Evaluation of spirometry gated CT scan to measure lung volumes in emphysema patients

IntroductionIn emphysema patients, being evaluated for bronchoscopic lung volume reduction (BLVR), accurate measurement of lung volumes is important. Total Lung Capacity (TLC) and Residual Volume (RV) are commonly measured by body-plethysmography, but can also be derived from chest computed tomography (CT). Spirometry-gated CT scanning potentially improves the agreement of CT and body-plethysmography.ObjectiveTo compare lung volumes derived from spirometry-gated CT and “breath-hold-coached” CT to the reference standard: body-plethysmography.MethodsIn this single centre retrospective cohort study, emphysema patients, evaluated for BLVR, underwent body-plethysmography, inspiration (TLC) and expiration (RV) CT-scan with spirometer guidance (“gated group”) or with breath-hold-coaching (“non-gated group”). Quantitative analysis was used to calculate lung volumes from the CT.ResultsWe included 200 patients (age 62±8 years, FEV1 29.2±8.7%, TLC 7.50±1.46 L, RV 4.54±1.07 L). The mean CT-derived TLC was 280(±340)ml lower compared to body-plethysmography in the gated group (n=100), and 590(±430)ml lower for the non-gated group (n=100) (both p<0.001). The mean CT-derived RV was 300(±470)ml higher in the gated group and 700(±720)ml higher in the non-gated group (both p<0.001). Pearson correlation factors were 0.947 for TLC gated, 0.917 for TLC non-gated, 0.823 for RV gated, 0.693 for RV non-gated, 0.539 for %RV/TLC gated and 0.204 for %RV/TLC non-gated. The differences between the gated and non-gated CT results for TLC and RV were significant for all measurements (p<0.001).ConclusionIn severe COPD patients with emphysema, CT-derived lung volumes are strongly correlated to body-plethysmography lung volumes, and especially for RV, more accurate when using spirometry-gating.

An adaptive multi-hop routing with IoT abstraction for minimizing delay-node capacity trade-offs in mobile ad-hoc network

<span>Delay and node capacity are incompatible mobile ad hoc constraints because of the network's versatility and self-disciplined design. </span><span>It is a challenging problem to maximize the trade-off between the above mobility correlation factors. </span><span>This manuscript proposes an adaptive multi-hop routing (A.M.R.) for mobile ad-hoc network (MANET) to minimize the trade-off by integrating the internet of things (IoT). IoT nodes' smart computing and offloading abilities are extended to ad-hoc nodes to improve routing and transmission. Dor MANET nodes in route exploration, neighbor selection, and data transmission, the beneficial features of IoT include enhanced decision making. The traditional routing protocols use IoT at the time of the neighbor discovery process in updating the routing table and localization. </span><span>The harmonizing technologies with their extended support improve the performance of MANETs has been estimated. The proposed method achieves better throughput (14.16 Mbps), delay (0.118), packet drop (126), and overhead (36 packets) when compared to existing methods.</span>

Factors Associated with Cranial Nerve Injury after Radiotherapy for Large Brain Metastases

This paper mainly studied the correlation factors of cranial nerve injury after radiotherapy for large brain metastases by investigating the influencing factors and predictors of cranial nerve injury, which can provide a good reference and idea for radiotherapy. Through a large number of experiments, it is proved that the research idea proposed in this paper is reasonable and correct.

Correlation Factors and a Predictive Model of Serum Ceruloplasmin Normalized Wilson’s Disease

Background: The false increase of ceruloplasmin (Cp) in some Wilson’s disease (WD) patients, which overlaps with those in non-WD liver disease patients, decrease the diagnostic accuracy. The aims of our study was to understand the factors affecting WD patients’ Cp normalization, and develop a model using routine predictors to identify WD patients with ambiguous serum Cp.Results: The mixed effects model analysis which executed in longitudinal study revealed that the WD patients’ Cp normalization were significantly associated with the copper burden and liver function indexes, like urinary copper treated with dimercaptopropansulfonate sodium (P=0.000), aspartate aminotransferase (P=0.011), γ-glutamyltransferase (P=0.000), albumin (P=0.000). Multivariate logistic regression analysis in case-control study showed age (P=0.000) and serum creatine (P=0.000) were independent risk factors associated with WD. Based on their regression coefficients, a simplified WD index was derived: 0.001 × age [yr] × Creatine [umol/L]. The AUC value of WD index in total cohort were 0.923 (P=0.000). At a WD index cutoff value of ≤ 1.9 and ≤ 2.5, the positive and negtive predictive value are 88.2% and 89.9% for WD, respectively.Conclusions: The increase of serum Cp in WD patients is related to their excessive copper burden and hepatic injury, common tests can effectively foretell those WD patients with nearly normal serum Cp from other liver injury patients.

Comparison of sorption efficiency of natural and MnO2 coated zeolite for copper removal from model solutions

Removal of heavy metals from the environment is important for living beings. The present work investigates the applicability of the natural and MnO2 - coated zeolite as sorbent for the removal of copper from synthetic solutions. Batch experiments were carried out to identify the influence of initial pH and concentration in the process of adsorption. A maximum removal efficiency of Cu(II) was observed in 10 mg/L for natural (95.6%) and modified (96.4%) zeolite, where the values was almost identical, but at concentration of 500 mg/L was the removal efficiency of modified zeolite three times higher. Based on the correlation factors R2, the Langmuir isotherms better describe the decontamination process than Freundlich. The optimum pH value was set at 5.0.

Model for construction project delay occurrence (PDO)

Extensive research work was conducted in relation with evaluating and ranking delay causes in construction projects, but limited research was performed to discuss the delay issue in theory. This paper discusses the theoretical basis for how delay occurs and propagates during project construction. A set of suggested assumptions were proposed to build a theoretical model for delay occurrence. These assumptions were driven from the analysis of construction project environment, and the concept of project implementation. The construction delay occurrence (PDO) model assumes that some of the root delay causes can convert by themselves and/or other triggers toward direct delay causes. Contractor management deficiency, project contract and procurement strategy, and contractor financial problems are examples of the root delay causes, which have significant influence on project delay and resource availability. The model assumes that construction resources unavailability is the underpinning driver for project delay. Graphical presentation of the PDO model is used to illustrate how delay is generated, propagated during the project life, and converted to be a real and physical delay. Interview questionnaires were used to verify the model bases. This is followed by statistical analysis to ascertain the model assumptions and Delphi technique to confirm questionnaire results. The correlation factors for the two rounds of questionnaires showed that there is a great enhancement for respondents’ answers regarding the effect of resource shortage on root delay causes. The study shows that the proposed set of root delay causes and their effect on project delay and their influence on resource availability were statistically accepted. The study results can be used as a basis for assessing root delay causes and predicting the prone of a project to delay before it starts.

Load noise prediction of a power transformer

In this article, we propose a new regression equation to predict the noise of a power transformer based on the winding vibration under a loading condition. A regression between load noises and tank vibrations for multiple transformers with different rated powers was confirmed through measurements and regression analysis. A regression equation for load noise and winding vibration was derived considering the fact that the winding vibration level is proportional to the tank vibration level. The electromagnetic force, which is the excitation force of the winding, was obtained using the equivalent magnetic circuit network method to obtain the winding vibration required for the regression equation. Subsequently, the obtained force was applied to a finite element model for the winding to achieve the vibration response. The winding vibration obtained through these methods is closely correlated with the load noise, and the amount of winding vibration transferred to the tank could be changed according to the distance between the tank and the winding. Accordingly, an equation for predicting the load noise was established considering the winding vibration and the correlation factors according to the distance of the transmission path. The proposed prediction equation is considerably more accurate than the previous prediction equation.

Visitor Counting and Monitoring in Forests Using Camera Traps: A Case Study from Bavaria (Southern Germany)

A variety of counting methods exist to analyze visitor numbers of outdoor settings such as national parks, recreation areas and urban green spaces, with sensor-based approaches being the most frequently applied. In this paper, we describe the application and practicality of camera traps originally designed for wildlife monitoring for visitor management purposes. The focus of the work is on the practicality of trigger camera traps and data collection for visitor monitoring from a more practice- and management-oriented perspective. Camera traps can provide interesting in-depth and detailed information about recreationists and are flexible and suitable for various uses; however, assessing the visual data manually requires significant staff and working time. To deal with the large amounts of data gathered for numbers of passersby and recreation activities, correlation factors between passersby and pictures were determined, so that the number of passersby related to the number of pictures taken per day or per other time unit could be established. In focusing on using the camera traps and assessing the generated data, it became clear that more studies have to be conducted to compare different methods of visitor monitoring and their accuracy in different outdoor environments.

Compressing atmospheric data into its real information content

Hundreds of petabytes of data are produced annually at weather and climate forecast centres worldwide. Compression is inevitable to reduce storage and to facilitate data sharing. Current techniques do not distinguish the real from the false information in data. We define the bitwise real information content from information theory for data from the Copernicus Atmospheric Monitoring Service (CAMS). Most variables contain less than 7 bits of real information per value, which are also highly compressible due to spatio-temporal correlation. Rounding bits without real information to zero facilitates lossless compression algorithms and encodes the uncertainty within the data itself. The entire CAMS data is compressed by a factor of 17x, relative to 64-bit floats, while preserving 99% of real information. Combined with 4-dimensional compression to exploit the spatio-temporal correlation, factors beyond 60x are achieved without an increase in forecast errors. A data compression Turing test is proposed to optimize compressibility while minimizing information loss for the end use of weather and climate forecast data.