Sharp Loss Research Articles

COVID-19 employment shocks and safety net expansion: Health effects on displaced workers

COVID-19 precipitated sharp job losses, concentrated in the service sector. Prior research suggests that such shocks would negatively affect health and wellbeing. However, the nature of the pandemic crisis was distinct in ways that may have mitigated any such negative effects, and historic expansions in unemployment insurance (UI) may have buffered workers from negative health consequences. We draw on employer-employee linked cross-sectional (N = 15,219) and panel (N = 3307) data from service sector workers to estimate the effects of job loss on health and wellbeing during COVID-19. Using employer fixed-effects, lagged dependent variables, and models that focus on job loss due to establishment closure to minimize confounding, we find negative effects of unemployment on health and wellbeing. However, in periods when UI was most generous or in cases where UI fully replaced pre-job loss wages, unemployed workers who received UI were no worse off than those who remained employed. Although UI protected against worsening health, receiving generous UI benefits did not confer a health advantage relative to working at the height of the pandemic.

Computational investigations of Ka-226T helicopter coaxial rotor aerodynamics in the vortex ring state

The vortex ring states are observed when the rotor is flowed at positive angles of attack. For the main rotor, these conditions are realized during a steep descent of the helicopter at low speeds. The rotor vortex ring states are affected by significant phenomena related to the behavior of its aerodynamics, including negative phenomena. The latter is, firstly, referred to decrease in rotor thrust, increase in the required power, pulsations of thrust and torque, unsteady flapping blade motion, etc. In terms of helicopter piloting, it means a sharp loss of altitude, increase in the control force, a high level of vibration, defocusing attenuation of rotor spinning cone, as well as controllability deterioration. All these factors determine the relevance of research on these modes and the importance of solving a problem of defining their boundaries. Recently, due to the rapid development of computer technologies and computational models, it has become practical to perform numerical research of the rotor aerodynamics in vortex ring states. The paper presents the study results of Ka-226T helicopter coaxial rotor aerodynamics in steep descent modes in the field of vortex ring states. The angles of rotor attack αВ = 90...30° and the range of vertical descent velocities Vу = 0...26 m/s are considered. The original nonlinear bladed vortex model of the rotor developed at the Moscow Aviation Institute (MAI) was used. The total and distributed aerodynamic rotor characteristics were calculated. The shapes of the vortex wake and the rotor flow patterns were analyzed. The boundaries of the vortex ring states in velocity coordinates “Vx − Vу” were constructed according to various criteria reflecting the known features of these states. The results obtained significantly complement the existing experience of experimental and numerical research in this field.

Sources of Algeria's economic growth, 1979–2019: Augmented growth accounting framework and growth regression method

This paper examines the sources of economic growth in Algeria, studying the key drivers of their slow and weak economic performance, during the period of 1979–2019 from the perspective of the augmented growth accounting framework and the growth regression method. More specifically, the paper uses the augmented growth accounting framework to decompose the aggregate growth of an individual economy to determine the contribution of various inputs and the total factor productivity. The growth regression method, then, links the growth performance of a given country to a set of economic, social, and institutional variables to identify the deep drivers of its economic growth. Results of the accounting framework show that Algeria's growth performance has been weak and modest for decades. This is due, mainly, to labor growth with weak gain in capital accumulation and to sharp losses in the total factor productivity growth. Furthermore, results of the econometrics study stress the importance of the political, institutional, and economic variables and the macroeconomic stability as potential factors that may affect growth in Algeria. These findings highlight the need for policymakers to identify and to target these determinants to improve the long‐run economic growth in Algeria.

Hydrogel Alginate Considerations for Improved 3D Matrix Stability and Cell Graft Viability and Function in Studying Type 1 Diabetes In Vitro.

Biomedical devices such as islet-encapsulating systems are used for treatment of type 1 diabetes (T1D). Despite recent strides in preventing biomaterial fibrosis, challenges remain for biomaterial scaffolds due to limitations on cells contained within. The study demonstrates that proliferation and function of insulinoma (INS-1) cells as well as pancreatic rat islets may be improved in alginate hydrogels with optimized gel%, crosslinking, and stiffness. Quantitative polymerase chain reaction (qPCR)-based graft phenotyping of encapsulated INS-1 cells and pancreatic islets identified a hydrogel stiffness range between 600 and 1000Pa that improved insulin Ins and Pdx1gene expression as well as glucose-sensitive insulin-secretion. Barium chloride (BaCl2) crosslinking time is also optimized due to toxicity of extended exposure. Despite possible benefits to cell viability, calcium chloride (CaCl2)-crosslinked hydrogels exhibited a sharp storage modulus loss in vitro. Despite improved stability, BaCl2-crosslinked hydrogels also exhibited stiffness losses over the same timeframe. It is believed that this is due to ion exchange with other species in culture media, as hydrogels incubated in dIH2O exhibited significantly improved stability. To maintain cell viability and function while increasing 3D matrix stability, a range of useful media:dIH2O dilution ratios for use are identified. Such findings have importance to carry out characterization and optimization of cell microphysiological systems with high fidelity in vitro.

Linguistic and cultural analysis of the written monuments of the Old Kipchak language of the Mamluk-Golden Horde period

Relevance. The study of the linguocultural foundations of the Kipchak language lays the foundation for the formation of historical, cultural, phonetic and lexico-grammatical components, which create a mechanism for the development of Turkic studies as a whole. The process of loss of clarity and sharpness of cultural contrasts and their dissipation must be adapted to save the potential of subtle differences in Kipchak speech present in the social reality of the Turks. Purpose. The purpose of the study is to analyse the features of the functioning of Turkic linguistic and cultural trends, taking into account the peculiarities of the use of Kipchak language units. Methodology. To achieve the research goals, the following methods were used: structural, content analysis, comparative. Results. The results of the work determined that the Kipchak words form the basis for the study of linguocultural and lexical components that form the cultural, phonetic and grammatical structures of the development of Turkic studies in general. Content analysis made it possible to identify various language units that describe the picture of the world of the Turks and are unique dialects of the cultural context. It was determined that the study of the phonetic and lexical and grammatical properties of the Kipchak language contributes to the active promotion of linguocultural elements that permeate the traditions, customs, and culture of the Turks. Conclusions. Consideration of the relevant phrases, expressions, and language units made it possible to see a wide linguocultural spectrum of the functioning of the Kipchak language within the framework of historical events, life, and professions of that time. The practical significance lies in the use of the results of the study by scientists, as well as specialists in the field of cultural studies, linguoculturology, linguistics and Turkology. Keywords: Kipchak language; culture; identity; dialects; linguistic picture of the world

Multiple Kernel Synthesis of Head CT Using a Task-Based Loss Function

In CT imaging of the head, multiple image series are routinely reconstructed with different kernels and slice thicknesses. Reviewing the redundant information is an inefficient process for radiologists. We address this issue with a convolutional neural network (CNN)-based technique, synthesiZed Improved Resolution and Concurrent nOise reductioN (ZIRCON), that creates a single, thin, low-noise series that combines the favorable features from smooth and sharp head kernels. ZIRCON uses a CNN model with an autoencoder U-Net architecture that accepts two input channels (smooth- and sharp-kernel CT images) and combines their salient features to produce a single CT image. Image quality requirements are built into a task-based loss function with a smooth and sharp loss terms specific to anatomical regions. The model is trained using supervised learning with paired routine-dose clinical non-contrast head CT images as training targets and simulated low-dose (25%) images as training inputs. One hundred unique de-identified clinical exams were used for training, ten for validation, and ten for testing. Visual comparisons and contrast measurements of ZIRCON revealed that thinner slices and the smooth-kernel loss function improved gray-white matter contrast. Combined with lower noise, this increased visibility of small soft-tissue features that would be otherwise impaired by partial volume averaging or noise. Line profile analysis showed that ZIRCON images largely retained sharpness compared to the sharp-kernel input images. ZIRCON combined desirable image quality properties of both smooth and sharp input kernels into a single, thin, low-noise series suitable for both brain and skull imaging.

An Efficient Latent Style Guided Transformer-CNN Framework for Face Super-Resolution

In the Face Super-Resolution (FSR) task, it is important to precisely recover facial textures while maintaining facial contours for realistic high resolution faces. Although several CNN-based FSR methods have achieved great performance, they fail in restoring the facial contours due to the limitation of local convolutions. In contrast, Transformer-based methods which use self-attention as the basic component, are expert in modeling long-range dependencies between image patches. However, learning long-range dependencies often deteriorates facial textures due to the lack of locality. Therefore, a question is naturally raised: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">how to effectively combine the superiority of CNN and Transformer for better reconstructing faces?</i> To address this issue, we propose an Efficient Latent Style guided Transformer-CNN framework for FSR called <bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ELSFace</b> , which can sufficiently integrate the advantages of CNN and Transformer. The framework consists of a Feature Preparation Stage and a Feature Carving Stage. Basic facial contours and textures are generated in the Feature Preparation Stage, and separately guided by latent styles, so that facial details are better represented in reconstruction. CNN and Transformer streams in the Feature Carving Stage are used to individually restore facial textures and facial contours, respectively in a parallel recursive way. Considering the negligence of high-frequency features when learning the long-range dependencies, we design the High-Frequency Enhancement Block (HFEB) in the Transformer stream. The Sharp Loss is also proposed for better perceptual quality in optimization. Extensive experimental results demonstrate that our ELSFace can achieve the best results among all metrics compared to the state-of-the-art CNN and Transformer-based methods on commonly used datasets and real-world tasks. Meanwhile, our ELSFace method has the least model parameters and running time. The codes are released at <uri xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">https://github.com/FVL2020/ELSFace</uri> .

Индивидуализация подходов к реабилитации детей с хроническим аденоидитом с учетом их конституциональных различий

The purpose — to reveal the features of the development, course and character of clinical manifestations of chronic adenoiditis in 4–7 y. o. children of various constitutional types. Material and methods. Children aged 4–7 years with a verified diagnosis of chronic adenoiditis were examined; they were divided into groups by constitutional types using the scale of mental activity orientation. The children with the expert assessment of mental activity orientation in the 1–3 interval were referred to the subgroup of «introverts», with 4–6 points — to the subgroup of «centroverts», and with 7–9 — to the subgroup of «extroverts». The sample of children was as follows: extroverts made up 35.9% of the total number of children, introverts — 34.1%, centroverts — 30%. The nature of clinical manifestations, development and course of chronic adenoiditis were assessed with the data from the child’s developmental history, additional parental questionnaire, and examination. Results. In introverts, the debut of chronic adenoiditis was at the age of 3–4 years, the disease duration by this age was about one and a half years, the diagnosis was made earlier than in extroverts, but with a later development of exudative otitis. In introverted children, complaints related to snoring and obstructive sleep apnea syndrome, as well as sound pronunciation disorders, came to the forefront. In extroverted children, chronic adenoiditis debuted at the age of 4–5 years, with the disease duration of about six months, with later diagnosis, but with early formation of exudative otitis. Clinical manifestations in extroverted children were associated with postnasal syndrome combined with nocturnal cough, formation of exudative otitis, frequent purulent otitis media and sharp hearing loss. Conclusion. Differences in the clinical and functional course of chronic adenoiditis in preschool children of various constitutional types should be taken into account in the organization of rehabilitation. This will improve the quality of life of these children, increase the bodily reactive capabilities and the levels of success and social adaptation in educational institutions.

THE POTENTIAL FOR ENSURING FOOD SECURITY IN UKRAINE IN THE CONTEXT OF THE ONGOING MILITARY CONFLICT

The subject of the research is the study of Ukraine's food security and the potential for improving it. Methodology. The article uses general scientific and specific methods of economic research: the method of content analysis (when processing scientific sources and reviewing the thematic literature, deduction and induction); abstract and logical method (when identifying problematic aspects of ensuring the country's food security, substantiating conclusions and proposals); the method of statistical calculations of regression economics (when substantiating the economic and mathematical model of food security, calculating the indicator of the actual state of self-sufficiency in food security). The purpose of the study is to assess the level of food security achieved by Ukraine and to identify the main factors that affect the potential for its possible improvement. Conclusion. Ukraine has significant potential to ensure food security at the national and European levels. However, over the past two years, Ukraine has lost its position in the global food security ranking according to the GFSI. The main problematic aspects that led to this are as follows: irrational use of land and labour resources, aging and migration of the rural population; sharp loss of agricultural biodiversity; high level of chemicalisation of agricultural production; loss of the potential for quality reproduction of agricultural land; significant inclusive gaps within rural areas; low level of funding for agricultural science and a predominantly raw material, agrarian orientation. The main reason for the downgrade of Ukraine's GFSI rating in 2022 was the ongoing military operations in the country. Despite the existing problematic aspects, the Ukrainian agricultural sector showed the highest level of sustainable development compared to other types of economic activity. The share of profitable enterprises in the sector was 79%. Ukraine is currently self-sufficient in food security for almost all types of agricultural products. The constructed economic-mathematical model showed a high degree of dependence of food security on such factors as the total value of assets of agricultural formations, the value of fixed assets and the amount of profit. It was determined that the key condition for increasing the potential for ensuring food security in Ukraine, both at the national and European level, should be the social responsibility of agribusiness and raising the level of sustainable development of agriculture and rural areas.

Pediatric evaluations for deep learning CT denoising.

Deep learning (DL) CT denoising models have the potential to improve image quality for lower radiation dose exams. These models are generally trained with large quantities of adult patient image data. However, CT, and increasingly DL denoising methods, are used in both adult and pediatric populations. Pediatric body habitus and size can differ significantly from adults and vary dramatically from newborns to adolescents. Ensuring that pediatric subgroups of different body sizes are not disadvantaged by DL methods requires evaluations capable of assessing performance in each subgroup. To assess DL CT denoising in pediatric and adult-sized patients, we built a framework of computer simulated image quality (IQ) control phantoms and evaluation methodology. The computer simulated IQ phantoms in the framework featured pediatric-sized versions of standard CatPhan 600 and MITA-LCD phantoms with a range of diameters matching the mean effective diameters of pediatric patients ranging from newborns to 18 years old. These phantoms were used in simulating CT images that were then inputs for a DL denoiser to evaluate performance in different sized patients. Adult CT test images were simulated using standard-sized phantoms scanned with adult scan protocols. Pediatric CT test images were simulated with pediatric-sized phantoms and adjusted pediatric protocols. The framework's evaluation methodology consisted of denoising both adult and pediatric test images then assessing changes in image quality, including noise, image sharpness, CT number accuracy, and low contrast detectability. To demonstrate the use of the framework, a REDCNN denoising model trained on adult patient images was evaluated. To validate that the DL model performance measured with the proposed pediatric IQ phantoms was representative of performance in more realistic patient anatomy, anthropomorphic pediatric XCAT phantoms of the same age range were also used to compare noise reduction performance. Using the proposed pediatric-sized IQ phantom framework, size differences between adult and pediatric-sized phantoms were observed to substantially influence the adult trained DL denoising model's performance. When applied to adult images, the DL model achieved a 60% reduction in noise standard deviation without substantial loss in sharpness in mid or high spatial frequencies. However, in smaller phantoms the denoising performance dropped due to different image noise textures resulting from the smaller field of view (FOV) between adult and pediatric protocols. In the validation study, noise reduction trends in the pediatric-sized IQ phantoms were found to be consistent with those found in anthropomorphic phantoms. We developed a framework of using pediatric-sized IQ phantoms for pediatric subgroup evaluation of DL denoising models. Using the framework, we found the performance of an adult trained DL denoiser did not generalize well in the smaller diameter phantoms corresponding to younger pediatric patient sizes. Our work suggests noise texture differences from FOV changes between adult and pediatric protocols can contribute to poor generalizability in DL denoising and that the proposed framework is an effective means to identify these performance disparities for a given model.

Review on optic atrophy

The illness known as otic atrophy damages the eye. It causes anterior ischemic optic neuropathy, also known as gloaucoma, and strokes of the optic nerve. A change in vision, notably blurred vision, problems with peripheral (side) vision, problems with colour vision, and a loss of vision sharpness, are indications of optic atrophy. The final stage of a disease process that affects the retinogeniculate section of the visual pathway is called optic atrophy, and it is identified by the non-specific symptom of optic disc pallor. As a result, rather than acting like a real peripheral nerve, the optic nerve, with its 1.2 million fibres, functions more like a white matter tract. Pial capillaries that supply the optic nerve head experience degeneration, which contributes to the pallor of the optic disc seen in optic atrophy.

Dual-core-enhanced surface plasmon resonance for sensing high refractive index liquid based on photonic crystal fiber

A dual-core photonic crystal fiber sensor based on surface plasmon resonance is theoretically proposed for the high-sensitive detection of high refractive index liquid analytes. Dual-core construction can effectively enhance the coupling effect between the fiber-core mode and the surface plasmon polariton modes, leading to sharp loss peaks at the resonance wavelengths. As the refractive index of the targeted analyte varies, the resonance condition will change as well and cause a certain shift of loss peak. Numeric results show that this dual-core fiber sensor exhibits an average linear sensitivity 9538 nm/RIU and a maximum sensitivity is 11400 nm/RIU with a resolution 8.77 × 10−6 RIU. The detected range is broad and covers the high refractive index range from 1.45 to 1.58 with an average figure of merit 284.5 RIU−1. The dependence of structure parameters and the thickness of coated-metal thin-film on sensing performance is performed systemically and suggests different responses. The proposed sensor is highly promising in detecting high refractive index liquid analytes in the fields of biological detection, environmental monitoring and chemical analysis.

Exploration of transient flow perturbations in a bulb turbine diffuser using proper orthogonal decomposition

Hydraulic turbines with high efficiency over a wide range of operating conditions offer a much sought-after flexibility to electricity producers. However, some low-head turbines exhibit sharp losses of efficiency close to their peak efficiency discharge that are linked to draft tube flow separations whose causes remain misunderstood. This paper presents the latest results obtained in the scope of the BulbT project that focused on the flow dynamics related to the efficiency drop. The main objectives are to document the transient characteristics of the flow in the hub-wake region and investigate interactions between the core flow and wall separations to identify potential mechanisms explaining the efficiency drop. Using proper orthogonal decompositions of synchronized time-resolved velocity and pressure measurements, highly energetic modes representing stochastic perturbations across BulbT's draft tube are identified. These perturbations occur only for the discharges affected by the efficiency drop, past the best efficiency point. Despite the absence of near-wall velocity measurements, the modal decompositions provide evidence that the onset of the efficiency drop is the result of two independent types of flow separation that occur on opposite sides of the draft tube. Upstream separations are found to happen simultaneously with an asymmetric acceleration of the flow in a region surrounding the turbine's axis and the tip of the runner hub and become the most important contributor to the efficiency drop at the highest measured flow rate. Furthermore, the likeliness of observing one kind of flow separation increases after it has already occurred, pointing to a strong history effect.

High-Roll-Off-Rate Ultrathin Polarization-Rotating Frequency Selective Surface

This letter introduces a transmission FSS with excellent roll-off feature, ultra-thin thickness, low insertion loss and wide rejection bands. Three novel basic component structures are developed based on the polarization rotator (PR) structure leading to multi-transmission zeros and poles which can be independently controlled. Theoretical analyses and simulations are carried out, and a prototype is fabricated and measured. The proposed FSS exhibits double sharp roll-off sidebands, ultra-thin thickness and low insertion loss, as well as two wide stopbands. In addition, the proposed FSS shows stable responses with oblique incidence up to 45 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> . As a result, the tight agreement between measurement and simulation validates the design principle.

Crystal Structure, Electronic Structure, the Density of States, Optical Properties, and Superconducting Transition Temperature of ZrBeSi Crystal under Pressure

Through a rigorous application of first‐principles simulations, it is endeavored to provide a systematic examination of how the crystal structure, electronic structure, density of states, optical properties, and superconducting transition temperature of ZrBeSi are influenced by variations in pressure. The research has shown that pressure can alter the electronic structure and density of states, with a tendency for expansion toward higher energy regions as pressure increases. By manipulating the pressure, both the absorption coefficient and energy loss are sensitive to pressure and exhibit sharp absorption and loss peaks in the UV wavelength region. In addition to the above, the effects of electron–phonon coupling are taken into account and further investigations of the superconducting transition temperature , which is found to be 0.564 K at 0 GPa, are subsequently delved into. Additionally, there exists a quadratic attenuation relationship between the temperature and pressure. Further studies reveal that the decrease of with increasing pressure is a result of the combined effects of the gradual increase in the phonon density of states’ frequency and the flattening of the density of states near the Fermi level. The findings of this study contribute to the understanding of the impact of pressure on the physical properties of materials.

NEUROIMAGING CHARACTERISTICS OF ENCEPHALOPATHY IN CHRONIC KIDNEY DISEASE

According to WHO, vascular diseases of the brain in the developed countries of the world account for 15% of the total mortality. At the same time, acute and chronic encephalopathies occupy a special place in the structure of vascular diseases. In recent years, special attention has been paid to encephalopathies developing as a result of renal pathology, since kidney diseases, namely chronic kidney disease (CKD) is a huge socio-economic problem that leads to cerebral complications, with a significant deterioration in the quality of life, a sharp loss of working capacity, and a high percentage of mortality. In the diagnosis of various encephalopathies and other disorders of cerebral circulation, an invaluable role is played by MRI, MSCT, brain angiography with their wide diagnostic capabilities.

Influence of adaptive denoising on Diffusion Kurtosis Imaging at 3T and 7T

Background and objectiveChoosing the most appropriate denoising method to improve the quality of diagnostic images maximally is key in pre-processing of diffusion MRI images. Recent advancements in acquisition and reconstruction techniques have questioned traditional noise estimation methods favoring adaptive denoising frameworks, circumventing the need to know a priori information that is hardly available in a clinical setting. In this observational study, we compared two innovative adaptive techniques sharing some features, Patch2Self and Nlsam, through application on reference adult data at 3T and 7T. The primary aim was identifying the most effective method in case of Diffusion Kurtosis Imaging (DKI) data - particularly susceptible to noise and signal fluctuations - at 3T and 7T fields. A side goal consisted of investigating the dependence of kurtosis metrics’ variability with respect to the magnetic field on the adopted denoising methodology. MethodsFor comparison purposes, we focused on qualitative and quantitative analysis of DKI data and related microstructural maps before and after applying the two denoising approaches. Specifically, we assessed computational efficiency, preservation of anatomical details via perceptual metrics, consistency of microstructure model fitting, alleviation of degeneracies in model estimation, and joint variability with varying field strength and denoising method. ResultsAccounting for all these factors, Patch2Self framework has turned out to be specifically suitable for DKI data, with improving performance at 7T. Nlsam method is more robust in alleviating degenerate black voxels while introducing some blurring, which in turn is reflected in an overall loss of image sharpness. Regarding the impact of denoising on field-dependent variability, both methods have been shown to make variations from standard to Ultra-High Field more concordant with theoretical evidence, claiming that kurtosis metrics are sensitive to susceptibility-induced background gradients, directly proportional to the magnetic field strength and sensitive to the microscopic distribution of iron and myelin. ConclusionsThis study serves as a proof-of-concept stressing the need for an accurate choice of a denoising methodology, specifically tailored for the data under analysis and allowing higher spatial resolution acquisition within clinically compatible timings, with all the potential benefits that improving suboptimal quality of diagnostic images entails.

Ultrahigh-Resolution Photon-Counting Detector CT of the Lungs: Association of Reconstruction Kernel and Slice Thickness With Image Quality.

BACKGROUND. Prior work has shown improved image quality for photon-counting detector (PCD) CT of the lungs compared with energy-integrating detector CT. A paucity of the literature has compared PCD CT of the lungs using different reconstruction parameters. OBJECTIVE. The purpose of this study is to the compare the image quality of ultra-high-resolution (UHR) PCD CT image sets of the lungs that were reconstructed using different kernels and slice thicknesses. METHODS. This retrospective study included 29 patients (17 women and 12 men; median age, 56 years) who underwent noncontrast chest CT from February 15, 2022, to March 15, 2022, by use of a commercially available PCD CT scanner. All acquisitions used UHR mode (1024 × 1024 matrix). Nine image sets were reconstructed for all combinations of three sharp kernels (BI56, BI60, and BI64) and three slice thicknesses (0.2, 0.4, and 1.0 mm). Three radiologists independently reviewed reconstructions for measures of visualization of pulmonary anatomic structures and pathologies; reader assessments were pooled. Reconstructions were compared with the clinical reference reconstruction (obtained using the BI64 kernel and a 1.0-mm slice thickness [BI641.0-mm]). RESULTS. The median difference in the number of bronchial divisions identified versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.5), BI600.4-mm (0.3), BI640.2-mm (0.5), and BI600.2-mm (0.2) (all p < .05). The median bronchial wall sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3) and BI640.2-mm (0.3) and was lower for BI561.0-mm (-0.7) and BI560.4-mm (-0.3) (all p < .05). Median pulmonary fissure sharpness versus the clinical reference reconstruction was higher for reconstructions with BI640.4-mm (0.3), BI600.4-mm (0.3), BI560.4-mm (0.5), BI640.2-mm (0.5), BI600.2-mm (0.5), and BI560.2-mm (0.3) (all p < .05). Median pulmonary vessel sharpness versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3), BI600.4-mm (-0.3), BI560.4-mm (-0.7), BI640.2-mm (-0.7), BI600.2-mm (-0.7), and BI560.2-mm (-0.7). Median lung nodule conspicuity versus the clinical reference reconstruction was lower for reconstructions with BI561.0-mm (-0.3) and BI560.4-mm (-0.3) (both p < .05). Median conspicuity of all other pathologies versus the clinical reference reconstruction was lower for reconstructions with BI561.0 mm (-0.3), BI560.4-mm (-0.3), BI640.2-mm (-0.3), BI600.2-mm (-0.3), and BI560.2-mm (-0.3). Other comparisons among reconstructions were not significant (all p > .05). CONCLUSION. Only the reconstruction using BI640.4-mm yielded improved bronchial division identification and bronchial wall and pulmonary fissure sharpness without a loss in pulmonary vessel sharpness or conspicuity of nodules or other pathologies. CLINICAL IMPACT. The findings of this study may guide protocol optimization for UHR PCD CT of the lungs.

Label-Guided Generative Adversarial Network for Realistic Image Synthesis.

Generating photo-realistic images from labels (e.g., semantic labels or sketch labels) is much more challenging than the general image-to-image translation task, mainly due to the large differences between extremely sparse labels and detail rich images. We propose a general framework Lab2Pix to tackle this issue from two aspects: 1) how to extract useful information from the input; and 2) how to efficiently bridge the gap between the labels and images. Specifically, we propose a Double-Guided Normalization (DG-Norm) to use the input label for semantically guiding activations in normalization layers, and use global features with large receptive fields for differentiating the activations within the same semantic region. To efficiently generate the images, we further propose Label Guided Spatial Co-Attention (LSCA) to encourage the learning of incremental visual information using limited model parameters while storing the well-synthesized part in lower-level features. Accordingly, Hierarchical Perceptual Discriminators with Foreground Enhancement Masks are proposed to toughly work against the generator thus encouraging realistic image generation and a sharp enhancement loss is further introduced for high-quality sharp image generation. We instantiate our Lab2Pix for the task of label-to-image in both unpaired (Lab2Pix-V1) and paired settings (Lab2Pix-V2). Extensive experiments conducted on various datasets demonstrate that our method significantly outperforms state-of-the-art methods quantitatively and qualitatively in both settings.

Remittances in Russia and Caucasus and Central Asia: The gravity model

AbstractRemittances are an important source of external financing in low‐ and middle‐income countries. This paper uses the gravity model to analyze remittance flows in Russia and Caucasus and Central Asia countries. Standard gravity determinants, such as gross domestic product in sending and receiving countries, bilateral distance, existence of common borders and common official language, and fit remittance, flow well. Remittances also react to inflation and exchange rate movements in recipient countries to sustain their purchasing power. In line with the altruism hypothesis, remittances flow to countries with higher age dependency ratio. Remittances are countercyclical and help stabilize outputs in recipient countries. However, global shocks resulting in sharp output losses of sending countries would lead to large volatility and decline in remittance inflows in recipient countries.