Ratio Values Research Articles

Uncertainty analysis for forest height inversion using L / P band PolInSAR datasets and RVoG model over kryclan forest site

Forest height, as a measure of the quantity and quality of forest resources, plays a significant role in the study of the ecological functions performed by forests. Although the polarimetric synthetic aperture radar interferometry (PolInSAR) technique has evolved as a potent method for forest height inversion, uncertainties still exist in the process of estimating forest height, and the uncertainties in predicted forest height directly lead into the uncertainty of terrestrial carbon stock calculation results. In this study, we took the Random Volume over Ground (RVoG) model as likelihood function and constructed a hierarchical Bayesian framework to calculate and reduce the uncertainty of forest height inversion using L / P band PolInSAR airborne data via RVoG model. Uncertainties resulted from five canopy types and three forest densities were analyzed, respectively. The results showed that among the five different canopy types, L band has the highest prediction accuracy in pure coniferous canopy with Acc. = 0.90. The uncertainty is extremely low for pure forest, with the ratio of uncertainty values of 0.09 for L band and 0.15 for the P band in pure coniferous canopy, and uncertainty values of 0.16 for L band and 0.11 for P band in pure broadleaf canopy, respectively. Furthermore, when the forest density is between 300 and 600 stems/ha, the ratio of uncertainties for the L band is 0.27, whereas the P band is 0.24. As forest density increases, the uncertainty in forest height estimates decreases for both bands. The changes in canopy types and forest density affect forest height estimation uncertainties obviously, the effects are different at each frequency. The forest height inversion accuracy of the L band in pure coniferous canopy surpasses that in other canopy types, with the lowest uncertainty. P band performed well in broadleaf canopy forest height inversion. The inversion uncertainties at both frequencies decrease with increase of forest densities.

Comparative study on the morphological characteristics, nutritional quality, and tastes of large yellow croaker from five cage culture areas: Relay farming improved fish quality

Relay culture of large yellow croaker from Fujian to Zhejiang is a good model for improved fish quality. However, there is a scarcity of information regarding the comprehensive evaluation of quality alterations following relay culture. In the present study, the large yellow croaker from Ningde (ND) was transferred to net cages in Dongtou (DT), Nanji (NJ), Dongji (DJ) and Dacheng (DC) for continued culture. The 15-month-old fish from ND, DJ, DC, DT, and NJ were sampled on-site for a subsequent comparative study on the morphological characteristics, nutritional quality, and tastes. Results showed that the fish from DJ, DC, DT, and NJ had a lower condition factor (CF) and a higher ratio of body length to height (L/H) than those from ND. The fish from DJ, DC, DT, and NJ, at rates of 77.8%, 91.3%, 95.7%, and 100%, exhibited different geometric morphometrics from those from ND using 10 typical landmarks and Morpho J software. Ralay culture also significantly affected the histology and ultrastructure of muscle fibers, as reflected by an increase in the muscle fiber density and decreases in the ratio of fiber area to gap, I band width, and sarcomere length in the relay culture fish compared to the ND fish. The relay culture fish showed low lipid content and high moisture content. Relay culture also significantly affected the levels of some nutritional composition, including deceases in the levels of hydrolyzed glycine, C16:0, C18:1n9c, C18:2n6c, Σn-6 PUFA (polyunsaturated fatty acids), Fe (iron), Mn (manganese), and Co (cobalt), and increases in the levels of C20:5n3 (EPA, eicosapentaenoic acid), C22:6n3 (DHA, docosahexaenoic acid), C18:0, Σn-3/Σn-6 PUFA, Σn-3 PUFA, Al (aluminum), Se (selenium), Na (sodium), and Ca (calcium). The levels of taste substances such as guanosine monophosphate (GMP) and most flavor amino acids sharply declined after relay culture. However, the ratio of taste activity value (TAV) of ΣDAA to ΣBAA (delicious amino acids/bitter amino acids) in the DT and NJ fish was higher than that in the ND fish. Significant negative relationships between market price and quality parameters were found, including CF, crude lipid, C18:1n9c, C18:2n6c, Σn-6 PUFA, Fe, Mn, and TAV of GMP, whereas there were positive relationships between market price and 4 quality parameters such as L/H, moisture, Σn-3/Σn-6 PUFA, and the ratio of TAC of ΣDAA to ΣBAA. In conclusion, relay culture improved large yellow croaker quality by changes in morphological characteristics, nutritional quality, and tastes, which provides a theoretical basis for quality improvement.

Transcranial Blood-Brain Barrier Opening in Alzheimer's Disease Patients Using a Portable Focused Ultrasound System with Real-Time 2-D Cavitation Mapping.

Focused ultrasound (FUS) in combination with microbubbles has recently shown great promise in facilitating blood-brain barrier (BBB) opening for drug delivery and immunotherapy in Alzheimer's disease (AD). However, it is currently limited to systems integrated within the MRI suites or requiring post-surgical implants, thus restricting its widespread clinical adoption. In this pilot study, we investigate the clinical safety and feasibility of a portable, non-invasive neuronavigation-guided FUS (NgFUS) system with integrated real-time 2-D microbubble cavitation mapping. A phase 1 clinical study with mild to moderate AD patients (N=6) underwent a single session of microbubble-mediated NgFUS to induce transient BBB opening (BBBO). Microbubble activity under FUS was monitored with real-time 2-D cavitation maps and dosing to ensure the efficacy and safety of the NgFUS treatment. Post-operative MRI was used for BBB opening and closure confirmation as well as safety assessment. Changes in AD biomarker levels in both blood serum and extracellular vesicles (EVs) were evaluated, while changes in amyloid-beta (Aβ) load in the brain were assessed through 18F-Florbetapir PET. BBBO was achieved in 5 out of 6 subjects with an average volume of 983±626 mm3 following FUS at the right frontal lobe both in white and gray matter regions. The outpatient treatment was completed within 34.8±10.7 min. Cavitation dose significantly correlated with the BBBO volume (R 2>0.9, N=4), demonstrating the portable NgFUS system's capability of predicting opening volumes. The cavitation maps co-localized closely with the BBBO location, representing the first report of real-time transcranial 2-D cavitation mapping in the human brain. Larger opening volumes correlated with increased levels of AD biomarkers, including Aβ42 (R 2=0.74), Tau (R 2=0.95), and P-Tau181 (R 2=0.86), assayed in serum-derived EVs sampled 3 days after FUS (N=5). From PET scans, subjects showed a lower Aβ load increase in the treated frontal lobe region compared to the contralateral region. Reduction in asymmetry standardized uptake value ratios (SUVR) correlated with the cavitation dose (R 2>0.9, N=3). Clinical changes in the mini-mental state examination over 6 months were within the expected range of cognitive decline with no additional changes observed as a result of FUS. We showed the safety and feasibility of this cost-effective and time-efficient portable NgFUS treatment for BBBO in AD patients with the first demonstration of real-time 2-D cavitation mapping. The cavitation dose correlated with BBBO volume, a slowed increase in pathology, and serum detection of AD proteins. Our study highlights the potential for accessible FUS treatment in AD, with or without drug delivery.

Molecular neuroimaging in dominantly inherited versus sporadic early-onset Alzheimer's disease.

Approximately 5% of Alzheimer's disease patients develop symptoms before age 65 (early-onset Alzheimer's disease), with either sporadic (sporadic early-onset Alzheimer's disease) or dominantly inherited (dominantly inherited Alzheimer's disease) presentations. Both sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease are characterized by brain amyloid-β accumulation, tau tangles, hypometabolism and neurodegeneration, but differences in topography and magnitude of these pathological changes are not fully elucidated. In this study, we directly compared patterns of amyloid-β plaque deposition and glucose hypometabolism in sporadic early-onset Alzheimer's disease and dominantly inherited Alzheimer's disease individuals. Our analysis included 134 symptomatic sporadic early-onset Alzheimer's disease amyloid-Positron Emission Tomography (PET)-positive cases from the University of California, San Francisco, Alzheimer's Disease Research Center (mean ± SD age 59.7 ± 5.6 years), 89 symptomatic dominantly inherited Alzheimer's disease cases (age 45.8 ± 9.3 years) and 102 cognitively unimpaired non-mutation carriers from the Dominantly Inherited Alzheimer Network study (age 44.9 ± 9.2). Each group underwent clinical and cognitive examinations, 11C-labelled Pittsburgh Compound B-PET and structural MRI. 18F-Fluorodeoxyglucose-PET was also available for most participants. Positron Emission Tomography scans from both studies were uniformly processed to obtain a standardized uptake value ratio (PIB50-70 cerebellar grey reference and FDG30-60 pons reference) images. Statistical analyses included pairwise global and voxelwise group comparisons and group-independent component analyses. Analyses were performed also adjusting for covariates including age, sex, Mini-Mental State Examination, apolipoprotein ε4 status and average composite cortical of standardized uptake value ratio. Compared with dominantly inherited Alzheimer's disease, sporadic early-onset Alzheimer's disease participants were older at age of onset (mean ± SD, 54.8 ± 8.2 versus 41.9 ± 8.2, Cohen's d = 1.91), with more years of education (16.4 ± 2.8 versus 13.5 ± 3.2, d = 1) and more likely to be apolipoprotein ε4 carriers (54.6% ε4 versus 28.1%, Cramer's V = 0.26), but similar Mini-Mental State Examination (20.6 ± 6.1 versus 21.2 ± 7.4, d = 0.08). Sporadic early-onset Alzheimer's disease had higher global cortical Pittsburgh Compound B-PET binding (mean ± SD standardized uptake value ratio, 1.92 ± 0.29 versus 1.58 ± 0.44, d = 0.96) and greater global cortical 18F-fluorodeoxyglucose-PET hypometabolism (mean ± SD standardized uptake value ratio, 1.32 ± 0.1 versus 1.39 ± 0.19, d = 0.48) compared with dominantly inherited Alzheimer's disease. Fully adjusted comparisons demonstrated relatively higher Pittsburgh Compound B-PET standardized uptake value ratio in the medial occipital, thalami, basal ganglia and medial/dorsal frontal regions in dominantly inherited Alzheimer's disease versus sporadic early-onset Alzheimer's disease. Sporadic early-onset Alzheimer's disease showed relatively greater 18F-fluorodeoxyglucose-PET hypometabolism in Alzheimer's disease signature temporoparietal regions and caudate nuclei, whereas dominantly inherited Alzheimer's disease showed relatively greater hypometabolism in frontal white matter and pericentral regions. Independent component analyses largely replicated these findings by highlighting common and unique Pittsburgh Compound B-PET and 18F-fluorodeoxyglucose-PET binding patterns. In summary, our findings suggest both common and distinct patterns of amyloid and glucose hypometabolism in sporadic and dominantly inherited early-onset Alzheimer's disease.

The value of elastography strain rate ratio in benign and malignant BI-RADS-US 3-4 breast masses.

In the realm of breast diagnostics, Breast Imaging Reporting and Data System (BI-RADS) serves as a systematic framework, guiding a methodical exploration into the nuanced narratives of masses. The current study aims to investigate the value of strain rate ratio (SR) of elastography for benign and malignant breast masses categorized by BI-RADS for Ultrasonography (BI-RADS-US) category 3-4. Ultrasonographic data of 1099 breast masses that underwent both elastography and pathological examination were retrospectively analyzed by non-parametric test, consistency analysis and receiver operating characteristic (ROC) curve sequentially. ROC curve was used to evaluate the diagnostic effect of SR method in different BI-RADS categories of breast lesions. The maximum Youden index obtained from the ROC curve was 0.845. At a cut-off value of 3.57, the SR values' diagnostic sensitivity, specificity, accuracy, positive predictive value and negative predictive value for distinguishing benign and malignant breast lesions were 85.7 %, 98.8 %, 93.6 %, 97.9 % and 91.45 %, respectively. Consistency analysis showed that the consistency between SR value and pathological diagnosis was 93.6 % (κ = 0.864). In addition, the SR values between benign and malignant lesions of BI-RADS 3 and 4 were statistically different (P < 0.001). ROC analysis indicated that the diagnostic area under curve (AUC) for SR value in BI-RADS 3, 4a, 4b and 4c lesions were 0.985, 0.866, 0.793 and 0.916, respectively. In addition, the study observed 58 cases of missed diagnosis and 20 cases of misdiagnosis in evaluating benign and malignant breast lesions. The elastic SR ratio method has a good diagnostic value for the evaluation of breast masses, particularly for lesions with a score of 3-4. The elastic SR ratio method is instrumental in enhancing the accuracy of diagnosis.

Clinical Performance Evaluation of an Artificial Intelligence-Powered Amyloid Brain PET Quantification Method

PurposeThis study assesses the clinical performance of BTXBrain-Amyloid, an artificial intelligence-powered software for quantifying amyloid uptake in brain PET images.Methods150 amyloid brain PET images were visually assessed by experts and categorized as negative and positive. Standardized uptake value ratio (SUVR) was calculated with cerebellum grey matter as the reference region, and receiver operating characteristic (ROC) and precision-recall (PR) analysis for BTXBrain-Amyloid were conducted. For comparison, same image processing and analysis was performed using Statistical Parametric Mapping (SPM) program. In addition, to evaluate the spatial normalization (SN) performance, mutual information (MI) between MRI template and spatially normalized PET images was calculated and SPM group analysis was conducted.ResultsBoth BTXBrain and SPM methods discriminated between negative and positive groups. However, BTXBrain exhibited lower SUVR standard deviation (0.06 and 0.21 for negative and positive, respectively) than SPM method (0.11 and 0.25). In ROC analysis, BTXBrain had an AUC of 0.979, compared to 0.959 for SPM, while PR curves showed an AUC of 0.983 for BTXBrain and 0.949 for SPM. At the optimal cut-off, the sensitivity and specificity were 0.983 and 0.921 for BTXBrain and 0.917 and 0.921 for SPM12, respectively. MI evaluation also favored BTXBrain (0.848 vs. 0.823), indicating improved SN. In SPM group analysis, BTXBrain exhibited higher sensitivity in detecting basal ganglia differences between negative and positive groups.ConclusionBTXBrain-Amyloid outperformed SPM in clinical performance evaluation, also demonstrating superior SN and improved detection of deep brain differences. These results suggest the potential of BTXBrain-Amyloid as a valuable tool for clinical amyloid PET image evaluation.

Exploration of neuroanatomical characteristics to differentiate prodromal Alzheimer’s disease from cognitively unimpaired amyloid-positive individuals

Differentiating clinical stages based solely on positive findings from amyloid PET is challenging. We aimed to investigate the neuroanatomical characteristics at the whole-brain level that differentiate prodromal Alzheimer’s disease (AD) from cognitively unimpaired amyloid-positive individuals (CU A+) in relation to amyloid deposition and regional atrophy. We included 45 CU A+ participants and 135 participants with amyloid-positive prodromal AD matched 1:3 by age, sex, and education. All participants underwent 18F-florbetaben positron emission tomography and 3D structural T1-weighted magnetic resonance imaging. We compared the standardized uptake value ratios (SUVRs) and volumes in 80 regions of interest (ROIs) between CU A+ and prodromal AD groups using independent t-tests, and employed the least absolute selection and shrinkage operator (LASSO) logistic regression model to identify ROIs associated with prodromal AD in relation to amyloid deposition, regional atrophy, and their interaction. After applying False Discovery Rate correction at < 0.1, there were no differences in global and regional SUVR between CU A+ and prodromal AD groups. Regional volume differences between the two groups were observed in the amygdala, hippocampus, entorhinal cortex, insula, parahippocampal gyrus, and inferior temporal and parietal cortices. LASSO logistic regression model showed significant associations between prodromal AD and atrophy in the entorhinal cortex, inferior parietal cortex, both amygdalae, and left hippocampus. The mean SUVR in the right superior parietal cortex (beta coefficient = 0.0172) and its interaction with the regional volume (0.0672) were also selected in the LASSO model. The mean SUVR in the right superior parietal cortex was associated with an increased likelihood of prodromal AD (Odds ratio [OR] 1.602, p = 0.014), particularly in participants with lower regional volume (OR 3.389, p < 0.001). Only regional volume differences, not amyloid deposition, were observed between CU A+ and prodromal AD. The reduced volume in the superior parietal cortex may play a significant role in the progression to prodromal AD through its interaction with amyloid deposition in that region.

QUEUING EFFICACY OF AUTOMATED TELLER MACHINES OPERATIONS ON MARKET PERFORMANCE OF SELECTED DEPOSIT MONEY BANKS IN RIVER STATE, NIGERIA

Generally, this study examines the queuing efficacy of ATMs operations on market performance of selected deposit money banks in Rivers State. Specifically, the study investigates how queuing efficiency affects customers’ patronage of money deposit banks in River State. Data were collected from selected ATM users at urban centres in River State. Descriptive and inferential statistics was used to discuss the findings which explain that Queuing Efficacy will increase customers’ patronage of banks in River State. The result presented shows that Queuing Efficacy had a positive relationship with customers’ patronage which its relationship was statistically significant at p = .000 [R = .267, p &lt;.05]. This indicates that service rate and customers’ patronage move in the same direction, that as service rate increases, customers’ patronage also increases. The model R2 (coefficient of determination) was 0.071 indicates that service rate explained 7.1% of the variance observed in customers’ patronage. Keywords: Customer Loyalty, Self Efficacy and Market Value Ratio.

Efficacy of intraoperative visual evoked potential amplitude reduction in predicting visual outcome after extended endoscopic endonasal resection of craniopharyngiomas.

Postoperative visual outcome is a major concern of neurosurgeons for patients with craniopharyngiomas. The current study aimed to investigate the value of visual evoked potential (VEP) amplitude reduction (N75-P100 and P100-N145) for predicting postoperative visual dysfunction (POVD) and refining current warning criteria for VEP monitoring. Data from 96 patients who underwent the extended endoscopic endonasal approach for craniopharyngiomas between October 2020 and November 2021 were retrospectively reviewed. VEP amplitude reduction ratios were calculated and compared between patients with POVD and those without. Subsequently, the critical threshold values of VEP amplitude reduction ratios for predicting POVD were obtained through receiver operating characteristic curve analysis. Finally, multivariate binary logistic regression analysis was applied to evaluate the effect of potential factors on the probability of experiencing POVD. Both N75-P100 and P100-N145 amplitude reduction ratios were significantly higher in patients with POVD (p < 0.001 for both). The threshold value of the N75-P100 amplitude reduction ratio for predicting POVD was 51.76% with an area under the curve (AUC) of 0.816 (p < 0.001), while the threshold value of the P100-N145 amplitude reduction ratio was 38.80% with an AUC of 0.738 (p < 0.001). Both N75-P100 and P100-N145 amplitude reduction ratios were identified as independent predictors for POVD via multivariate analysis (p < 0.001 and p = 0.018, respectively). Both N75-P100 and P100-N145 amplitude reduction ratios showed great potential to be indicators for POVD in patients with craniopharyngiomas. Regarding warning criteria for VEP monitoring, the authors recommend that both N75-P100 and P100-N145 amplitude reduction should be considered, with early warning criteria of a 50% reduction for N75-P100 amplitude and/or a 40% reduction for P100-N145 amplitude.

Local Means Binary Networks for Image Super-Resolution.

The success of modern single image super-resolution (SISR) algorithms is inspired by the development of deep convolutional neural networks (CNNs). However, these CNN-based methods require considerable computation and complexity, making it impossible for these methods to perform real-time calculations in edge devices. Thus, lightweight model design has become a development trend in the super-resolution field, including pruning, quantization, and other methods. The 1-bit quantization is an extreme lightweight method which can reduce the calculation amount of the model in an extreme manner and is friendly to hardware such as edge devices. Most existing binary quantization approaches lead to a large information loss during forward propagation, especially in detailed color information (e.g., edge, texture, and contrast). The loss of color information makes modern binary methods unsuitable for SISR tasks. We think the loss occurs because these methods typically utilize a uniform threshold to quantize the weights and activations. Thus, in this article, we thoroughly analyze the difference between normal classification tasks and SISR tasks, and present a binarization scheme based on local means. The proposed method can maintain more detailed information in feature maps using dynamic thresholds during quantization. Specifically, each value in the full precision activations has a corresponding threshold during the quantization process, and those thresholds are determined by the full precision values of the surroundings. In addition, a gradient approximator is introduced to adaptively optimize the gradient for updating binary weights. We then verify the effectiveness of our method for training binary networks on several SISR benchmarks including VDSR and SRResNet. Experimental results show that the proposed method can outperform the state-of-the-art algorithms to obtain binary networks for image super-resolution with better peak signal-to-noise ratio (PSNR) values and visual quality.

Stability assessment of CIPP liner under varied boundary conditions: A theoretical and simulation study

The buckling of liners carries significant implications, including hampered medium transmission, structural damage, and the risk of leaks, adversely affecting production, economy, and the environment. The interface performance between Cured-in-place-pipe (CIPP) liners and host pipes is pivotal for overall structural stability. However, this interface's influence has been underestimated in engineering practices and laboratory research. This study introduces two novel hydrostatic pressure buckling models, enhancing constrained arch and energy-based Glock models, while considering both free and bonded boundary conditions. Subsequently, a validated 3D finite element model of CIPP lined pipes is established from full-scale tests. Through comprehensive sensitivity analysis, the study investigates the influence of diameter-to-wall thickness ratio (DR) and annular gap on liner buckling under free boundary conditions. Additionally, it explores the effects of DR value and ovality ratio on buckling behavior under bonded conditions. Results reveal distinct buckling and post-buckling modes under different boundary conditions. The proposed theoretical analysis method accurately predicts critical buckling pressure within a 10 % error margin, validated through experiments and numerical simulations, offering practical guidance for assessing repaired pipe stability.

Analisis Nilai Tambah Bonggol Pisang (Musa paradisiaca L.) Menjadi Kerupuk Bongsang Pada UKM Abopink Di Desa Pringgacala Kecamatan Karangampel Kabupaten Indramayu

The purpose of this study was to (1) the added value of the banana corm processing business into bongsang crackers in UKM ABOPINK; and (2) to determine the value-added ratio of banana corm processing business becoming bongsang crackers at UKM ABOPINK. The research method used was a survey method, and the research design was a descriptive survey. Determination of the sample using purposive sampling technique, namely purposive sampling. Analysis of the data used in this study using added value analysis with the Hayami method. Based on the results of this study, the bongsang cracker processing business at UKM ABOPINK Pringgacala Village, Karangampel District, Indramayu Regency in 2020. UKM ABOPINK produces bongsang crackers with 1 package, which is a package containing 100 grams. With an added value of IDR. 40.905,50 with an added value ratio of 77,92% means that the added value is high in one production process.

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.