Real Volume Research Articles

The determination of the optimal threshold on measurement of thyroid volume using quantitative SPECT/CT for Graves' hyperthyroidism

PurposeTo investigate the optimal threshold for measuring thyroid volume in patients with Grave's hyperthyroidism (GH) by SPECT/CT.Materials and methodsA 53 mL butterfly-shaped hollow container made of two 45-degree transparent elbows was put into a NEMA IEC phantom tank. The butterfly-shaped container and the tank were then filled with Na99mTcO4 of different radioactive concentrations, respectively, which could simulate thyroid gland with GH by different target-to-background ratios (T/B) (200:1, 600:1, 1000:1). The different T/B of planar imaging and SPECT/CT were acquired by a Discovery NM/CT 670 Pro SPECT/CT. With Thyroid software (Version 4.0) of GE-Xeleris workstation, the region of the thyroid gland in planar imaging was delineated. The thyroid area and average long diameter of both lobes were substituted into the Allen formula to calculate the thyroid volume. The calculation error was compared with the actual volume. Q-Metrix software was used to perform CT-based attenuation correction, scatter correction, resolution recovery. Ordered-subsets expectation maximization was used to reconstruct SPECT data. 20%, 25%, 30%, 40%, 50%, 60% thresholds were selected to automatically delineate the volume of interest and compared with the real volume, which determinated the optimal threshold. We measured the thyroid volume of 40 GH patients using the threshold and compared the volumes obtained by planar imaging and ultrasound three-dimensional. The differences of the volumes with different T/B and thresholds were compared by the ANOVA and least significant difference t test. The volumes delineated by SPECT/CT were evaluated using ANOVA, least significant difference t test, correlation analysis and, linear regression and Bland–Altman concordance test plot. The differences and consistency of thyroid volume were compared among the above three methods.ResultsThere was no significant difference in the results between different T/B models (P > 0.05). The thyroid volume calculated by the planar imaging formula method was higher than the real volume, with an average overestimation of 22.81%. The volumes delineated by SPECT/CT threshold automatically decreased while the threshold increased. There were significant differences between groups with different thresholds (P < 0.001). With an average error of 3.73%, the thyroid volume analyzed by the threshold of 25% was close to the results of ultrasound measurement (P > 0.05). Thyroid volume measured by planar imaging method was significantly higher than ultrasound and SPECT/CT threshold automatic delineation method (P < 0.05). The agreement between the SPECT/CT 25% threshold and ultrasound (r = 0.956, b = 0.961) was better than that between the planar imaging and ultrasound (r = 0.590, b = 0.574). The Bland–Altman plot also showed that the thyroid volume measured by the 25% threshold automatic delineation method was in good agreement with the ultrasound measurement.ConclusionsThe T/B has no effect on the measurement of thyroid volume in GH patients; planar imaging method can significantly overestimate thyroid volume in GH patients, and 25% threshold automatic delineation method can obtain more accurate thyroid volume in GH patients.

ОСОБЕННОСТИ ДИВЕРСИФИКАЦИИ РИСКОВ ВАЛЮТНЫХ КОЛЕБАНИЙ ПРИ ФОРМИРОВАНИИ ОПЕРАЦИОННОЙ ЛИКВИДНОСТИ КОРПОРАЦИИ ПОСРЕДСТВОМ ИСПОЛЬЗОВАНИЯ ЦИФРОВЫХ ФИНАНСОВЫХ ИНСТРУМЕНТОВ

The article considers the impact of currency fluctuation risks on the operating liquidity of companies in the current macroeconomic environment. It describes the main directions of currency fluctuation risks, as well as their impact on the real volume of temporarily free cash, solvency and stability of companies in the market. To reduce the risks of currency fluctuations, it is suggested to use a multi-currency basket and invest in alternative assets, such as cryptocurrencies and digital financial assets.

Рупия против мировых резервных валют в российско-индийской торговле

This article analyses possible connection between sharp depreciation of the Russian Rouble in the second half of 2023 and the growing usage of Indian Rupees for settlement of Russo-Indian trade. Some experts explained that depreciation by the ‘Rupee trap’, which was created by quick growth of Russian exports to India while the opposite flow was not significantly changed. They suggested that superior export revenues of Russian companies from exports to India were accumulated in Rupee accounts in Indian banks. Then somehow, these Rupees have penetrated the foreign exchange market in Russia and have depreciated the Rouble exchange rate. Author has analysed available statistics from both countries and came to conclusion that described problem is factitious. It is true that the usage of Rupee for invoicing in the external trade of India has increased in the last couple of years. However, the real volume of such usage is much smaller than the volume of Indian external trade. Indian Rupee is not a freely convertible currency, so exchange of Rupee assets for other currencies is a subject of a range of restrictions and quotas. Foreign exporters to India are aware of this and in practice agree to accept Rupees only in limited amounts. A number of top-ranking people from Russia and India, who were well informed about mutual trade, confirmed such practice. Therefore, there is no reason to consider that Russian exporters might accumulate too big Rupee assets. In addition, statistics of currency invoicing of Russian external trade in 2022–2023 suggest that volumes of inward and outward flows of non-reserve currencies (like Renminbi, Rupee, Dirham etc.) are about equal. This means that demand/offer of such currencies are balanced. However, for the same period, the demand for Roubles outside Russia was bigger than their offer from Russia. So all together, this does not confirm assertions that increase of Rupee (or other non-reserve currency) assets was the main cause of the sharp Rouble depreciation in 2023.

Visualization and characterization of agricultural sprays using machine learning based digital inline holography

Accurate characterization of agricultural sprays is crucial to predict in-field performance of liquid applied crop protection products. In this paper, we introduce a robust and efficient machine learning (ML) based Digital In-line Holography (DIH) algorithm to accurately characterize the droplet field for a wide range of commonly used agricultural spray nozzles. Compared to non-ML based DIH processing, the ML-based algorithm enhances accuracy, generalizability, and processing speed. The ML-based approach employs two neural networks: a modified U-Net to obtain the 3D droplet field from the numerically reconstructed optical field, followed by a VGG16 classifier to reduce false positives from the U-Net prediction. The modified U-Net is trained using holograms generated using a single spray nozzle (XR11003) at three different spray locations; center, half-span, and the spray edge to create training data with different number densities and droplet size ranges. VGG16 is trained using the minimum intensity projection of the droplet 3D point spread function (PSF). Data augmentation is used to increase the efficiency of classification and make the algorithm generalizable for different measurement settings. The model is validated using National Institute of Standards and Technology (NIST) traceable glass beads and six different agricultural spray nozzles representing various spray characteristics. The principal results demonstrate a high accuracy rate, with over 90% droplet extraction and less than 5% false positives, regardless of droplet number density and size. Compared to traditional spray measurement techniques, the new ML-based DIH methodology offers a significant leap forward in spatial resolution and generalizability. We show that the proposed ML-based algorithm can extract the real cumulative volume distribution of the NIST beads, where the LD system measurements are biased towards droplets moving at slower speeds. Additionally, the ML-based DIH approach enables the estimation of mass and momentum flux at different locations and the calculation of relative velocities of droplet pairs, which are difficult to obtain using conventional spray characterization techniques.

Automatic GAN-based MRI volume synthesis from US volumes: a proof of concept investigation

Usually, a baseline image, either through magnetic resonance imaging (MRI) or computed tomography (CT), is captured as a reference before medical procedures such as respiratory interventions like Thoracentesis. In these procedures, ultrasound (US) imaging is often employed for guiding needle placement during Thoracentesis or providing image guidance in MISS procedures within the thoracic region. Following the procedure, a post-procedure image is acquired to monitor and evaluate the patient’s progress. Currently, there are no real-time guidance and tracking capabilities that allow a surgeon to perform their procedure using the familiarity of the reference imaging modality. In this work, we propose a real-time volumetric indirect registration using a deep learning approach where the fusion of multi-imaging modalities will allow for guidance and tracking of surgical procedures using US while displaying the resultant changes in a clinically friendly reference imaging modality (MRI). The deep learning method employs a series of generative adversarial networks (GANs), specifically CycleGAN, to conduct an unsupervised image-to-image translation. This process produces spatially aligned US and MRI volumes corresponding to their respective input volumes (MRI and US) of the thoracic spine anatomical region. In this preliminary proof-of-concept study, the focus was on the T9 vertebrae. A clinical expert performs anatomical validation of randomly selected real and generated volumes of the T9 thoracic vertebrae and gives a score of 0 (conclusive anatomical structures present) or 1 (inconclusive anatomical structures present) to each volume to check if the volumes are anatomically accurate. The Dice and Overlap metrics show how accurate the shape of T9 is when compared to real volumes and how consistent the shape of T9 is when compared to other generated volumes. The average Dice, Overlap and Accuracy to clearly label all the anatomical structures of the T9 vertebrae are approximately 80% across the board.

Customers’ behavior changes of Russian representatives of generations X and Z due to social and economic factors in 2022

The article is devoted to the study of consumer expectations influence on the volume of produced spending within the framework of consumer preferences. The relevance of the study is related to the current processes in consumer market, which are characterized, on the one hand, by decrease in population income real volume, and on the other hand, by withdrawal of major international brands from Russia due to sanctions pressure. The classical theory of William Strauss and Neil Howe developed in 1991 was chosen as a methodological basis for demographic division of respondents of different generations. The purpose of the study is to analyze consumer preferences within two demographic generations (generations X and Z) related to spending due to expectation of crisis phenomena in consumer market. To test this hypothesis, a questionnaire survey was conducted among the representatives of the two generations. The respondents were students aged 17–21 (generation Z) and their parents aged 45–55 (generation X).

FREELANCING IN THE KAZAKHSTAN MARKET: NEW OPPORTUNITIES

The purpose of the research. Assessment of the real volume of the freelance services market, the scale of freelancing in the Kazakh labor market based on the available official data from the information systems.Methodology includes the use of methods: statistical and quantitative analysis of labor market indicators; qualitative analysis in reviewing the works of domestic and foreign scientists on the topic of research; graphic methods of visualizing the results of the study.Originality/value of the research. The paper offers the results of the analysis of the current state and key problems of Kazakhstan's freelancing market; it assesses the scale of domestic freelancing, considered new prospects for the development of freelance, its social and economic role in solving the problems of reducing unemployment and ensuring employment of the population.Findings. Freelancing in Kazakhstan is currently not widespread and has little impact on the labor market, although many freelancers are still out of the picture. The freelance services market is closely interconnected with the situation on the labor market. Rather high level of unemployment, lack of opportunity to get a job in their specialty force people to this type of employment.

Using an Artificial Neural Network to Record and Analyse the Performance Indicators of a Transport Enterprise

Recently, the issue of determining actual values of passenger flow processed by urban public and suburban transport on each section of the route in real time has become even more relevant since those values affect planning, organisation of operations and performance of transport enterprises.It is not possible to assess the real volume of passenger flow with the number of tickets issued to passengers due to the large number of unaccounted passengers (the discrepancy between the number of tickets issued to passengers and the real number of passengers transported).The objective of the study which results are described in the article was to develop an intelligent system for calculating and analysing the transport enterprise performance, which allows automatically collecting, processing and analysing information about passenger flows, calculating the passenger rotation ratio on the route, drawing up optimal bus schedules and timetables, adjusting vehicle traffic intervals, determining the need for rolling stock to minimise the likelihood that a passenger is denied boarding, improving the quality of passenger service and reducing the operating costs of a transport enterprise.Real-time calculation of passenger flow values for each vehicle on the route of urban public transport is carried out by a quantitative method based on artificial neural network technology, which allows automatic processing of a large amount of information from CCTV cameras installed in vehicle interiors.The use of theoretical research methods helped to create an intelligent system capable to analyse and compare the number of tickets issued to passengers with the actual number of passengers transported on Samara city public transport route, the results were displayed through a graphical user interface. It was possible to reveal dependences of the number of unaccounted passengers on the route on the amount of passenger flow and the time of day.A possibility of using the proposed intelligent system in commuter trains was noted, provided that the cars are equipped with video surveillance cameras.

Contouring Analysis on Synthetic Contrast-Enhanced MR from GRMM-GAN and Implications on MR-Guide Radiation Therapy

MR-guided linear accelerators have been commercialized making MR-only planning and adaptation an appealing alternative circumventing MR-CT registration. However, obtaining daily contrast-enhanced MR images can be prohibitive due to the increased risk of side effects from repeated contrast injections. In this work, we evaluate the quality of contrast-enhanced multi-modal MR image synthesis network GRMM-GAN (gradient regularized multi-modal multi-discrimination sparse-attention fusion generative adversarial network) for MR-guided radiation therapy. With IRB approval, we trained the GRMM-GAN based on 165 abdominal MR studies from 65 patients. Each study included T2, T1 pre-contrast (T1pre), and T1 contrast enhanced (T1ce) images. The two pre-contrast MR modalities, T2 and T1pre images were adopted as inputs for GRMM-GAN, and the T1ce image at the portal venous phase was used as an output. Ten MR scans containing 21 liver tumors were selected for contouring analysis. A Turing test was first given to six radiation oncologists, in which 100 real T1ce and synthetic T1ce image slices are randomly given to the radiation oncologists to determine the authenticity of the synthesis. We then invited two radiation oncologists (RadOnc 1 and RadOnc2) to manually contour the 21 liver tumors independently on the real T1ce images. RadOnc2 then performed contouring on the respective synthetic T1ce MRs. DICE coefficient (defined as the intersection over the average of two volumes) and Hausdorff distance (HD, measuring how far two volumes are from each other) were used as analysis metrics. The DICE coefficients were calculated from the two radiation oncologists' contours on the real T1ce MR for each tumor. The DICE coefficients were also calculated from RadOnc 2's contours on real and synthetic MRs. Besides, tumor center shifts were extracted. The tumor center of mass coordinates was extracted from real and synthetic volumes. The difference in the coordinates indicated the shifts in the superior-inferior (SI), right-left (RL), and anterior-posterior (AP) directions between real and synthetic tumor volumes. An average of 52.3% test score was achieved from the six radiation oncologists, which is close to random guessing. RadOnc 1 and RadOnc 2, who had participated in the contouring analysis, achieved an average DICE of 0.91±0.02 from tumor volumes drawn on the real T1ce MRs. This result sets the inter-operator uncertainty baseline in the real clinical setting. RadOnc 2 achieved an average DICE (real vs. synth) of 0.90±0.04 and HD of 4.76±1.82 mm. Only sub-millimeter (SI: 0.67 mm, RL: 0.41 mm, AP: 0.39 mm) tumor center shifts were observed in all three directions. The GRMM-GAN method has the potential for MR-guided liver radiation when contrast agents cannot be administered daily and provide synthetic contrast-enhanced MR for better tumor targeting. The network can produce synthetic MR images with satisfactory contour agreement and geometric integrity.

Semi-microscopic optical-model with channel coupling analysis to describe neutron-nucleus scattering of light and heavy nuclei

Many studies utilizing various potential models have been conducted on the scattering of nucleons from nuclei. In our study, we added channel coupling to a semi-microscopic optical model. With incident energies between 10 and 30 MeV, we sought to compare the predicted reaction observables for the neutron scattering of the following nuclei: 12C, 16O, 54Fe, 58Ni, 120Sn, and 208Pb. We did this twice, once using the density-dependent M3Y-Reid nucleon-nucleon effective bare interaction and once using the density-independent M3Y-Reid effective bare interaction. The remaining terms of the optical potential model take the form of Woods-Saxon and its derivatives, and the real volume term is obtained by folding the NN effective bare potential over the density of the nuclear target using the density-dependent M3Y-Reid NN effective bare interaction and density-independent M3Y-Reid NN effective bare interaction. To investigate how the potential characteristics depend on energy, the ground state is connected to a select few low-lying collective excited states. The density-dependent M3Y-Reid NN effective bare interaction-based semi-microscopic model reproduces the reaction features and forecasts the experimental total cross sections. The parameters of potential depth exhibit a linear energy dependence. We contrast the outcomes of the M3Y-Reid density-dependent model with those attained using the M3Y-Reid nucleon-nucleon effective bare interaction, which is density-independent. The M3Y Reid density-dependent model performs well when the two models are compared.

Modeling the behavior of the acetabular axis and the axis of the ischial tuberosities during the transition from a standing to a sitting position

Introduction The success of the treatment of patients with degenerative diseases of the spine and concomitant damage to the hip joint depends on the understanding of the biomechanics of movements in the spinal-pelvic segment. After a thorough analysis of the biomechanical processes occurring in the spine-pelvis system during the transition from a standing to a sitting position, it becomes clear that the acetabular axis of rotation of the pelvis in space is not the only one.The purpose of the study was to develop and test a virtual model of the pelvis to study the kinematics of the movement of the spinal-pelvic complex with a description of the emergence of the iscial axis of rotation by changing the position from standing to sitting.Materials and methods The problem was solved using the finite element method. The bones were modeled as absolutely rigid bodies. The main ligaments and muscles were modeled using finite element springs: elastic fragments with specified rheological characteristics. The study of contact interaction was carried out for pairs: "femoral head – acetabulum" and "ischial tuberosities - chair surface".Results A new axis of rotation was revealed, the ischial axis, which corresponded to the points of initial contact of the ischial tuberosities with the surface of the chair. The axis of the acetabulum rotated by 7.1° relative to the ischial axis and at the final moment shifted in the horizontal direction relative to the acetabular axis by 8.83 mm. The gap between the surfaces of the femoral head and the acetabulum was about 8 mm.Discussion The study shows that the pelvis rotates depending on the position around two axes: acetabular and ischial ones, hence it follows that the acetabular axis oscillates back and forth during ante- and retroversion, that is, it is non-static. Shortcomings of the model: 1) muscles and ligaments were modeled using FE springs, the end and beginning of which were set by two points, and the muscles and ligaments in the real body are attached along the entire surface of the bones; 2) soft tissues were not modeled in real volume. The merit of the study is the contact interaction of the pelvis with the chair and its rotation relative to the ischial axis, while other studies consider the rotation of the pelvis only relative to the acetabular axis.Conclusion A new axis of rotation arises due to the contact interaction of the pelvic bone with the surface of the chair when the skeleton moves from a standing position to a sitting position, the ischial axis. The gap between the surfaces of the femoral head and the acetabulum was about 8 mm. It is advisable to conduct a clinical study.

Analysis on the Difference between the Practical Brassiere Size and Real Breast Volume.

Brassiere cup size is defined as the difference in chest circumference between the inframammary fold and the fullest part of the breast. However, a large number of women are not aware of the correct definition and are prone to wearing incorrectly-sized brassieres. In this report, the authors compared the cup size of worn brassieres and the actual measurement. This study was a retrospective review of patients who had undergone breast reconstruction operation between May 2020 and June 2021. All patients who visited the plastic surgery clinic for breast reconstruction were inquired about their cup size, and their breast circumferences were measured. The patient demographic information, ptosis grade, mastectomy specimen weight, measured breast circumference, and known cup size were analyzed. Overall, 163 women were included. Notably, 92 of 163 patients (56.4%) were wearing a correctly-sized brassiere. Patients were more likely to wear a correctly-sized brassiere as the cup size became smaller. Moreover, patients with A-cup breasts tended to wear larger brassieres, whereas patients with B and C-cup breasts tended to wear smaller brassieres than their actual breast cup size. Approximately one in two women do not know their correct brassiere cup size. Women tend to wear a brassiere of the wrong size as their cup size becomes larger. Therefore, it is important for surgeons to be aware of their patient's brassiere wearing habit and their perception when a surgery, such as augmentation or reconstruction, is planned.

Epidemiology, clinical profile and outcome of acute kidney injury in intensive coronary care unit

Background: The incidence of AKI in cardiac ICU is attributed mainly to Heart Failure and Acute Coronary Syndrome. AKI occurs commonly in the setting of AHF, and is termed CRS type 1. Biomarkers and bioelectrical impedance analysis can be helpful in estimating the real volume overload and may be useful to predict and avoid AKI. The role of UF remains controversial, and it is currently recommended only for diuretic-resistant patients. Objective of current study was to study demographic &amp; clinical profile and outcome of patients with AKI in intensive coronary care unit. Methods: This prospective study was conducted in ICCU of R.N.T. Medical College, Udaipur. All the patients with increase in serum creatinine &gt;50% were included in the study. Detailed investigations like urinary analysis, renal function tests (blood urea, serum creatinine, serum electrolytes), USG whole abdomen, 12 lead ECG, Echocardiography and Troponin T. Results: Among cases 56.67% had ADHF, 25% had MI, 10% had structural heart disease, 3.3% had systemic illness, 1.67% had cardiogenic shock, 1.67% were cardiac surgery associated and 1.67% had other causes of AKI. 30.0% of cases required ionotropic support while 2.5% of controls required ionotropic support. 5.0% of cases required ventilator support &amp; renal replacement therapy while none of the controls required these. Conclusions: Patients with AKI had worse outcomes when compared to non-AKI. Mortality among cases was significantly higher than controls, 10% among cases versus only 2.5% in controls.

Micro-CT driven characterization and validation of constituents’ properties used in origami-inspired foldable composites fabricated via different manufacturing processes

High packaging efficient lightweight jointless deployable folding structures are nowadays fabricated from combination of rigid and thin flexible elastic hinges using fiber reinforced polymers composites (FRPCs) for various applications such as space, robotics, flexible electronics, etc. It is of high importance to optimize these structures in the design phase using computer aided analysis tools for which the structural-level elastic constants are challenging to find experimentally. In this work, a generic X-ray computed tomography (micro-CT) driven framework based on voxel modeling approach was developed to virtually characterize the smallest building block of a typical large-scale foldable structure that consists of a rigid region and elastic hinge needed for folding operation. The voxel-based description of a real representative volume element (RVE) was generated using the images obtained from the micro-CT. The homogenized mechanical properties for each of the material systems was then obtained by multi-parameter component segmentation and subsequent directional averaging of the corresponding voxels. Three-dimensional void analyses were also shown using the micro-CT based voxel modeling. The accuracy of the non-destructive framework was demonstrated for four materials systems, based on different combinations of the matrix and fabric architectures in comparison with the mechanical tests. The homogenized mechanical properties obtained using the present framework based on the real RVE showed good agreement with the experimental results providing a foundation for a structural-level computer aided analysis.

Semi-Supervised Modified-UNet for Lung Infection Image Segmentation

Automatic lung infection segmentation in computed tomography (CT) scans can offer great assistance in radiological diagnosis by improving accuracy and reducing time required for diagnosis. The biggest challenges for deep learning (DL) models in segmenting infection region are the high variances in infection characteristics, fuzzy boundaries between infected and normal tissues, and the troubles in getting large number of annotated data for training. To resolve such issues, we propose a Modified U-Net (Mod-UNet) model with minor architectural changes and significant modifications in the training process of vanilla 2D UNet. As part of these modifications, we updated the loss function, optimization function, and regularization methods, added a learning rate scheduler and applied advanced data augmentation techniques. Segmentation results on two Covid-19 Lung CT segmentation datasets show that the performance of Mod-UNet is considerably better than the baseline U-Net. Furthermore, to mitigate the issue of lack of annotated data, the Mod-UNet is used in a semi-supervised framework (Semi-Mod-UNet) which works on a random sampling approach to progressively enlarge the training dataset from a large pool of unannotated CT slices. Exhaustive experiments on the two Covid-19 CT segmentation datasets and on a real lung CT volume show that the Mod-UNet and Semi-Mod-UNet significantly outperform other state-of-theart approaches in automated lung infection segmentation.

Formation of the system of financial support of higher education institutions in Ukraine

In the conditions of a military challenge, the financial system of Ukraine is under significant pressure, which also affects the supply of universities. The purpose of the article is to analyze the formation of the system of financial support of higher education institutions in Ukraine. System analysis, comparison, modeling became the main methods for writing research. The research used indicators of expenditures of the consolidated budget of Ukraine. In the results, the role of the inflationary challenge in the financial support of higher education institutions of Ukraine was traced, and it was established that in fact the real volumes of budget financing of the industry (at the level of 7% of GDP) were never reached. Ensuring financial diversification is an important aspect for overcoming negative manifestations of lack of funds. The article traces separate methods: the introduction of a targeted tax, independent financial activity and the help of patrons, implementation of joint projects with private structures, receiving international financial assistance. With the help of content analysis, the strengths and weaknesses of all the proposed paths were determined. The conclusions state that in the conditions of martial law, the last two items are the most relevant sources of filling university budgets.

Real time three-dimensional transthoracic echocardiographic segmental volume analysis: quantitative and objective tool for assessing regional wall motion abnormalities in ischemic heart disease

Abstract Funding Acknowledgements Type of funding sources: None. Background Evaluation of regional wall motion abnormality (RWMA) by 2D echocardiography (2DE) plays an important role in the diagnosing ischemic heart disease (IHD). However, 2DE is disadvantaged by being subjective, semi-quantitative, and expert-dependent. Recently, a method of measuring LV segmental volume by 3DE has been introduced, which enabled volume changes in LV regional to be measured. This study aimed to demonstrate the clinical usefulness of 3DE segmental volume analysis as an objective and quantitative tool for assessing RWMA in patients with IHD. Methods 33 patients with ischemic heart disease confirmed by coronary aniography and showing single vessel territory RWMA by 2DE were retrospectively enrolled. In the 2DE study, RWMAs were evaluated visually by and experienced physicians, and 17-segment bull's-eye polar maps were generated using a two-point scale, viz. 'normal' (showing normal contractility) or 'abnormal' (showing hypokinesis or akinesis). Culprit vessel territories were specified by a physician based on typical coronary artery distributions. In the 3DE study, two independent observers analyzed data using QLAB 3D quantification advanced software (version 10.0, Philips Healthcare). Segmental volumes of 17 LV segments were measured using a predetermined algorithm, and segmental volume ejection fractions (SVEFs) were calculated. Receiver operating characteristic (ROC) curve analysis was used to determine the SVEF cut-off value that best differentiated 'normal' and 'abnormal'. Using this cut-off value, 17-segment bull's-eye polar maps were generated. Reliability of correct predicting the culprit coronary arteries by 3DE bull's-eyes compared to 2DE ones was evaluated using Cohen's kappa co-efficients, which were also used for inter- and intra-observer variability analysis of 3DE bull's-eye derived culprit coronary artery predictions. Results Mean 3DE SVEFs were significantly lower for segments showing RWMA by 2DE. Additionally, among the segments determined to be normal by 2DE, 3D basal segmental EF is statistically lower than mid- and apical ones. The optimum SVEF cut-off value was 44%, with a sensitivity of 75.0% and a specificity of 73.9% (AUC = 0.801, 95% CI 0.763–0.838, p&amp;lt;0.001). The reliability of 3DE bull's-eye derived culprit coronary artery predictions was 81.8% (kappa = 0.672, 95% CI 0.555–0.789, p&amp;lt;0.001). Inter- and intra-observer variabilities of 3DE bull's-eye derived culprit coronary artery predictions were 97.0% (kappa = 0.947, 95% CI 0.894–0.100, p&amp;lt;0.001) and 93.9% (kappa = 0.897, 95% CI 0.827–0.967, p&amp;lt;0.001), respectively. Conclusion Assessment of RWMA using 3D echocardiographic segmental volume analysis was found to be feasible and reproducible, and its predictions of culprit coronary arteries well matched those of 2DE. 3DE segmental volume analysis could be used as a quantitative and objective tool for assessing RWMA in ischemic heart disease patients.

Water contact mapping and saturation estimation using simultaneous inversion of time-lapse seismic data constrained by fluid substitution and Leverett J-function analysis

The integration of a Leverett J-function analysis with the Gassmann and mass-balance equations allows the time-lapse change of seismic reflectivity to be expressed explicitly in terms of the change of the free water-contact (WC) level, reservoir porosity, and initial water saturation. Given the initial 3D distribution of water saturation and porosity and a well-log derived height-saturation-porosity function as a hard inversion constraint, synthetic modeling suggests that time-lapse seismic data can potentially be directly inverted for the change in free-water level, and time-lapse changes in the spatial variation of water saturation can thus be predicted. This integrated inversion approach is applied to a real time-lapse seismic difference volume from the Maui-B field in the Taranaki Basin, New Zealand, where the change of WC level from a baseline model is the only free parameter to be inverted and is obtained by searching for the global error minimum between tmodeled and real time-lapse seismic differences as the modeled WC level is varied. The method correctly predicts the gas depletion and a measurable rise of the water contact on the southern flank of the field.

Analysis of the data sources for sizing the phenomenon of international migration in the context of the major exodus of Romanian labor force

Being a complex and multi-criteria phenomenon, the international migration can have a lot of different meanings, which suppose different scopes and methods of estimating various data, depending on the hypotheses and research objectives pursued. In the last decade the mass-media also gave an increased importance to the phenomenon and in the era of fake news, it led to the fact that the magnitude of the phenomenon was often communicated differently from the real situation or the existing statistics. Even though there is a great diversity of data sources that could be used to estimate international migration flows, these are not directly oriented to measure migration, so great difficulties in terms of data comparability occur very often. In Romania the phenomenon of international migration has taken a large scale, the country being on the first places worldwide in terms of labor force exits to destination countries, but, practically, the Romanian authorities have very less information regarding the residence of Romanian citizens abroad and, implicitly, no data is collected regarding the real volume of the migration phenomenon. This paper aims to inventory the available data sources regarding international migration from Romania and, as much as possible, to propose solutions by which this phenomenon could be better quantified to support the development of effective migration policies. The research methodology consists in the theoretical analysis of data sources and indicators that measure the migration phenomenon in order to identify a possibility to quantify the volume of the migrant population by proposing a model that calculates the potential migrant workforce calculated as a difference between the labor resource and the employed population.

Coronary artery calcium quantification: comparison between filtered-back projection, hybrid iterative reconstruction, and deep learning reconstruction techniques.

The reference protocol for the quantification of coronary artery calcium (CAC) should be updated to meet the standards of modern imaging techniques. To assess the influence of filtered-back projection (FBP), hybrid iterative reconstruction (IR), and three levels of deep learning reconstruction (DLR) on CAC quantification on both in vitro and in vivo studies. In vitro study was performed with a multipurpose anthropomorphic chest phantom and small pieces of bones. The real volume of each piece was measured using the water displacement method. In the in vivo study, 100 patients (84 men; mean age = 71.2 ± 8.7 years) underwent CAC scoring with a tube voltage of 120 kVp and image thickness of 3 mm. The image reconstruction was done with FBP, hybrid IR, and three levels of DLR including mild (DLRmild), standard (DLRstd), and strong (DLRstr). In the in vitro study, the calcium volume was equivalent (P = 0.949) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. In the in vivo study, the image noise was significantly lower in images that used DLRstr-based reconstruction, when compared images other reconstructions (P < 0.001). There were no significant differences in the calcium volume (P = 0.987) and Agatston score (P = 0.991) among FBP, hybrid IR, DLRmild, DLRstd, and DLRstr. The highest overall agreement of Agatston scores was found in the DLR groups (98%) and hybrid IR (95%) when compared to standard FBP reconstruction. The DLRstr presented the lowest bias of agreement in the Agatston scores and is recommended for the accurate quantification of CAC.