oral hygiene index OHI. The obesity was defined based to the measurement of BMI index. Results: The caries prevalence was 57.7% in temporary dentition and 43% in permanent dentition. The caries index was dmft= 2.44 and DMFT= 1.3. Higher Caries prevalence was associated with poor oral hygiene, increased consumption of sweets; however, caries prevalence in temporary and permanent dentition was lower in children with obesity (5,5% and 4,9% respectively), and exposed to passive smoking (25,4%,31,8% respectively).

Weighted Asymmetry Index: A New Graph-Theoretic Measure for Network Analysis and Optimization

Graph theory is a crucial branch of mathematics in fields like network analysis, molecular chemistry, and computer science, where it models complex relationships and structures. Many indices are used to capture the specific nuances in these structures. In this paper, we propose a new index, the weighted asymmetry index, a graph-theoretic metric quantifying the asymmetry in a network using the distances of the vertices connected by an edge. This index measures how uneven the distances from each vertex to the rest of the graph are when considering the contribution of each edge. We show how the index can capture the intrinsic asymmetries in diverse networks and is an important tool for applications in network analysis, optimization problems, social networks, chemical graph theory, and modeling complex systems. We first identify its extreme values and describe the corresponding extremal trees. We also give explicit formulas for the weighted asymmetry index for path, star, complete bipartite, complete tripartite, generalized star, and wheel graphs. At the end, we propose some open problems.

Role of Zinc Alpha2-Glycoprotein and Retinol-Binding Protein-4 in Iraqi Women with Thyroid Dysfunctions

Thyroid dysfunction (TD) and diabetes mellitus (DM) are two of the most frequent chronic endocrine disorders. This study included 60 women with thyroid disorders: 30 with hypothyroidism and 30 with hyperthyroidism, aged between 20 and 40 years. This study used 30 healthy women aged 20-40 years as a control group. Anthropometric measurements of Body Mass Index (BMI), hematological analysis of glycated hemoglobin (HbA1c), biochemical parameters (Thyroid-stimulating hormone TSH, Free triiodothyronine FT3, Free thyroxine FT4, Fasting Blood Sugar FBS), and adipokine concentrations zinc-α2-glycoprotein (AZGP-1) and retinol-binding protein-4 (RBP-4) were performed for all participants. The results revealed that the serum levels of zinc-α2-glycoprotein and retinol-binding protein-4 are significantly higher in hyperthyroidism (P<0.0001) compared to both healthy and hypothyroid women. Besides that, zinc-α2-glycoprotein has a negative correlation with TSH in the hyperthyroidism group. In the hypothyroidism group, it correlates positively with retinol-binding protein-4. In addition to that, retinol-binding protein-4 is positively correlated with FT3 and FT4 and negatively correlated with BMI in the hyperthyroidism group. For this reason, we conclude that these adipokines can aid in the diagnosis and monitoring of thyroid disorders, thereby preventing the onset of disease complications associated with type 2 diabetes mellitus. It is important to highlight that women with hypothyroidism are more likely than those with hyperthyroidism to develop diabetes.

Validity and reliability of the physical fitness test instrument for retired martial art athletes

Background and Study Aim. Developing exercise programs to maintain the fitness and health of retired athletes is crucial as a preventive measure against common health problems in this population. Equally important is the creation of an exercise evaluation tool to assess the effectiveness of these programs. This study aims to test the validity and reliability of a physical fitness test instrument for retired martial arts athletes. Material and Methods. This study used an evaluation approach with data collected through tests and measurements. A total of 147 subjects participated. For validity testing, there were 35 retired male martial arts athletes and 37 retired female athletes. For reliability testing, there were 36 retired male and 39 retired female martial arts athletes. The instruments used included body mass index (BMI) measurements with digital scales, flexibility measurements with the sit-and-reach test, muscle strength measurements with a leg and back dynamometer, and cardiovascular endurance measurements with the Cooper test. Validity was assessed using a concurrent validity approach. Reliability was tested using the test-retest method. The Pearson product-moment correlation was used for validity analysis, while Cronbach's alpha was used to assess reliability. The JASP software was used for the analysis. Results. For male athletes, the r-values for each test item exceeded the r-table value of 0.275, confirming the validity of the body mass index (BMI), sit-and-reach test, leg and back dynamometers, and the Cooper test. Similarly, female athletes demonstrated r-values above the r-table value of 0.267, confirming the validity of all test items. The reliability of each item was confirmed by Cronbach’s alpha values, which were above the 0.7 threshold for both male and female athletes. The Cronbach's alpha value for BMI was 0.998 for both male and female athletes, indicating excellent reliability. Other test items, such as flexibility and muscle strength, also showed strong reliability, with Cronbach’s alpha values ranging from 0.742 to 0.985. Conclusions. The study highlights the importance of developing valid and reliable instruments to assess the physical fitness of retired martial arts athletes. Such instruments are essential for monitoring the effectiveness of training programs aimed at maintaining the health and fitness of retired athletes. The findings of this research confirm the value of structured fitness tests. These tests effectively evaluate key physical components such as body composition, flexibility, muscle strength, and cardiovascular endurance.

Seismic Random Noise Attenuation Using DARE U-Net

Seismic data processing plays a pivotal role in extracting valuable subsurface information for various geophysical applications. However, seismic records often suffer from inherent random noise, which obscures meaningful geological features and reduces the reliability of interpretations. In recent years, deep learning methodologies have shown promising results in performing noise attenuation tasks on seismic data. In this research, we propose modifications to the standard U-Net structure by integrating dense and residual connections, which serve as the foundation of our approach named the dense and residual (DARE U-Net) network. Dense connections enhance the receptive field and ensure that information from different scales is considered during the denoising process. Our model implements local residual connections between layers within the encoder, which allows earlier layers to directly connect with deep layers. This promotes the flow of information, allowing the network to utilize filtered and unfiltered input. The combined network mechanisms preserve the spatial information loss during the contraction process so that the decoder can locate the features more accurately by retaining the high-resolution features, enabling precise location in seismic image denoising. We evaluate this adapted architecture by applying synthetic and real data sets and calculating the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). The effectiveness of this method is well noted.

Cortical Alterations Associated with Executive Function Deficits in Youth with a Congenital Heart Defect

Abstract Adolescents and young adults born with a complex congenital heart defect (CHD) are at risk for executive function (ExF) impairments, which contribute to the psychological and everyday burden of CHD. Cortical dysmaturation has been well described in fetuses and neonates with CHD and early evidence suggests that cortical alterations in thickness, surface area, and gyrification index are non-transient and can be observed in adolescents with CHD. However, cortical alterations have yet to be correlated with ExF deficits in youth with CHD. This study aims to use a data-driven approach to identify the most important cortical features associated with ExF deficits in adolescents and young adults with CHD. To do so, we combined two comparable datasets acquired at the Research Institute of the McGill University Health Centre and the University Children’s Hospital Zurich each including both youth with CHD and healthy controls. For each participant, a high-resolution T1-weighted magnetic resonance image, a self-reported ExF assessment (the Behaviour Rating Inventory of Executive Function— Adult Scale), and their clinical and demographic characteristics were available. Corticometric Iterative Vertex-Based Estimation of Thickness (CIVET) was used to extract cortical thickness, cortical surface area, and local gyrification index measures. Using orthogonal projective non-negative matrix factorization (OPNMF), we identified non-overlapping spatial components that integrate cortical thickness, cortical surface area, and local gyrification index and capture structural covariance across these features. Behavioural partial least squares correlation (bPLS) analysis was then used to compute correlations between the individual variability in the OPNMF covariance patterns and ExF outcomes for each subject. A total of 56 youth with CHD who underwent cardiopulmonary bypass surgery before three years of age and 56 age- and sex-matched healthy controls were included in our analyses. Cortical grey matter volume, cortical thickness, and cortical surface area were found to be significantly reduced in CHD patients compared to controls. OPNMF identified 12 stable cortex-wide components summarizing the inter-subject variability in cortical thickness, cortical surface area, and local gyrification index. bPLS revealed two significant latent variables (LV) accounting for a total of 82.8% of the variance in the sample, each describing distinct patterns between the brain and cognitive data. LV1 summarized a pattern of belonging to the CHD group, worse scores on most BRIEF-A scales, younger age at MRI, and female sex. This pattern was associated with increased cortical thickness, local gyrification index, and decreased cortical surface area in several OPNMF components. Finally, we identified a positive relationship between the LV1 brain-behaviour pattern and total aortic cross-clamp time in the CHD group, indicating that longer aortic cross-clamp time was associated with worse neurodevelopmental outcomes. In this study, we uncover novel multivariate relationships between ExF and alterations in cortical thickness, surface area, and local gyrification index in adolescents and young adults with CHD using a data-driven approach. Although our findings highlight the important role played by the cortex in higher order cognitive processes, future studies are needed to elucidate the individual contribution of individual and clinical attributes into the deficits observed in this population.

Polarization-maintaining fiber based macehead shaped interferometric sensor for accurate measurement of refractive index and temperature

A macehead-shaped bent polarization-maintaining fiber-based interferometric sensing structure called MBPIS is described and experimentally demonstrated for precise temperature and refractive index measurement. The sensor’s working principle is explained by simulating the spatial distribution of the field intensity in straight and bending PANDA fibers. A maximum extinction ratio (∼21 dBm) for the interference dip wavelength (1527.825 nm) in the sensor’s output spectrum was optimized by manipulating the birefringence of propagating fiber modes by adjusting PMF’s bending diameter from 17 to 11 mm. The phase difference changes between these fiber modes due to temperature and RI-induced birefringence cause a shift in the interference spectrum. The sensor’s highest RI sensitivity has been seen at −259.32 nm/RIU for a wide range of analytes from 1.3333 to 1.3579. In contrast, the highest temperature sensitivities evaluated for the temperature range of 0 ∼ 100 ℃ are −220 pm/℃ and −0.139 dBm/℃, respectively.

Echocardiographic insights redefining risk in pulmonary arterial hypertension: a focus on right atrial volume index for enhanced stratification

Abstract Introduction In Pulmonary arterial hypertension (PAH), the right atrium plays a critical role, and its size, determined by echocardiography, is crucial for risk stratification. Despite this, current guidelines still prioritize right atrial area (RAA) over the right atrial volume index (RAVI). This approach is contrary to the recommendations of international echocardiography societies since 2016, which advocate for the use of RAVI for a more accurate assessment. Purpose Identify the RAVI value corresponding to the RAA, in PAH risk stratification used in the 2022 ESC guidelines. Methods We conducted a retrospective analysis of all consecutive patients of a single-center, since 2002. Patient's echocardiograms were revised for simultaneous assessment of RAA and right atrial volume index (RAVI). Over an average follow-up of 6.7 years (SD 5.9), we recorded a cohort of 82 patients diagnosed with PAH. From this group, we excluded 27 patients with congenital etiologies, 14 due to the insufficient quality of echocardiographic data, and one patient identified as an extreme statistical outlier. A Pearson's correlation analysis was used to access the correlation between RAA and RAVI for PAH diagnosis. Results A total of 40 patients were included with a mean age at diagnosis of 48.85 years (SD 17.82), predominantly female (77.5 %). The most prevalent etiologies were idiopathic (32.5%) and connective tissue disease-associated PAH (27.5%). Clinical presentations included right heart failure signs in 30% of patients, rapid symptom progression in 12.5%, syncope history in 15% and 77.5% in WHO-FC III-IV. Average 6-MWD and NT-proBNP levels were 392,1 m (SD 120,2) and 1636,18 ng/L (SD 2576,14), respectively. Average hemodynamics parameters were right atrial pressure 7,39 mmHg (SD 4,940); cardiac index 2,28 L/min/m2 (SD 2,06); stroke volume index 3,38 mL/m2 (SD 3,92) and mixed venous oxygen saturation 65,68% (SD 10,86). Average echocardiographic parameters were RAA 20,14 cm2 (SD 4,80); TAPSE/sPAP 0,34 mm/mmHg (SD 0,18) and RAVI 37,78 mL/m2 (SD 13,67), with 10% of pericardial effusion. Statistical analysis revealed a strong and significant correlation between RAA and RAVI (r=0.82, 95% CI: 0.69-0.90, p<0.001). The derived linear relationship is expressed as "y=2.8*X -18". Therefore, an RAA value of 18 cm² translates to a RAVI of 32 mL/m², while an RAA of 26 cm² corresponds to a RAVI of 55 mL/m². Conclusion Our study supports a revision in HAP risk assessment guidelines, suggesting a shift to a more comprehensive approach using right atrial volume index (RAVI) measurements. We propose categorizing risk as low for RAVI < 32 mL/m², intermediate for RAVI between 32 and 55 mL/m², and high for RAVI > 55 mL/m². This recommendation aligns with the standards of international societies and is grounded in best clinical practices, considering that indexing measurements of the right atrium to body size potentially offers greater accuracy than absolute values.

Functional improvement of non-infarct related coronary artery stenosis by extensive LDL-C reduction with a PCSK9 antibody: the FITTER trial, microvascular function analysis

Abstract Background Atherosclerosis and microvascular dysfunction are closely linked. Moreover, impaired microvascular function is strongly associated with increased risk on major adverse cardiac events. In patients presenting with acute coronary syndrome (ACS), microvascular function is reduced. PCSK9-inhibitors have shown to reduce plaque burden and lipid load in epicardial vessels and might exhibit similar results on microvascular vessels, thereby improving microvascular function. The FITTER trial offers the unique opportunity to test this hypothesis. Methods The FITTER trial is a multi-center, randomized, double blind, placebo controlled clinical trial for patients presenting with ACS and multi-vessel disease (MVD). After treatment of the culprit lesion, fractional flow reserve (FFR) measurement of non-infarct related artery (non-IRA) lesions was performed. Patients with intermediate, non-critical lesions (FFR: 0.67-0.85) were included in this trial. For exploratory purpose, additional physiological assessment of the non-IRA included coronary flow reserve (CFR) and microvascular resistance index (IMR) measurements. Microvascular function was evaluated using a pressure- and temperature-sensitive guidewire and a bolus thermodilution method. Participants were randomized and treated for 12 weeks with either evolocumab or placebo in addition to high-intensity statin therapy. Staged reevaluation was done at 12 weeks. After repeated physiology testing, PCI was performed if deemed necessary. Pre-defined exploratory analysis includes the absolute and relative difference in change between CFR and IMR from baseline to follow up in the non-IRA. PCSK9 inhibition might result in a relatively larger increase of CFR and larger decrease of IMR. Results Between March 2020 and August 2023, a total of 150 patients were included in the trial. In 61 patients (88.5% male, age 65.3 ± 9.1 years, 23.0% STEMI, 70.5% non-STEMI, 6.6% UAP) successful baseline and follow-up measurements of microvascular function were performed. Complete results will be available at the beginning of March 2024. The primary- and secondary endpoints will be submitted for late-breaking clinical trials selection. The results of this abstract will include a per vessel analysis of coronary artery microvascular function. Conclusion The FITTER trial will provide new insights on the potential of extensive LDL-C reduction with a PCSK9 antibody on microvascular coronary artery function in patients presenting with ACS and MVD.

Overlapping markets and quality competition among community health centers.

To examine the response of community health center (CHC) quality to quality levels at neighboring CHCs in the presence of non-price competition. A quasi-experimental study of US community health centers. Outcome variables were indices that measured overall quality of CHC care. Using patient flow data, we constructed CHC-specific Hirschman-Herfindahl index (HHI) and competitors' composite quality measure. The plausibly exogenous change in characteristics of "competitors' competitors" was exploited to identify the relationship between competition and quality of care, using a generalized two-stage least square model with instrumental variables. Using the Health Center Program Uniform Data System (2014-2018), linked with American Community Survey and Medical Expenditure Panel Survey, we analyzed 1098 unique federally funded CHCs in 50 states and District of Columbia which had at least one neighboring CHC and had non-missing data for 2015-2018 (4226 CHC-years). Most of CHCs served populations in overlapping geographic markets, with median market concentration decreasing during the study period. A one-percent increase in competitors' quality was associated with a 0.71-percent increase in an index CHC's composite quality (p < 0.01), consisting of a 0.59-percent increase in chronic condition control rates (p < 0.01); a 0.68-percent increase in the screening and assessment rates (p < 0.01); and a 0.78-percent increase in medication management rates (p < 0.01). The association was stronger at CHCs serving a smaller proportion of uninsured patients. No significant quality reaction was observed at CHCs with a percentage of uninsured patients larger than the 75th percentile. We observed no significant associations between HHI and quality. Increasing competition does not harm quality of care at CHCs. A CHC appears to improve its quality if its competitors improved quality. The beneficial quality effect was less pronounced in CHCs providing a significant proportion of care to uninsured patients, suggesting lack of incentives faced by these CHCs.

Isolation, Screening and Identification of Biosurfactant Producing Strain Nocardiopsis dassonvillei var B2 From Oil Contaminated Soil.

Petroleum and other oil manufacturing industries contribute to environmental pollution by releasing hazardous hydrocarbons. Biosurfactants offer a sustainable solution for mitigating oil pollution through emulsification processes, safeguarding agricultural soils, aquatic ecosystems, and human health. This study focuses on isolating, screening, and identifying actinomycetes producing biosurfactant from oil-polluted soil in the naval dockyard of Visakhapatnam. Biosurfactant production was successfully achieved utilizing Kim's medium, which was supplemented with olive oil serving as the carbon source. The evaluation involved preliminary identification tests, including oil displacement, Parafilm-M, and lipase activity assays, using sodium lauryl sulfate as the standard reference. Surface tension and emulsification index measurements were conducted, and the chemical composition of glycolipids and phospholipids was elucidated using phenol-sulfuric acid and phosphate assays. Glycolipids, specifically identified as rhamnolipids, were confirmed via cetyltrimethylammonium bromide (CTAB) testing and quantitatively analyzed using the orcinol method. The cell-free broth exhibited antagonistic activity against Gram-positive and negative bacilli.16S rRNA sequencing-based phylogenetic analysis was carried out by the NCIM, Pune, with the gene sequence being deposited in GenBank. Further characterization of isolate B2 included scanning electron microscopy (SEM) analysis, as well as physiological and biochemical assays. This study highlights the ability of Nocardiopsis dassonvillei var. B2, isolated from oil-polluted soil, to produce biosurfactants, specifically glycolipids identified as rhamnolipids. Our findings represent the first reported instance of biosurfactant production from isolate B2 originating from the naval dockyard in Visakhapatnam, Andhra Pradesh, India.

Air quality index prediction with optimisation enabled deep learning model in IoT application

ABSTRACT The development of industrial and urban places caused air pollution, which has resulted in a variety of effects on individuals and the atmosphere over the years. The measurement of the air quality index (AQI) depends on various environmental situations, such as emissions, dispersions, and chemical reactions. This paper developed the Internet of Things (IoT)-based Deep Learning (DL) technique for predicting air quality. Initially, the IoT simulation is performed, where the nodes receive input data. The routing technique is used to identify the best route toward the Base station (BS). The proposed Tangent Two-Stage Algorithm (TTSA) is used in the routing mechanism. For AQI prediction, the time series data is transmitted to the BS. The Z-score normalisation is employed to neglect the unessential data. Furthermore, feature indicator extraction is employed to extract the relevant feature indicators. The Deep Feedforward Neural Network (DFNN) is used to predict air quality. Furthermore, the proposed Fractional Tangent Two-Stage Optimisation (FTTSA) is employed for the training process of DFNN. Moreover, metrics such as energy, time, and distance are used to evaluate the routing process, and superior results such as 0.979J, 0.025s and 0.196 m are obtained. Furthermore, the AQI is predicted by metrics like root mean square error (RMSE), R-squared (R2), mean square error (MSE), and mean absolute percentage error (MAPE), whereas the superior values such as 0.602, 0.598, 0.362, and 0.456 are attained.

Schiff base approach to introduce chitosan-phytic acid complex for flame-retardant cotton fabrics

In this study, chitosan was integrated onto cotton fabric fibers through a Schiff base reaction, followed by the in-situ generation of Chitosan-Phytic acid (CH-PA) complex to achieve green flame retardancy. The process began with oxidizing the fabric using sodium periodate (NaIO4) to create numerous aldehyde groups on the fiber surface. Subsequently, CH was grafted onto the fabric via a Schiff base reaction. The fabric was then immersed in a PA solution to form a CH-PA complex, resulting in a novel and highly efficient flame-retardant (FR) fabric. The structure of the treated fabric was analyzed by using Fourier-transform infrared spectroscopy (FTIR), Scanning electron microscopy (SEM), and energy-dispersive spectroscopy (EDS), confirming the successful formation of the desired structure. The thermal stability and flame retardancy of the fabric were systematically evaluated using thermogravimetric analysis (TGA), cone calorimetry (CONE), vertical combustion tests, and limiting oxygen index (LOI) measurements. The LOI increased from 17.6 % to 30.6 %, and vertical combustion tests demonstrated self-extinguishing capabilities when the fabric was treated by the NaIO4 solution at concentrations of 0.02 g/mL or higher. In the CONE test, the modified fabric showed significant improvements, with peak heat release rate (pHRR) and total heat release (THR) decreasing by approximately 80 % and 60 %, respectively. Comprehensive analysis indicated that the FR mechanism involved both gas phase and condensed phase actions. Further characterization of the material included tensile testing and wash resistance assessments. By comparing these findings with recent research on similar topics, the advantages and disadvantages of the materials were thoroughly evaluated. Notably, this work provides a robust experimental foundation and conceptual expansion for the green flame retardancy of cotton fabrics.

Image Denoising Using Deblur Generative Adversarial Network Denoising U-Net

Convolutional neural networks (CNNs) are becoming increasingly popular for image denoising. U-Nets, a type of CNN architecture, have been shown to be effective for this task. However, the impact of shallow layers on deeper layers decreases as the depth of the network increases. To address this issue, the authors propose a new image denoising method called DGANDU-Net. DGANDU-Net combines the DeblurGAN design with a U-Net architecture. This combination allows DGANDU-Net to effectively remove noise from images while preserving fine details. The authors also propose the use of two loss functions, mean square error (MSE) and perceptual loss, to improve the performance of DGANDU-Net. MSE is used to learn and improve the extracted features, while perceptual loss is used to produce the final denoised image. The authors evaluate the performance of DGANDU-Net on a variety of noise levels and find that it outperforms other state-of-the-art denoising algorithms in terms of both visual quality and two evaluation indices, including peak signal-to-noise ratio (PSNR) and Structural Similarity Index Measure (SSIM). Specifically, for extremely noisy environments with a noise standard deviation of 75, DGANDU-Net achieves an average PSNR of 37.39[Formula: see text]dB in the test dataset. The authors conclude that DGANDU-Net is a promising new method for image denoising that has the potential to significantly improve the quality of medical images used for diagnosis and treatment.

Physics-Driven Image Dehazing from the Perspective of Unmanned Aerial Vehicles

Drone vision is widely used in change detection, disaster response, and military reconnaissance due to its wide field of view and flexibility. However, under haze and thin cloud conditions, image quality is usually degraded due to atmospheric scattering. This results in issues like color distortion, reduced contrast, and lower clarity, which negatively impact the performance of subsequent advanced visual tasks. To improve the quality of unmanned aerial vehicle (UAV) images, we propose a dehazing method based on calibration of the atmospheric scattering model. We designed two specialized neural network structures to estimate the two unknown parameters in the atmospheric scattering model: the atmospheric light intensity A and medium transmission t. However, calculation errors always occur in both processes for estimating the two unknown parameters. The error accumulation for atmospheric light and medium transmission will cause the deviation in color fidelity and brightness. Therefore, we designed an encoder-decoder structure for irradiance guidance, which not only eliminates error accumulation but also enhances the detail in the restored image, achieving higher-quality dehazing results. Quantitative and qualitative evaluations indicate that our dehazing method outperforms existing techniques, effectively eliminating haze from drone images and significantly enhancing image clarity and quality in hazy conditions. Specifically, the compared experiment on the R100 dataset demonstrates that the proposed method improved the peak signal-to-noise ratio (PSNR) and structure similarity index measure (SSIM) metrics by 6.9 dB and 0.08 over the second-best method, respectively. On the N100 dataset, the method improved the PSNR and SSIM metrics by 8.7 dB and 0.05 over the second-best method, respectively.

Distinct Immunophenotypes in the DNA Index-Based Stratification of Pediatric B-Cell Acute Lymphoblastic Leukemia.

B-cell acute lymphoblastic leukemia (B-ALL) presents a challenge in hematological malignancies due to its heterogeneity, which impacts treatment outcomes. Stratification based on the DNA index (DNAi) categorizes patients into favorable prognosis (hyperploid), standard prognosis (normoploid), and uncertain or poor prognosis (hypoploid) groups. In this study, we explored whether specific immunophenotypic markers are associated with each DNAi-based group and their potential connection to prognostic categories, aiming to provide new insights that may contribute to a better understanding of prognosis in B-ALL. In this study, we utilized flow cytometry to analyze immunophenotypic markers and combined this with DNA index (DNAi) measurements to stratify pediatric B-ALL patients into distinct risk categories. Our methodology focused on accurately classifying patients into hyperploid, normoploid, and hypoploid groups based on their DNA content, facilitating a comparative analysis of immunophenotypic characteristics across these groups. Our analysis revealed that hypoploid B-ALL patients displayed a significantly lower percentage of cells in the S phase of the cell cycle compared to normoploid and hyperploid groups. Additionally, distinct immunophenotypic profiles were observed in hypoploid patients, characterized by higher expression levels of HLA-DR and a notable co-expression of CD34 and CD22. This study found that hypoploid B-ALL patients have distinct characteristics, such as lower S-phase cell percentages and specific immunophenotypic profiles, including higher HLA-DR expression and CD34/CD22 co-expression. These differences across DNA index-based prognostic categories warrant further research to explore their potential prognostic significance.

Integrated physiological and transcriptome analyses of the effects of water-soluble amino acid fertilizer on plant growth

Tobacco is a key component of China’s economy, serving as a major cash crop. With traditional fertilizers reaching their maximum potential in promoting tobacco growth, the exploration of new fertilizers has emerged as a viable solution for advancing experimental sustainable development. Spraying foliar fertilizer is a key measure to improve tobacco yield and quality. This study employed a combination of field and pot experiments to investigate the effects of applying water-soluble amino acid fertilizers on the growth, development, and quality of tobacco. The results of transcriptome analysis and physiological index measurements indicate that the application of water-soluble amino acid fertilizer can enhance the area of tobacco leaves, promote photosynthesis, and improve the chemical composition of the leaves. This research determined that the optimal concentration for spraying water-soluble amino acid fertilizer is diluted 500 times. Transcriptome analysis identified a total of 6,489 differentially expressed genes (DEGs), including 3,843 genes that were up-regulated and 2,646 genes that were down-regulated. Gene Ontology (GO)analysis demonstrated that these DEGs were significantlyassociatedwithprocessesincludingcell recognition, photosynthesis,thylakoidcomponents, calcium ion binding, and carbohydrate binding.Additionally, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis emphasized that the DEGs were largely found in pathwaysrelated tophotosynthesis-antenna proteins, interactions between plants and pathogens, photosynthesisitself, phenylpropanoid biosynthesis, andplant hormone signaling. Further research revealed that a significant number of genes involved in the auxin, gibberellin, salicylic acid, and jasmonic acid signal transduction pathways exhibited varying expression patterns following the application of water-soluble amino acid fertilizers.Additionally, the expression levels of bZIP, MYB, WRKY, bHLH, and AP2/ERF transcription factors exhibited significant variations following the application of water-soluble amino acid fertilizer. These results analyze the mechanisms of action of water-soluble amino acid fertilizers, offering new effective strategies to enhance both the yield and quality of tobacco.

Refractive index sensing characteristics of PCF-SPR based on dual-plasmon materials

Abstract In this paper, a photonic crystal fiber (PCF) refractive index sensor based on surface plasmon resonance with dual plasmonic materials (indium tin oxide and gold) is proposed. We innovatively designed a dual-core PCF structure and pore arrangement effectively enhancing the coupling effect. Using two different plasma materials, phase matching is achieved at two different wavelengths for the evanescent and surface plasmon waves, resulting in dual resonance peaks. The refractive index sensing is accomplished by measuring the dual-peak resonance shift, which expands the detection wavelength and RI detection ranges. The sensor can detect analytes with refractive indices ranging from 1.32 to 1.43 at wavelengths between 0.4 µm and 1.4 µm. We optimized the PCF structure and studied the sensing performance of the sensor, improving its sensitivity. Simulation results indicate that the designed PCF sensor exhibits outstanding maximum dual-peak shift sensitivity, reaching up to 28 000 RIU−1, along with maximum amplitude sensitivity and wavelength sensitivity of 18 500 RIU−1 and 34 500 RIU−1, respectively, in the direction of y-polarization. Furthermore, the sensor achieves high resolution, and the figure of merit (FOM) values can reach up to 5.134 × 10−7 and 2758. Consequently, the proposed sensor can provide high-precision and extensive-range measurements of solution refractive indices within the visible and infrared light spectrum, and it holds potential application prospects in numerous fields, such as food safety testing and chemical substance detection.

Configurable multiple virtual lenses conjugated with singlet physical lens for achromatic extended depth-of-field imaging.

An achromatic extended depth-of-field (EDOF) system can obtain clear scene information that is crucial for target recognition, dynamic monitoring, and other applications. However, the imaging performance of most optical systems is depth-variant and wavelength-variant, which leads to the generation of chromatic aberrations. Traditional optical design and image post-processing algorithms cannot effectively eliminate these chromatic aberrations. Here, we propose a deep configurable multiple virtual lenses optimization method that embeds four virtual lenses in parallel conjugated with a real lens. Combined with a lens fusion recovery network (LFRNet), it compensates for chromatic aberrations at different depths to achieve achromatic EDOF imaging. Trainable virtual optics can eliminate chromatic aberrations and overcome the limitations of traditional optics. The proposed framework reduces the optical design complexity and improves the imaging quality of a simple optical system. We validate our method using a singlet lens, and the experimental results show that the reconstructed images have an average peak signal-to-noise ratio (PSNR) improvement of 12.1447 dB and an average structural similarity index measure (SSIM) improvement of 0.2465. The proposed method opens a new avenue for ultra-compact, high-freedom, high-efficiency, and wholly configurable deep optics design, and empowers various advanced applications, such as portable photography and other complex vision tasks.