Volume Deviation Research Articles

Volumetric properties and viscosity for the ternary system of (1-pentanol + ethylcyclohexane + methyl myristate) and corresponding binary systems at T = 293.15–323.15 K

Densities and viscosities of ternary system (1-pentanol + ethylcyclohexane + methyl myristate) and the corresponding binary systems, (1-pentanol + ethylcyclohexane), (1-pentanol + methyl myristate), and (ethylcyclohexane + methyl myristate) were determined at different temperatures from 293.15 to 323.15 K. The experimental data were further employed to calculate excess molar volume (VmE) and viscosity deviation (Δη). Over the whole composition range, the VmE values show positive deviations from ideal behavior and the Δη values are negative. The VmE values for the ternary mixtures were also correlated with the corresponding binary data using Cibulka and Redlich–Kister equations, respectively. The experimental data and results provide useful base data for further thermodynamic studies of alcohol–biodiesel–diesel blends.

Comparison of augmented reality and cutting guide technology in assisted harvesting of iliac crest grafts – A cadaver study

BackgroundHarvesting vascularized bone grafts with computer-assisted surgery represents the gold standard for mandibular reconstruction. However, current augmented reality (AR) approaches are limited to invasive marker fixation. This trial compared a markerless AR-guided real-time navigation with virtually planned and 3D printed cutting guides for harvesting iliac crest grafts. Material and methodsTwo commonly used iliac crest transplant configurations were virtually planned on 10 cadaver hips. Transplant harvest was performed with AR guidance and cutting guide technology. The harvested transplants were digitalized using cone beam CT. Deviations of angulation, distance and volume between the executed and planned osteotomies were measured. ResultsBoth AR and cutting guides accurately rendered the virtually planned transplant volume. However, the cumulative osteotomy plane angulation differed significantly (p = 0.018) between AR (14.99 ± 11.69°) and the cutting guides (8.49 ± 5.42°). The cumulative osteotomy plane distance showed that AR-guided navigation had lower accuracy (2.65 ± 3.32 mm) than the cutting guides (1.47 ± 1.36 mm), although without significant difference. ConclusionThis study demonstrated the clinical usability of markerless AR-guided navigation for harvesting iliac crest grafts. Further improvement of accuracy rates might bring clinical implementation closer to reality.

PENGARUH KEPEMILIKAN INSTITUSIONAL TERHADAP LIKUIDITAS PASAR SAHAM: STUDI PADA PERUSAHAAN-PERUSAHAAN MANUFAKTUR YANG TELAH GO PUBLIC DI BURSA EFEK INDONESIA

The purpose of this study is to obtain the empirical evidence about the impact of institutional ownership on stock market liquidity in manufacturing companies that have gone public on the Indonesia Stock Exchange. To achieve this goal, research was carried out on the Indonesia Stock Exchange using a research sample of 100 companies included in the manufacturing industry group. In explaining the effect of institutional ownership on stock market liquidity, 2 (two) models are used. The first model only uses institutional ownership as an independent variable, and the second model includes control variables, namely the standard deviation of price and volume of stock trading using the t test and the F test with α (alpha) of 10 percent. Based on the results of research and discussion, several conclusions can be drawn as follows: First, institutional ownership has a negative and significant effect on stock market liquidity and institutional ownership capacity in explaining stock market liquidity of 4.7 percent. Second, institutional ownership has a negative and significant effect on stock market liquidity, standard deviation of stock prices has a negative and significant effect on stock market liquidity, stock trading volume has a moderate and negative effect on stock market liquidity. The ability of these three variables in explaining stock market liquidity is 13.1 percent.Third, institutional ownership can increase stock market liquidity as indicated by the value of the direction coefficient and the level of significance of the variable of institutional ownership and the coefficient of direction and significance level of the standard deviation variable of stock prices.

Reliability of mechanical ventilation during continuous chest compressions: a crossover study of transport ventilators in a human cadaver model of CPR

BackgroundPrevious studies have stated that hyperventilation often occurs in cardiopulmonary resuscitation (CPR) mainly due to excessive ventilation frequencies, especially when a manual valve bag is used. Transport ventilators may provide mandatory ventilation with predetermined tidal volumes and without the risk of hyperventilation. Nonetheless, interactions between chest compressions and ventilations are likely to occur. We investigated whether transport ventilators can provide adequate alveolar ventilation during continuous chest compression in adult CPR.MethodsA three-period crossover study with three common transport ventilators in a cadaver model of CPR was carried out. The three ventilators ‘MEDUMAT Standard²’, ‘Oxylog 3000 plus’, and ‘Monnal T60’ represent three different interventions, providing volume-controlled continuous mandatory ventilation (VC-CMV) via an endotracheal tube with a tidal volume of 6 mL/kg predicted body weight. Proximal airflow was measured, and the net tidal volume was derived for each respiratory cycle. The deviation from the predetermined tidal volume was calculated and analysed. Several mixed linear models were calculated with the cadaver as a random factor and ventilator, height, sex, crossover period and incremental number of each ventilation within the period as covariates to evaluate differences between ventilators.ResultsOverall median deviation of net tidal volume from predetermined tidal volume was − 21.2 % (IQR: 19.6, range: [− 87.9 %; 25.8 %]) corresponding to a tidal volume of 4.75 mL/kg predicted body weight (IQR: 1.2, range: [0.7; 7.6]). In a mixed linear model, the ventilator model, the crossover period, and the cadaver’s height were significant factors for decreased tidal volume. The estimated effects of tidal volume deviation for each ventilator were − 14.5 % [95 %-CI: −22.5; −6.5] (p = 0.0004) for ‘Monnal T60’, − 30.6 % [95 %-CI: −38.6; −22.6] (p < 0.0001) for ‘Oxylog 3000 plus’ and − 31.0 % [95 %-CI: −38.9; −23.0] (p < 0.0001) for ‘MEDUMAT Standard²’.ConclusionsAll investigated transport ventilators were able to provide alveolar ventilation even though chest compressions considerably decreased tidal volumes. Our results support the concept of using ventilators to avoid excessive ventilatory rates in CPR. This experimental study suggests that healthcare professionals should carefully monitor actual tidal volumes to recognise the occurrence of hypoventilation during continuous chest compressions.

Market power analysis of the Indian power market

Emerging electricity reforms in the power market aims at removing the monopolistic oligopoly power market and promoting competition in the market by providing opportunities to more producers. This paper seeks to investigate various existing structures of the Power Market. Indian Energy Exchange (IEX) and Power Exchange India Limited (PXIL) facilitates transparent trading of electricity, a larger market spectrum and allows the participation of other players in the market. Market power is an indicator of an non-competitive market, that is increase in the market power will result in the degradation of competition. This research will help modify the current parameters (HHI Index and Concentration ratio) which are used for measuring the market power of the power markets. As there is always deviation in unconstrained cleared volume and actual cleared or scheduled volume, deviation arises due to the volume of electricity that could not be cleared because of congestion in the power exchange. The researchers have also examined the Indian Power market and analyzed different developed power markets of the world like the US Pennsylvania-New Jersey-Maryland Interconnection (PJM) and the Nordpool.

Comparison of Respiratory Effects between Dexmedetomidine and Propofol Sedation for Ultrasound-Guided Radiofrequency Ablation of Hepatic Neoplasm: A Randomized Controlled Trial.

Patient’s cooperation and respiration is necessary in percutaneous radiofrequency ablation (RFA) for hepatocellular carcinoma (HCC). We compared the respiratory patterns of dexmedetomidine and propofol sedation during this procedure. Participants were randomly allocated into two groups: the continuous infusions of dexmedetomidine-remifentanil (DR group) or the propofol-remifentanil (PR group). We measured the tidal volume for each patient’s respiration during one-minute intervals at five points and compared the standard deviation of the tidal volumes (SDvt) between the groups. Sixty-two patients completed the study. SDvt at 10 min was not different between the groups (DR group, 108.58 vs. PR group, 149.06, p = 0.451). However, SDvt and end-tidal carbon dioxide (EtCO2) level of PR group were significantly increased over time compared to DR group (p = 0.004, p = 0.021; ß = 0.14, ß = −0.91, respectively). Heart rate was significantly decreased during sedation in DR group (p < 0.001, ß = −2.32). Radiologist satisfaction was significantly higher, and the incidence of apnea was lower in DR group (p = 0.010, p = 0.009, respectively). Compared with propofol-remifentanil, sedation using dexmedetomidine-remifentanil provided a lower increase of the standard deviation of tidal volume and EtCO2, and also showed less apnea during RFA of HCC.

Parameter Optimization of Pretin Printing Process of Wireless Communication Module

For system manufacturers, packaging of the ball grid array (BGA) of wireless communication modules can be performed via solder paste printing. As reballing can be conducted via the pretinning process, it can be compatible with its existing surface mount technology (SMT). This study referred to the Taguchi experimental design to plan its experiment. Three quality characteristics related to the consistency of the solder volume are applied for printing, that is, the standard deviation of the deposition volume of solder paste on all bonding pads of a single component, the coplanarity of the solder balls of the component, and the height range of the solder ball of a single component, which were regarded as the response values. Important design and process parameters related to the pretinning process and the relative location of the bonding pads of components on a connecting board are considered as the controlling factors. Then, this study applied and integrated the results of two multivariate analysis methods, i.e., gray correlation of the principal components and a technique for order preference by similarity to ideal solution (TOPSIS), in order to determine the ideal solution and propose the optimal parameter combination: general squeegee: pressure 40 N and speed 30 mm/s; steel: separation distance 3 mm, speed 2 mm/s, and aspect ratio 0.17; and cleaning frequency: cleaning of stencils after the printing of every two boards. This method effectively improves the control of the solder volume in the pretinning process and meets the acceptance criteria of manufacturers.

Intercomparison of UAV platforms for mapping snow depth distribution in complex alpine terrain

Unmanned Aerial Vehicles (UAVs) offer great flexibility in acquiring images in inaccessible study areas, which are then processed with stereo-matching techniques through Structure-from-Motion (SfM) algorithms. This procedure allows generating high spatial resolution 3D point clouds. The high accuracy of these 3D models allows the production of detailed snow depth distribution maps through the comparison of point clouds from different dates. In this way, UAVs allow monitoring of remote areas that were not achievable previously. The large number of works evaluating this novel technique has not, to date, conducted a systematic evaluation of concurrent snowpack observations with different UAV devices. Taking into account this, and also bearing in mind that potential users of this technique may be interested in exploiting ready-to-use commercial devices, we conducted an evaluation of the snow depth distribution maps with different commercial UAVs. During the 2018–19 snow season, two multi-rotors (Parrot Anafi and DJI Mavic Pro2) and one fixed-wing device (SenseFly eBee plus) were used on three different dates over a small test area (5 ha) within Izas Experimental Catchment in the Central Pyrenees. Simultaneously, snowpack distribution was retrieved with a Terrestrial Laser Scanner (TLS, RIEGL LPM-321) and was considered as ground truth. Three different georeferencing methods (Ground Control Points, ICP algorithm over snow-free areas and RTK-GPS positioning) were tested, showing equivalent performances under optimum illumination conditions. Additionally, for the three acquisition dates, both multi-rotors were flown at two distinct altitudes (50 and 75 m) to evaluate impact on the obtained snow depth maps. The evaluation with the TLS showed an equivalent performance of the two multi-rotors, with mean RMSE below 0.23 m and maximum volume deviations of less than 5%. Flying altitudes did not show significant differences in the obtained maps. These results were obtained under contrasted snow surface characteristics. This study reveals that under good illumination conditions and in relatively small areas, affordable commercial UAVs provide reliable estimations of snow distribution compared to more sophisticated and expensive close-range remote sensing techniques. Results obtained under overcast skies were poor, demonstrating that UAV observations require clear-sky conditions and acquisitions around noon to guarantee a homogenous illumination of the study area.

A generative adversarial network (GAN)-based technique for synthesizing realistic respiratory motion in the extended cardiac-torso (XCAT) phantoms

Objective. Synthesize realistic and controllable respiratory motions in the extended cardiac-torso (XCAT) phantoms by developing a generative adversarial network (GAN)-based deep learning technique. Methods. A motion generation model was developed using bicycle-GAN with a novel 4D generator. Input with the end-of-inhale (EOI) phase images and a Gaussian perturbation, the model generates inter-phase deformable-vector-fields (DVFs), which were composed and applied to the input to generate 4D images. The model was trained and validated using 71 4D-CT images from lung cancer patients and then applied to the XCAT EOI images to generate 4D-XCAT with realistic respiratory motions. A separate respiratory motion amplitude control model was built using decision tree regression to predict the input perturbation needed for a specific motion amplitude, and this model was developed using 300 4D-XCAT generated from 6 XCAT phantom sizes with 50 different perturbations for each size. In both patient and phantom studies, Dice coefficients for lungs and lung volume variation during respiration were compared between the simulated images and reference images. The generated DVF was evaluated by deformation energy. DVFs and ventilation maps of the simulated 4D-CT were compared with the reference 4D-CTs using cross correlation and Spearman’s correlation. Comparison of DVFs and ventilation maps among the original 4D-XCAT, the generated 4D-XCAT, and reference patient 4D-CTs were made to show the improvement of motion realism by the model. The amplitude control error was calculated. Results. Comparing the simulated and reference 4D-CTs, the maximum deviation of lung volume during respiration was 5.8%, and the Dice coefficient reached at least 0.95 for lungs. The generated DVFs presented comparable deformation energy levels. The cross correlation of DVFs achieved 0.89 ± 0.10/0.86 ± 0.12/0.95 ± 0.04 along the x/y/z direction in the testing group. The cross correlation of ventilation maps derived achieved 0.80 ± 0.05/0.67 ± 0.09/0.68 ± 0.13, and the Spearman’s correlation achieved 0.70 ± 0.05/0, 60 ± 0.09/0.53 ± 0.01, respectively, in the training/validation/testing groups. The generated 4D-XCAT phantoms presented similar deformation energy as patient data while maintained the lung volumes of the original XCAT phantom (Dice = 0.95, maximum lung volume variation = 4%). The motion amplitude control models controlled the motion amplitude control error to be less than 0.5 mm. Conclusions. The results demonstrated the feasibility of synthesizing realistic controllable respiratory motion in the XCAT phantom using the proposed method. This crucial development enhances the value of XCAT phantoms for various 4D imaging and therapy studies.

Deep Learning Improves the Temporal Reproducibility of Aortic Measurement.

Imaging-based measurements form the basis of surgical decision making in patients with aortic aneurysm. Unfortunately, manual measurement suffer from suboptimal temporal reproducibility, which can lead to delayed or unnecessary intervention. We tested the hypothesis that deep learning could improve upon the temporal reproducibility of CT angiography-derived thoracic aortic measurements in the setting of imperfect ground-truth training data. To this end, we trained a standard deep learning segmentation model from which measurements of aortic volume and diameter could be extracted. First, three blinded cardiothoracic radiologists visually confirmed non-inferiority of deep learning segmentation maps with respect to manual segmentation on a 50-patient hold-out test cohort, demonstrating a slight preference for the deep learning method (p < 1e-5). Next, reproducibility was assessed by evaluating measured change (coefficient of reproducibility and standard deviation) in volume and diameter values extracted from segmentation maps in patients for whom multiple scans were available and whose aortas had been deemed stable over time by visual assessment (n = 57 patients, 206 scans). Deep learning temporal reproducibility was superior for measures of both volume (p < 0.008) and diameter (p < 1e-5) and reproducibility metrics compared favorably with previously reported values of manual inter-rater variability. Our work motivates future efforts to apply deep learning to aortic evaluation.

Spectroscopic, thermodynamic and ultrasonic properties of pseudo‐binary mixtures of organic extractants and vegetable oil at 25–60°C under atmospheric pressure

AbstractThis work is intended to investigate the molecular interactions and transport properties of five pseudo‐binary mixtures of various combinations of vegetable oils (sesame oil and sunflower oil) and organic extractants (Aliquat 336, TBP, D2EHPA and TOA) by determining their surface tension, density and viscosity over a temperature range of 25–60°C at atmospheric pressure. The experimental data are fitted into various literature models. Information on excess molar volume and viscosity deviation leads to an understanding of solute–solvent interactions. Further, the ultrasonic velocity, isentropic compressibility, intermolecular free length, specific impedance, apparent molar volume, volumetric thermal expansion coefficient, excess Gibbs' free energy, change in enthalpy of mixing and entropy of activation of the liquids have been calculated. A model relating the surface tension, density and viscosity of the pseudo‐binary mixtures has been proposed in this paper. Analysis of Fourier transform infrared (FTIR) studies has further illustrated the intermolecular interactions in the pseudo‐binary mixtures.

Improved predictions of thermomechanical properties of molecular crystals from energy and dispersion corrected DFT.

Thermal stability and pressure-dependent changes are key to molecular crystals and their properties. The determination of their thermal properties from ab initio methods is, however, a challenging task. While the low-frequency phonon spectrum related to intermolecular vibrations remains difficult to describe, the Quasi-Harmonic Approximation (QHA) also induces for molecular crystals a significant volume deviation, which makes their thermal behavior ill-determined. To overcome these difficulties, we consider a pragmatic energy correction (EC) that has long been used for atomic crystals, and we presently report the first ever use for molecular crystals. Applying the QHA in dispersion-corrected density functional theory (DFT-D) calculations with an ab initio parameterized EC, the resulting model can simultaneously and accurately derive thermal and mechanical properties of high-explosive molecular crystals. When compared to experiments, the mean absolute percent error of previous DFT-based thermomechanical models is 12% for mechanical and 31% for thermal properties. Our model performs significantly better and reduces these uncertainties to 4.1% and 9.8%, respectively. In particular, the agreement between our model and experiments for the thermal properties is three times better. This significant improvement greatly benefits the determination of thermomechanical properties such as the Grüneisen parameter and the shock properties. The method has been successfully applied to molecular crystals showing a large diversity of weak intermolecular interactions (β-1,3,5,7-tetranitro-1,3,5,7-tetrazoctane (HMX), α-1,1-diamino-2,2-dinitroethylene (FOX-7), Triaminotrinitrobenzene (TATB), ε-Hexanitrohexaazaisowurtzitane (CL20), and Pentaerythritol tetranitrate (PETN)-I). Due to its accuracy and transferability, our model is expected to work for a large class of computationally designed molecular crystals and co-crystals, providing a basis for a predictive framework.

Effect of temperature, radiation dose and composition on density, viscosity and volumetric properties of N,N,N′,N′-tetraoctyl diglycolamide (TODGA) and n-dodecane mixture, a promising system for the separation of actinides

The organic solution composed of N,N,N′,N′-tetraoctyldiglycolamide (TODGA) and n-dodecane is extensively studied for the removal of trivalent actinides from the high-level liquid waste arising from nuclear industry. Present work deals with the evaluation of density and viscosity of TODGA/n-dodecane as a function of absorbed gamma radiation dose, temperature and composition. In addition, volumetric and viscometric properties like excess molar volume, apparent molar volume, viscosity deviation, activation energy for the viscous flow, enthalpy and entropy changes of activation of this binary mixture were also estimated. Based on these derived thermodynamic properties, the inter-molecular interactions of this binary liquid solution were predicted. Redlich–Kister type equations were employed to correlate excess volume and viscosity deviation, and the coefficients of fourth degree polynomial that fitted well with the experimental data were estimated. Present study indicated the stable nature of hydrodynamic behaviour of TODGA/n-dodecane system with respect to physical properties up to 500 kGy of absorbed gamma radiation dose.

Conventional and machine learning improved prediction of hydrocarbon density using volume-translation at high-pressure high-temperature conditions

ABSTRACT Non-cubic equations of state (nCEOS) are increasingly showing improved performance at predicting volumetric properties of hydrocarbons, nitrogen, and carbon dioxide at high-pressure high-temperature over volume-translation-based cubic equations of state (VT-CEOS). However, since nCEOS are rather complex, a less mathematically complex and more accurate CEOS is desired. Hence, in this study, we have explored different techniques, including conventional (non-linear regression) and machine learning-based approaches (random forest) to predict a more accurate molar volume deviation term of the VT-CEOS. We used an extensive high-pressure and high-temperature PVT dataset ranging from 50 to 150 MPa and 300 – 500 K respectively in this study. The VT was modeled as a function of reduced temperature only as well as reduced temperature and molecular weight/critical pressure of the pure hydrocarbon components. Statistical analyses and graphs displayed high performance of the developed predictive models over existing VT-CEOS models applied to HPHT and PC–SAFT. More specifically, the machine learning model gave 99% accuracy while the accuracy of the conventional approach ranged from 60-98%. To the best of the knowledge of the authors, the application of machine learning to estimating volume-translation based on CEOS for pure hydrocarbon components of natural gas and heavy hydrocarbons is nonexistent. This paper presents the first application of physics-based machine learning and the use of features that honors thermodynamic principles for prediction of hydrocarbon density.

Comparisons of Some Selected Physiological and Physical Aspects of Snow Skaters and Rock Climbers of Jammu and Kashmir

Researchers have shown their interest in taking up this issue to assess and compare several physical and physiological variables between snow skaters and rock climbers JAMMU and KASHMIR. The investigators limited their studies to physical and physiological variables: flexibility, BMI, tidal volume, and cardiovascular endurance. The study was conducted on 60 players, all subjects were from JAMMU and KASHMIR, and the sampling technique adopted for topic selection from both groups was carried out through the random sampling method. Data for comparing various physical and physiological variables is collected through standardized and scientifically approved testing devices. The standard deviation calculated from the snow-skaters' four variables and rock-climbing JAMMU and KASHMIR, namely the mean and standard deviation of the rock climber's tidal volume, is (455.74 ± 78.94), and the mean and standard deviation of the tidal volume of the snow rate. Skaters were (497.3 ± 82.07), with a mean difference of 42.56. The mean and standard deviation of rock climbers' BMI were (20.76 ± 1.04) and snowboarding (23.54 ± 1.89), respectively, with a mean difference of 2.77. The mean and standard deviation of rock climber flexibility is (24.65 ± 4.3) and snow skater sane is (21.74 ± 4.01) with a mean difference of 2.91, mean and standard deviation of vo2 Max snow skater is (58.24 ± 3.68) and the mean and standard deviation of vo2max calculated from the rock climber is (70.4 ± 4.03) with a mean difference of 11.8. Therefore rock climbers were excellent at all BMI, lung tidal volume, and endurance but lower in flexibility than snow skaters. The practical implications of this study show that rock climbing is better for overall health than snowboarding. Not much effort is required for snowboarding as it is necessary for rock climbing, which may cause better physical and physiological development of the rock climbing profile.

Effect of Aqua Therapy Exercises on Postmastectomy Lymphedema: A Prospective Randomized Controlled Trial.

Objective To investigate the effect of aqua therapy resistance exercise on arm volume, pain, and shoulder range of movements in post-mastectomy lymphedema.MethodsThis was a single-blind randomized controlled trial. Fifty eligible breast cancer survivors (median, 10 years after surgery) with lymphedema (median, 21% inter-limb difference) were assigned randomly to group A (n=25) or control group B (n=25). The study group underwent 60 minutes of aqua therapy exercise comprising of warm-up for 10 minutes, 40 minutes of strengthening exercises, and 10 minutes of cooling down, three times a week for 8 weeks. The control group underwent 60 minutes of land-based exercise three times a week for 8 weeks. Arm volume calculated by measuring the arm circumference, shoulder flexion, and abduction range of motion (ROM), and pain using a visual analog scale (VAS) were assessed at baseline and after 8 weeks of treatment.ResultsThere was a statistically significant difference in limb volume, shoulder flexion and abduction ROM, and VAS scores in favor of the study group (p<0.001) after 8 weeks of intervention. The mean±standard deviation for limb volume, shoulder flexion, abduction, and pain score were 2,108.71±200.97 mL, 169.68°±4.54°, 150.44°±3.92°, and 3.16±1.1 in the study group and 2,256.41±186.94 mL, 147.36°±5.32°, 131.32°±4.38°, and 5.68±0.94 in the control group, respectively.ConclusionAdding aqua therapy resistance exercise to routine physical therapy might be more effective in decreasing the limb volume and pain intensity and improving ROM of the shoulder in postmastectomy lymphedema.

Individualized brain development and cognitive outcome in infants with congenital heart disease.

Infants with congenital heart disease are at risk of neurodevelopmental impairments, the origins of which are currently unclear. This study aimed to characterize the relationship between neonatal brain development, cerebral oxygen delivery and neurodevelopmental outcome in infants with congenital heart disease. A cohort of infants with serious or critical congenital heart disease (N = 66; N = 62 born ≥37 weeks) underwent brain MRI before surgery on a 3T scanner situated on the neonatal unit. T2-weighted images were segmented into brain regions using a neonatal-specific algorithm. We generated normative curves of typical volumetric brain development using a data-driven technique applied to 219 healthy infants from the Developing Human Connectome Project (dHCP). Atypicality indices, representing the degree of positive or negative deviation of a regional volume from the normative mean for a given gestational age, sex and postnatal age, were calculated for each infant with congenital heart disease. Phase contrast angiography was acquired in 53 infants with congenital heart disease and cerebral oxygen delivery was calculated. Cognitive and motor abilities were assessed at 22 months (N = 46) using the Bayley scales of Infant and Toddler Development–Third Edition. We assessed the relationship between atypicality indices, cerebral oxygen delivery and cognitive and motor outcome. Additionally, we examined whether cerebral oxygen delivery was associated with neurodevelopmental outcome through the mediating effect of brain volume. Negative atypicality indices in deep grey matter were associated with both reduced neonatal cerebral oxygen delivery and poorer cognitive abilities at 22 months across the whole sample. In infants with congenital heart disease born ≥37 weeks, negative cortical grey matter and total tissue volume atypicality indices, in addition to deep grey matter structures, were associated with poorer cognition. There was a significant indirect relationship between cerebral oxygen delivery and cognition through the mediating effect of negative deep grey matter atypicality indices across the whole sample. In infants born ≥37 weeks, cortical grey matter and total tissue volume atypicality indices were also mediators of this relationship. In summary, lower cognitive abilities in toddlers with congenital heart disease were associated with smaller grey matter volumes before cardiac surgery. The aetiology of poor cognition may encompass poor cerebral oxygen delivery leading to impaired grey matter growth. Interventions to improve cerebral oxygen delivery may promote early brain growth and improve cognitive outcomes in infants with congenital heart disease.

Online program engagement and audience size during television ads

This research explores how television viewers’ online program engagement (OPE)—engagement in social media conversations about television programs—relates to audience size during ads in those programs. We leverage a multisource dataset of 8417 ad instances, volume and deviation measures of OPE activity (program-related Twitter mentions), and audience size during ads. We show that increases in OPE volume and positive deviations from the episode’s average level of OPE before an ad relate to higher ad audience size. To explain, we argue that OPE reflects viewers’ program involvement which attenuates their channel-changing behavior during ads. Positive OPE deviations moreover relate to higher ad audience sizes most strongly for earlier ads in a break. Our results help television networks and advertisers strategically determine ad placements for increased ad audience size by highlighting social episodes (characterized by high OPE volume) and social moments (characterized by positive OPE deviations) as attractive advertising environments.

Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones.

To evaluate the ability of a semi-automated radiomic analysis software in predicting the likelihood of spontaneous passage of urinary stones compared with manual measurements. Symptomatic patients visiting the emergency department with suspected stones in either kidney or ureters who underwent a CT scan were included. Patients were followed for up to 6 months for the outcome of a trial of passage. Maximum stone diameters in axial and coronal images were measured manually. Stone length, width, height, max diameter, volume, the mean and standard deviation of the Hounsfield units, and morphologic features were also measured using automated radiomic analysis software. Multivariate models were developed using these data to predict subsequent spontaneous stone passage, with results expressed as the area under a receiver operating curve (AUC). One hundred eighty-four patients (69 females) with a median age of 56 years were included. Spontaneous stone passage occurred in 114 patients (62%). Univariate analysis demonstrated an AUC of 0.83 and 0.82 for the maximum stone diameter determined manually in the axial and coronal planes, respectively. Multivariate models demonstrated an AUC of 0.82 for a model including manual measurement of maximum stone diameter in axial and coronal planes. The same AUC was found for a model including automatic measurement of maximum height and diameter of the stone. Further addition of morphological parameters measured automatically did not increase AUC beyond 0.83. The semi-automated radiomic analysis of urinary stones shows similar accuracy compared with manual measurements for predicting urinary stone passage. Further studies are needed to predict clinical impacts of reporting the likelihood of urinary stone passage and improving inter-observer variation using automatic radiomic analysis software.

Volume decomposition and volatility in dual-listing H-shares

We investigate the volume impact on volatility for 14 Chinese ADRs and their underlying H-shares. We decompose volume into expected and unanticipated components and include those as determinants of conditional volatility in a bivariate GARCH model for each ADR and its underlying H-share. Expected volume denotes liquidity, while unanticipated volume implies information content in volume. The GARCH model fits the data well. In addition to the conventional GARCH parameters, for ADRs and their underlying H-shares, expected and unanticipated volumes significantly but asymmetrically affect both the variance and the covariance functions. Further, volume components asymmetrically impact volatility of ADRs and H-shares in high- versus low-liquidity and high- versus low-liquidity-risk buckets denoted by volume and standard deviation of volume, respectively.