Ratio Values Research Articles

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data.

MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA-miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

Association of Basal Forebrain Volume with Amyloid, Tau, and Cognition in Alzheimer's Disease.

Degeneration of cholinergic basal forebrain (BF) neurons characterizes Alzheimer's disease (AD). However, what role the BF plays in the dynamics of AD pathophysiology has not been investigated precisely. To investigate the baseline and longitudinal roles of BF along with core neuropathologies in AD. In this retrospective cohort study, we enrolled 113 subjects (38 amyloid [Aβ]-negative cognitively unimpaired, 6 Aβ-positive cognitively unimpaired, 39 with prodromal AD, and 30 with AD dementia) who performed brain MRI for BF volume and cortical thickness, 18F-florbetaben PET for Aβ, 18F-flortaucipir PET for tau, and detailed cognitive testing longitudinally. We investigated the baseline and longitudinal association of BF volume with Aβ and tau standardized uptake value ratio and cognition. Cross-sectionally, lower BF volume was not independently associated with higher cortical Aβ, but it was associated with tau burden. Tau burden in the orbitofrontal, insular, lateral temporal, inferior temporo-occipital, and anterior cingulate cortices were associated with progressive BF atrophy. Lower BF volume was associated with faster Aβ accumulation, mainly in the prefrontal, anterior temporal, cingulate, and medial occipital cortices. BF volume was associated with progressive decline in language and memory functions regardless of baseline Aβ and tau burden. Tau deposition affected progressive BF atrophy, which in turn accelerated amyloid deposition, leading to a vicious cycle. Also, lower baseline BF volume independently predicted deterioration in cognitive function.

Burst Diagnosis Multi-Stage Model for Water Distribution Networks Based on Deep Learning Algorithms

Pipe bursts in water distribution networks (WDNs) pose significant threats to the safety of distribution networks, driving attention to deep learning-based burst detection and localization. However, the applicability of different pressure features still needs to be compared and verified. A large number of nodes challenges deep learning with the excessive number of classification categories and low recognition accuracy. To address these problems, this paper extracts different burst pressure features, including pressure value, pressure difference, and pressure fluctuation ratio, and inputs one of these features into a Burst Diagnosis Multi-Stage Model (BDMM) based on three CS-LSTMs (a combination of the Cuckoo Search algorithm and a long short-term memory network). The first model addresses a binary classification problem, outputting labels indicating whether a pipe burst has occurred. The second one solves a multi-classification problem, outputting the label of the burst partition, and the third model also solves a multi-classification problem, outputting the ID of the bursting junction. The model is tested on a real network and outperforms ELM. For basic burst identification tasks using CS-LSTM, differences among the three features are minimal, while pressure difference and pressure fluctuation ratio exhibit superior performance to pressure value when resolving more complex problems like burst junction localization.

A New Approach to the Economic Evaluation of Thermomodernization: Annual Assessment Based on the Example of Production Space

Energy and economic assessments are of great relevance in the context of decision processes for the most optimal solutions for building renovations. Following the method recommended by UNIDO, economic analyses of thermal modernization options are carried out based on the Simple Payback Time (SPBT), Net Present Value Ratio (NPVR) and Internal Rate of Return (IRR) indices. Incorporating these indicators and a new approach that involves aggregating thermomodernization activities not only in the cold and warm seasons separately, but throughout the whole year, an economic evaluation of the thermomodernization of a production space was carried out. In this case study, the renovation options included wall insulation, window replacement, the installation of infrared heater, a two-flow air diffuser (TFAD) and variable air volume. The economic effect indicated by the highest NPVR over a normative period of 15 years was obtained for the installation of an infrared heater and a TFAD with a variable mode ventilation system. The SPBT for this case was also the lowest.

Expression of regional brain amyloid-β deposition with [18F]Flutemetamol in Centiloid scale -a multi-site study.

The Centiloid project helps calibrate the quantitative amyloid-β (Aβ) load into a unified Centiloid (CL) scale that allows data comparison across multi-site. How the smaller regional amyloid converted into CL has not been attempted. We first aimed to express regional Aβ deposition in CL using [18F]Flutemetamol and evaluate regional Aβ deposition in CL with that in standardized uptake value ratio (SUVr). Second, we aimed to determine the presence or absence of focal Aβ deposition by measuring regional CL in equivocal cases showing negative global CL. Following the Centiloid project pipeline, Level-1 replication, Level-2 calibration, and quality control were completed to generate corresponding Centiloid conversion equations to convert SUVr into Centiloid at regional levels. In equivocal cases, the regional CL was compared with visual inspection to evaluate regional Aβ positivity. 14 out of 16 regional conversions from [18F]Flutemetamol SUVr to Centiloid successfully passed the quality control, showing good reliability and relative variance, especially precuneus/posterior cingulate and prefrontal regions with good stability for Centiloid scaling. The absence of focal Aβ deposition could be detected by measuring regional CL, showing a high agreement rate with visual inspection. The regional Aβ positivity in the bilateral anterior cingulate cortex was most prevalent in equivocal cases. The expression of regional brain Aβ deposition in CL with [18F]Flutemetamol has been attempted in this study. Equivocal cases had focal Aβ deposition that can be detected by measuring regional CL.

Inference for the stress-strength parameter of multi-state systems based on records

. Stress-strength models are used to analyze the reliability of the two-state systems. In this article, the stress-strength model for a multi-state system is discussed. It is assumed that the stress-strength reliability depends on the ratio of strength and stress values. When the stress and the strength random variables follow two independent Weibull distributions, the estimation of the multi-state stress-strength reliability function by various methods is investigated. Particularly, the problem of parameter estimation on the basis of the records is studied in detail. Furthermore, simulation studies are conducted for comparative purposes. Finally, two illustrative examples are presented.

Relationship between neuroimaging and cognition in frontotemporal dementia: An FDG-PET and structural MRI study.

Frontotemporal dementia (FTD) is a clinically and pathologically heterogeneous neurodegenerative condition with a prevalence comparable to Alzheimer's disease for patients under 65 years of age. Limited studies have examined the association between cognition and neuroimaging in FTD using different imaging modalities. We examined the association of cognition using Montreal Cognitive Assessment (MoCA) with both gray matter (GM) volume and glucose metabolism using magnetic resonance imaging and fluorodeoxyglucose (FDG)-PET in 21 patients diagnosed with FTD. Standardized uptake value ratio (SUVR) using the brainstem as a reference region was the primary outcome measure for FDG-PET. Partial volume correction was applied to PET data to account for disease-related atrophy. Significant positive associations were found between whole-cortex GM volume and MoCA scores (r = 0.46, p =.04). The association between whole-cortex FDG SUVR and MoCA scores was not significant (r = 0.37, p =.09). GM volumes of the frontal cortex (r = 0.54, p =.01), caudate (r = 0.62, p<.01), and insula (r = 0.57, p<.01) were also significantly correlated with MoCA, as were SUVR values of the insula (r = 0.51, p =.02), thalamus (r = 0.48, p =.03), and posterior cingulate cortex (PCC) (r = 0.47, p =.03). Whole-cortex atrophy is associated with cognitive dysfunction, and this association is larger than for whole-cortex hypometabolism as measured with FDG-PET. At the regional level, focal atrophy and/or hypometabolism in the frontal cortex, insula, PCC, thalamus, and caudate seem to be important for the decline of cognitive function in FTD. Furthermore, these results highlight how functional and structural changes may not overlap and might contribute to cognitive dysfunction in FTD in different ways.

Characterizing brain tau and cognitive decline along the amyloid timeline in Alzheimer's disease.

Recent longitudinal PET imaging studies have established methods to estimate the age at which amyloid becomes abnormal at the level of the individual. Here we recontextualized amyloid levels into the temporal domain to better understand the downstream Alzheimer's disease processes of tau neurofibrillary tangle (NFT) accumulation and cognitive decline. This cohort study included a total of 601 individuals from the Wisconsin Registry for Alzheimer's Prevention and Wisconsin Alzheimer's Disease Research Center that underwent amyloid and tau PET, longitudinal neuropsychological assessments and met clinical criteria for three clinical diagnosis groups: cognitively unimpaired (n = 537); mild cognitive impairment (n = 48); or dementia (n = 16). Cortical 11C-Pittsburgh compound B (PiB) distribution volume ratio (DVR) and sampled iterative local approximation were used to estimate amyloid positive (A+; global PiB DVR > 1.16 equivalent to 17.1 centiloids) onset age and years of A+ duration at tau PET (i.e. amyloid chronicity). Tau PET burden was quantified using 18F-MK-6240 standardized uptake value ratios (70-90 min, inferior cerebellar grey matter reference region). Whole-brain and region-specific approaches were used to examine tau PET binding along the amyloid timeline and across the Alzheimer's disease clinical continuum. Voxel-wise 18F-MK-6240 analyses revealed that with each decade of A+, the spatial extent of measurable tau spread (i.e. progressed) from regions associated with early to late NFT tau stages. Regional analyses indicated that tau burden in the entorhinal cortex was detectable, on average, within 10 years of A+ onset. Additionally, the entorhinal cortex was the region most sensitive to early amyloid pathology and clinical impairment in this predominantly preclinical sample. Among initially cognitively unimpaired (n = 472) individuals with longitudinal cognitive follow-up, mixed effects models showed significant linear and non-linear interactions of A+ duration and entorhinal tau on cognitive decline, suggesting a synergistic effect whereby greater A+ duration, together with a higher entorhinal tau burden, increases the likelihood of cognitive decline beyond their separable effects. Overall, the amyloid time framework enabled a spatiotemporal characterization of tau deposition patterns across the Alzheimer's disease continuum. This approach, which examined cross-sectional tau PET data along the amyloid timeline to make longitudinal disease course inferences, demonstrated that A+ duration explains a considerable amount of variability in the magnitude and topography of tau spread, which largely recapitulated NFT staging observed in human neuropathological studies. By anchoring disease progression to the onset of amyloid, this study provides a temporal disease context, which may help inform disease prognosis and timing windows for anti-amyloid therapies.

Two-Level Dynamic Programming-Enabled Non-Metric Data Aggregation Technique for the Internet of Things

The Internet of Things (IoT) has become a transformative technological infrastructure, serving as a benchmark for automating and standardizing various activities across different domains to reduce human effort, especially in hazardous environments. In these networks, devices with embedded sensors capture valuable information about activities and report it to the nearest server. Although IoT networks are exceptionally useful in solving real-life problems, managing duplicate data values, often captured by neighboring devices, remains a challenging issue. Despite various methodologies reported in the literature to minimize the occurrence of duplicate data, it continues to be an open research problem. This paper presents a sophisticated data aggregation approach designed to minimize the ratio of duplicate data values in the refined set with the least possible information loss in IoT networks. First, at the device level, a local data aggregation process filters out outliers and duplicates data before transmission. Second, at the server level, a dynamic programming-based non-metric method identifies the longest common subsequence (LCS) among data from neighboring devices, which is then shared with the edge module. Simulation results confirm the approach’s exceptional performance in optimizing the bandwidth, energy consumption, and response time while maintaining high accuracy and precision, thus significantly reducing overall network congestion.

Development and Preclinical Evaluation of a Copper-64-Labeled Antibody Targeting Glycine-Alanine Dipeptides for PET Imaging of C9orf72-Associated Amyotrophic Lateral Sclerosis/Frontotemporal Dementia.

Aggregating poly(glycine-alanine) (poly-GA) is derived from the unconventional translation of the pathogenic intronic hexanucleotide repeat expansion in the C9orf72 gene, which is the most common genetic cause of frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). Poly-GA accumulates predominantly in neuronal cytoplasmic inclusions unique to C9orf72 ALS/FTD patients. Poly-GA is, therefore, a promising target for PET/CT imaging of FTD/ALS to monitor disease progression and therapeutic interventions. A novel 64Cu-labeled anti-GA antibody (mAb1A12) targeting the poly-GA protein was developed and evaluated in a transgenic mouse model. It was obtained with high radiochemical purity (RCP), radiochemical yield (RCY), and specific activity, and showed high stability in vitro and ex vivo and specifically bound to poly-GA. The affinity of NODAGA-mAb1A12 for poly-GA was not affected by this modification. [64Cu]Cu-NODAGA-mAb1A12 was injected into transgenic mice expressing GFP-(GA)175 in excitatory neurons driven by Camk2a-Cre and in control littermates. PET/CT imaging was performed at 2, 20, and 40 h post-injection (p.i.) and revealed a higher accumulation in the cortex in transgenic mice than in wild-type mice, as reflected by higher standardized uptake value ratios (SUVR) using the cerebellum as the reference region. The organs were isolated for biodistribution and ex vivo autoradiography. Autoradiography revealed a higher cortex-to-cerebellum ratio in the transgenic mice than in the controls. Results from autoradiography were validated by immunohistochemistry and poly-GA immunoassays. Moreover, we confirmed antibody uptake in the CNS in a pharmacokinetic study of the perfused tissues. In summary, [64Cu]Cu-NODAGA-mAb1A12 demonstrated favorable in vitro characteristics and an increased relative binding in poly-GA transgenic mice compared to wild-type mice in vivo. Our results with this first-in-class radiotracer suggested that targeting poly-GA is a promising approach for PET/CT imaging in FTD/ALS.

Feature Importance Analysis and Machine Learning for Alzheimer’s Disease Early Detection: Feature Fusion of the Hippocampus, Entorhinal Cortex, and Standardized Uptake Value Ratio

Introduction: Alzheimer’s disease (AD) is a progressive neurological disorder characterized by mild memory loss and ranks as a leading cause of mortality in the USA, accounting for approximately 120,000 deaths per year. It is also the primary form of dementia. Early detection is critical for timely intervention as the neurodegenerative process often starts 15–20 years before cognitive symptoms manifest. This study focuses on determining feature importance in AD classification using fused texture features from 3D magnetic resonance imaging hippocampal and entorhinal cortex and standardized uptake value ratio (SUVR) derived from positron emission tomography (PET) images. Methods: To achieve this objective, we employed four distinct classifiers (Linear Support Vector Classification, Linear Discriminant Analysis, Logistic Regression, and Logistic Regression Classifier with Stochastic Gradient Descent Learning). These classifiers were used to derive both average and top-ranked importance scores for each feature based on their outputs. Our framework is designed to distinguish between two classes, AD-negative (or mild cognitive impairment stable [MCIs]) and AD-positive (or MCI conversion [MCIc]), using a probabilistic neural network classifier and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Results: The findings from the feature importance highlight the crucial role of the GLCM texture features extracted from the hippocampus and entorhinal cortex, demonstrating their superior performance compared to the volume and SUVR. GLCM texture AD classification achieved approximately 90% sensitivity in identifying MCIc cases while maintaining low false positives (below 30%) when fused with other features. Moreover, the receiver operating characteristic curves validate the GLCMs’ superior performance in distinguishing between MCIs and MCIc. Additionally, fusing different types of features improved classification performance compared to relying solely on any single feature category. Conclusion: Our study emphasizes the pivotal role of GLCM texture features in early Alzheimer’s detection.

Phantom and clinical evaluation of the Bayesian penalised likelihood reconstruction algorithm Q.Clear without PSF correction in amyloid PET images

PurposeBayesian penalised likelihood (BPL) reconstruction, which incorporates point-spread-function (PSF) correction, provides higher signal-to-noise ratios and more accurate quantitation than conventional ordered subset expectation maximization (OSEM) reconstruction. However, applying PSF correction to brain PET imaging is controversial due to Gibbs artefacts that manifest as unpredicted cortical uptake enhancement. The present study aimed to validate whether BPL without PSF would be useful for amyloid PET imaging.MethodsImages were acquired from Hoffman 3D brain and cylindrical phantoms for phantom study and 71 patients administered with [18F]flutemetamol in clinical study using a Discovery MI. All images were reconstructed using OSEM, BPL with PSF correction, and BPL without PSF correction. Count profile, %contrast, recovery coefficients (RCs), and image noise were calculated from the images acquired from the phantoms. Amyloid β deposition in patients was visually assessed by two physicians and quantified based on the standardised uptake value ratio (SUVR).ResultsThe overestimated radioactivity in profile curves was eliminated using BPL without PSF correction. The %contrast and image noise decreased with increasing β values in phantom images. Image quality and RCs were better using BPL with, than without PSF correction or OSEM. An optimal β value of 600 was determined for BPL without PSF correction. Visual evaluation almost agreed perfectly (κ = 0.91–0.97), without depending on reconstruction methods. Composite SUVRs did not significantly differ between reconstruction methods.ConclusionGibbs artefacts disappeared from phantom images using the BPL without PSF correction. Visual and quantitative evaluation of [18F]flutemetamol imaging was independent of the reconstruction method. The BPL without PSF correction could be the standard reconstruction method for amyloid PET imaging, despite being qualitatively inferior to BPL with PSF correction for [18F]flutemetamol amyloid PET imaging.

Optimization Model of Emergency Evacuation Network Based on Genetic Algorithm

Aggregation and dispersion are the normal states. In economic production and social life, the evacuation of people and materials deserves extensive attention. From the perspective of mathematics and economics, arranging a thoughtful evacuation is essential for the best balance between personal satisfaction and cost. In this paper, evacuation is deeply studied by a genetic algorithm; the balance, cost, and willingness (satisfaction) priority models, which consider both satisfaction and cost, are established. In this paper, based on the field investigation and questionnaire survey conducted by Oriental Sports Center, overall satisfaction is inferred by the satisfaction of each person in the tested sample, and the time cost from the evacuation point to different reception points is inferred through actual investigation. Based on these data, a balance model is established, and the calculation is performed. The ratio of the total willingness value of the evacuated individuals to the total cost is taken as the function of the optimization objective. When the optimization objective function is complex, the genetic algorithm is used to search for the optimal solution by simulating the process of natural evolution. At the same time, the cost priority and willingness priority models are established to compare the advantages and disadvantages of different evacuation schemes and their applicable situations. The evacuation of Oriental Sports Center is studied using a genetic algorithm. The objective function value of equilibrium model optimization is 0.2155 (optimal solution), significantly different from willingness priority model optimization (0.0300). After calculating the optimization objective function value and cost value under the conditions of cost priority and willingness priority, a “People-oriented and cost-balanced” suggestion is put forward for a large crowd evacuation scheme.

Development and validation of headteachers' leadership behavior questionnaire (HLBQ)

The leadership behavior of the headteachers is associated with institutional worth. This study intended to develop and validate a headteachers’ leadership behavior questionnaire (HLBQ) to measure the leadership behavior of headteachers. The questionnaire encompassed two sub-dimensions viz: people-oriented leadership behavior and task-oriented leadership behavior as per Blake and Mouton’s Managerial Grid. After a rigorous literature review followed by focus group discussions, the preliminary draft of the tool encompassed forty-three (43) items on the five (5) points Likert Scale. Based on the content and face validity, the items with CVR values less than 0.42 were dropped. The revised questionnaire was pilot tested on three hundred and ten (310) public secondary school teachers employed in the school education department. The data were processed through Smart PLS version 4, which provided the questionnaire’s validity, reliability, and model fit. After deleting the unfit items, the questionnaire was further reduced to thirty-one (31) items. AVE values of the items related to people-oriented leadership behavior were 0.658 &gt; 0.5, and for task-oriented were 0.686 &gt; 0.5. Fornell-Lacker criterion value (0.828) was more than the correlations with other latent constructs, i.e., 0.811 and 0.831. The Heterotrait-Monotrait ratio (HTMT) value was 0.859 &lt; 0.9, which is acceptable. Cronbach alpha for people-oriented leadership behavior was 0.967 &gt; 0.7, and task-oriented leadership behavior was 0.658 &gt; 0.7. Similarly, the composite reliability (CR) values for people-oriented leadership behavior were 0.970 &gt; 0.7, and task-oriented leadership behavior was 0.963 &gt; 0.7. Thus, the headteachers’ leadership behavior questionnaire (HTLB) was internally consistent, valid, and reliable. The findings of the entire study supported using the headteachers’ leadership behavior questionnaire (HLBQ) to explore and measure the leadership behavior of the headteachers.

PERBANDINGAN NILAI TAMBAH PRODUK OLAHAN IKAN LELE (Clarias Gariepinus) DI GRIYA ULAM-Q KABUPATEN KEDIRI

The purpose of this research is to determine the process of processing catfish into processed catfish in the form of floss and nuggets and to find out the comparison of the amount of added value and profits obtained by MSMEs processing catfish in Griya Ulam-Q, Ngasem District, Kediri Regency. This research was conducted in July - August 2023. The data analysis method used was the hayami value added analysis method. The respondents in this research were catfish processing businesses under the auspices of Griya Ulam-Q, Kediri Regency. The research results show the process of processing catfish into floss and nuggets with various additional raw materials. In calculating the added value using the Hayami method, the added value of abon was IDR 46,822.40 per kilogram, and for nuggets IDR 158,814 per kilogram. Based on the added value calculation using the hayami method, the smallest added value ratio is the added value of floss, namely 31.21%. Meanwhile, the largest added value ratio is the added value of catfish nuggets of 52.94%. The largest level of profit obtained was from floss, namely 88.79%.

In vivo translocator protein in females with autism spectrum disorder: a pilot study

Sex-based differences in the prevalence of autism spectrum disorder (ASD) are well-documented, with a male-to-female ratio of approximately 4:1. The clinical presentation of the core symptoms of ASD can also vary between sexes. Previously, positron emission tomography (PET) studies have identified alterations in the in vivo levels of translocator protein (TSPO)—a mitochondrial protein—in primarily or only male adults with ASD, with our group reporting lower TSPO relative to whole brain mean in males with ASD. However, whether in vivo TSPO levels are altered in females with ASD, specifically, is unknown. This is the first pilot study to measure in vivo TSPO in the brain in adult females with ASD using [11C]PBR28 PET-magnetic resonance imaging (MRI). Twelve adult females with ASD and 10 age- and TSPO genotype-matched controls (CON) completed one or two [11C]PBR28 PET–MRI scans. Females with ASD exhibited elevated [11C]PBR28 standardized uptake value ratio (SUVR) in the midcingulate cortex and splenium of the corpus callosum compared to CON. No brain area showed lower [11C]PBR28 SUVR in females with ASD compared to CON. Test-retest over several months showed stable [11C]PBR28 SUVR across time in both groups. Elevated regional [11C]PBR28 SUVR in females with ASD stand in stark contrast to our previous findings of lower regional [11C]PBR28 SUVR in males with ASD. Preliminary evidence of regionally elevated mitochondrial protein TSPO relative to whole brain mean in ASD females may reflect neuroimmuno-metabolic alterations specific to females with ASD.

Effects of ambient air pollution on the risk of small- and large-for-gestational-age births: an analysis using national birth data in Japan.

Small-for-gestational-age (SGA) and large-for-gestational-age (LGA) births are major adverse birth outcomes related to newborn health. In contrast, the association between ambient air pollution levels and SGA or LGA births has not been investigated in Japan; hence, the purpose of our study is to investigate this association. We used birth data from Vital Statistics in Japan from 2017 to 2021 and municipality-level data on air pollutants, including nitrogen dioxide (NO2), sulfur dioxide (SO2), photochemical oxidants, and particulate matter 2.5 (PM2.5). Ambient air pollution levels throughout the first, second, and third trimesters, as well as the whole pregnancy, were calculated for each birth. The association between SGA/LGA and ambient levels of the air pollutants was investigated using crude and adjusted log-binomial regression models. In addition, a regression model with spline functions was also used to detect the non-linear association. We analyzed data from 2,434,217 births. Adjusted regression analyses revealed statistically significant and positive associations between SGA birth and SO2 level, regardless of the exposure period. Specifically, the risk ratio for average SO2 values throughout the whole pregnancy was 1.014 (95% confidence interval [CI] 1.009, 1.019) per 1ppb increase. In addition, regression analysis with spline functions indicated that an increase in risk ratio for SGA birth depending on SO2 level was linear. Furthermore, statistically significant and negative associations were observed between LGA birth and SO2 except for the third trimester. It was suggested that ambient level of SO2 during the pregnancy term is a risk factor for SGA birth in Japan.

New simplified design methods for engineering barriers around contaminated sites with Cauchy boundaries

Since the 1980s, low-permeability slurry trench cutoff walls have been widely constructed as barriers to retard the migration of contaminants. The thickness of the cutoff walls is a key determinant of the wall service life. Through a series of theoretical derivations, simplified methods for determining the flux limit and concentration limit were proposed to determine the thickness of cutoff walls for contaminated sites with constant pollutant flux. The relative errors of both the flux-based and concentration-based methods increase as the breakthrough criterion of the ratio between the specified limit concentration of the contaminant to the source concentration (C*) and the ratio of the limited value of contaminant flux to the constant source flux (F*) increases, with a given Peclet number PL. The maximum relative error reaches 4% and 6% when C* and F* are both 0.1, which covers most practical situations in cutoff wall design. Good agreements of wall thickness were obtained between the proposed simplified methods and analytical solutions via a clear example. The proposed method can efficiently simplify the design process of cutoff walls with high accuracy, providing a basis for containing contaminated sites.

Comparative performance evaluation and economic assessment between traditional and vibration assisted EDM during machining of Inconel 718

Nickel based superalloy, Inconel 718 offers extensive applications in aerospace and gas turbine industries because of its outstanding properties, enabling high performance in various critical components. Despite the wide application of electric discharge machining (EDM) for difficult-to-cut conductive materials, the process becomes less productive due to unstable arcing and inadequate debris flushing during machining, leading to reduced operational efficiency. This research focuses on comparative performance evaluation and economic assessment between conventional-EDM and vibration assisted EDM (VA-EDM) while machining Inconel 718 with copper electrode. The workpiece was excited to vibrate with low frequency by employing unbalanced mass attached in a rotary motor with the aim of enhancing EDM performance. Material removal rate MRR, surface integrity (surface crack density SCD, surface roughness Ra, white (recast) layer thickness WLT) and tool wear rate TWR are analyzed to determine machining performance in comprehensive analysis. The results of the performance comparison show that vibration assisted is superior to the conventional-EDM process concerning enhanced material removal rate, and surface morphology with minimum surface crack density, tool wear rate and white layer thickness. The mean value ratios for Ra EDM/ Ra VA-EDM, TWR EDM/ TWR VA-EDM, WLT EDM/ WLT VA-EDM, and SCD EDM/ SCD VA-EDM are 1.35, 1.52, 1.21, and 1.74, respectively. Additionally, the surface integrity was enhanced using vibration-assisted EDM because it (a) increases the plasma flushing efficiency and the gap pressure gradient; (b) raises the energy of electrically charged plasma particles; (c) increases the effective flow of dielectric in the gap; (d) minimizes the number of ineffective pulses (short-circuiting and arching) on the surface; and (e) improves the dielectric flushing conditions in sparking gap. According to the findings, the overall machining expenditure per part under VA-EDM in Indian rupees (INR) 534 is lowered by 8% than expenditure under conventional-EDM (INR 576.60). The outcomes of this research have the potential to benefit numerous industries that deal with difficult-to-cut materials.

Association of β-Amyloid, Microglial Activation, Cortical Thickness, and Metabolism in Older Adults Without Dementia.

Plasma β-amyloid42 (Aβ42)/Aβ40 levels have shown promise in identifying Aβ-PET positive individuals. This study explored the concordance and discordance of plasma Aβ42/Aβ40 positivity (Plasma±) with CSF Aβ42/Aβ40 positivity (CSF±) and Aβ-PET positivity (PET±) in older adults without dementia. Associations of Aβ deposition, cortical thickness, glucose metabolism, and microglial activation were also investigated. We selected participants without dementia who had concurrent plasma Aβ42/Aβ40 and Aβ-PET scans from the Alzheimer's Disease Neuroimaging Initiative cohort. Participants were categorized into Plasma±/PET± based on thresholds of composite 18F-florbetapir (FBP) standardized uptake value ratio (SUVR) ≥1.11 and plasma Aβ42/Aβ40 ≤0.1218. Aβ-PET-negative individuals were further divided into Plasma±/CSF± (CSF Aβ42/Aβ40 ≤0.138), and the concordance and discordance of Aβ42/Aβ40 in the plasma and CSF were investigated. Baseline and slopes of regional FBP SUVR were compared among Plasma±/PET± groups, and associations of regional FBP SUVR, FDG SUVR, cortical thickness, and CSF soluble Triggering Receptor Expressed on Myeloid Cell 2 (sTREM2) levels were analyzed. One hundred eighty participants (mean age 72.7 years, 51.4% female, 96 cognitively unimpaired, and 84 with mild cognitive impairment) were included. We found that the proportion of Plasma+/PET- individuals was 6.14 times higher (odds ratio (OR) = 6.143, 95% confidence interval (CI) 2.740-16.185, p < 0.001) than that of Plasma-/PET+ individuals, and Plasma+/CSF- individuals showed 8.5 times larger percentage (OR = 8.5, 95% CI: 3.031-32.974, p < 0.001) than Plasma-/CSF+ individuals in Aβ-PET-negative individuals. Besides, Plasma+/PET- individuals exhibited faster (p < 0.05) Aβ accumulation predominantly in bilateral banks of superior temporal sulcus (BANKSSTS) and supramarginal, and superior parietal cortices compared with Plasma-/PET- individuals, despite no difference in baseline FBP SUVRs. In Plasma+/PET+ individuals, higher CSF sTREM2 levels correlated with slower BANKSSTS Aβ accumulation (standardized β (βstd) = -0.418, 95% CI -0.681 to -0.154, p = 0.002). Conversely, thicker cortical thickness and higher glucose metabolism in supramarginal and superior parietal cortices were associated with faster (p < 0.05) CSF sTREM2 increase in Plasma+/PET- individuals rather than in Plasma+/PET+ individuals. These findings suggest that plasma Aβ42/Aβ40 abnormalities may predate CSF Aβ42/Aβ40 and Aβ-PET abnormalities. Higher sTREM2-related microglial activation is linked to thicker cortical thickness and higher metabolism in early amyloidosis stages but tends to mitigate Aβ accumulation primarily at relatively advanced stages.