Miracle-dz/UniFAR-FTUs huggingface dataset:
Fast Sparse Aperture ISAR Autofocusing and Imaging via ADMM Based Sparse Bayesian Learning

Sparse aperture ISAR autofocusing and imaging is generally achieved by methods of compressive sensing (CS), or, sparse signal recovery, because non-uniform sampling of sparse aperture disables fast Fourier transform (FFT)–the core of traditional ISAR imaging algorithms. Note that the CS based ISAR autofocusing methods are often computationally heavy to execute, which limits their applications in real-time ISAR systems. The improvement of computational efficiency of sparse aperture ISAR autofocusing is either necessary or at least highly desirable to promote their practical usage. This paper proposes an efficient sparse aperture ISAR autofocusing algorithm. To eliminate the effect of sparse aperture, the ISAR image is reconstructed by sparse Bayesian learning (SBL), and the phase error is estimated by minimum entropy during the reconstruction of ISAR image. However, the computation of expectation in SBL involves a matrix inversion with an intolerable computational complexity of at least ${\mathcal{ O}}(L^{3})$ . Here, in the Bayesian inference of SBL, we transform the time-consuming matrix inversion into an element-wise matrix division by the alternating direction method of multipliers (ADMM). An auxiliary variable is introduced to divide the computation of posterior into three simpler subproblems, bringing computational efficiency improvement. Experimental results based on both simulated and measured data validate the effectiveness as well as high efficiency of the proposed algorithm. It is 20–30 times faster than the SBL based sparse aperture ISAR autofocusing approach.
‘I'm not just a number on a sheet, I’m a person’: Domiciliary care, self and getting older

Abstract Social care funding is reducing in spite of a growing older population. Within this context, domiciliary services are increasingly failing to deliver care that respects the individuality and heterogeneity of older people. To date, there has been limited research in the U.K. that explores, from the older person's perspective, how care practices interact with self. Using biographical‐narrative methodology, this study takes a constructionist approach to understand the individual's lived experience of care and how it interacts with sense of self. A three‐stage model of data collection was used, beginning with a narrative biographic enquiry, exploring with participants (65 yrs +, n = 17) their journeys into care and any possible relationship to personal identity. Stage 2 involved a two‐week period of diary completion, with participants recording daily reflections on their care experiences. In stage 3, a semi‐structured interview explored the diary entries, linking back to the narrative biographic enquiry to reveal ways in which specific care practices interacted with the sense of self. The findings reveal that a strong relationship between older person and formal carer, forged through familiarity, regularity and consistency, plays a significant role in promoting feelings of autonomy. Furthermore, such relationship mediates against the loss of executional autonomy that often accompanies increasing disability. Maintaining autonomy and control was a recurring theme, including in relation to home, privacy and dignity. Feelings of autonomy are also promoted when formal carers understand the unique ways in which individuals experience ageing and being in the cared‐for relationship. This paper suggests that a care approach should be based on two tenets. First, a knowledge and insight into the importance of understanding and respecting the older person's continuing development of self, and second applying this knowledge to care through a positive, stable and consistent relationship between the older person and the carer.
Sarcopenia is associated with longer hospital stay and multiorgan dysfunction in alcoholic hepatitis

Introduction: Excessive alcohol consumption has steadily risen to become the third leading cause of preventable death in the USA. One consequence of heavy alcohol use recently under considerable investigation is alcoholic hepatitis. Although many risk factors for developing alcoholic hepatitis have been documented, our aim in this study was to examine the potential association between sarcopenia and severity, mortality, 30 days readmission rate, complication, infections and length of hospital stay in alcoholic hepatitis patients. Methods: A retrospective analysis was performed at a large, academic hospital in 194 alcoholic hepatitis patients aged 18–60 who had cross-sectional computed tomography imaging and met our clinical definition of alcoholic hepatitis. The fifth percentile of the psoas muscle index was used as a cutoff for sarcopenia. Results: One hundred ninety-four patients met the criteria for alcoholic hepatitis and had cross-sectional imaging. Higher Model for End-Stage Liver disease score was found in the sarcopenia group when compared to the non-sarcopenia group (mean Model for End-Stage Liver disease 21.5 and 24.2, respectively, P = 0.03). Sarcopenia also correlated with significantly longer hospital stay; the average length of stay in the sarcopenia group was 17.2 days while the non-sarcopenia patients had an average of 12.4 days. We found higher risk of developing pneumonia, sepsis and hepatic encephalopathy in sarcopenic patients. Conclusion: Alcoholic hepatitis patients with sarcopenia have significantly worse outcomes when compared with the patients without sarcopenia, including a severe form of alcoholic hepatitis, longer hospital stays, higher risk of developing pneumonia, sepsis and hepatic encephalopathy.
A Neural Network Approach to Arbitrary Symbol Recognition on Modern Smartphones

Making a computer understand handwritten text and symbols have numerous applications ranging from reading of bank checks, mail addresses or digitalizing arbitrary note taking. Benefits include atomization of processes, efficient electronic storage, and possible augmented usage of parsed content. This report will provide an overview of how off-line handwriting recognition systems can be constructed. We will show how such systems can be split into isolated modules which can be constructed individually. Focus will be on handwritten single symbol recognition and we will present how this could be accomplished using convolutional neural networks on a modern smartphone. A symbol recognition prototype application for the Apple iOS operation system will be constructed and evaluated as a proof-of-concept. Results obtained during this project shows that it is possible to train a classifier to understand arbitrary symbols without the need to manually crafting class separating features and instead rely on deep learning for automatic structure discovery.
Reducing overreporting of voter turnout in seven European countries – results from a survey experiment

The phenomenon of overreporting presents a challenge to scholars who analyze voter turnout using surveys. There have been several attempts to reduce overreporting by introducing new ways of question wordings and a more extended list of response options. Although it is known that overreporting is sensitive to context variables, we still lack knowledge, how reducing overreporting works in different contexts. Thus, in this paper we study how the different ways of question wordings work in different contextual settings and which impact this has on comparative survey research. To do so, we conducted a survey experiment (web survey) including the usual turnout question and two new question forms in 7 European countries in December 2011. We find that (1) it is possible to Paper was presented at the AAPOR 67 General Conference, Orlando, Florida, May 2012
Electronic Module Based on Outdoor Learning for Thematic Learning of Elementary School

The aim of this study was to describe the students and teachers need for teaching material of electronic module based on outdoor learning to improve the learning outcomes on the material of our friend's environmental in elementary school students. This study used qualitative research. The research approach used a descriptive approach. This study was conducted at the elementary school of Klaten, Indonesia. The sampling technique in this study used purposive random sampling. Data collection technique used observation, interview, and document analysis. The technique of checking the validity of the data used triangulation technique. Data analysis in this study referred to qualitative analysis. Based on the result of observation, interview, and document analysis, it can be concluded that the use of teaching material was still in the form of textbooks only and still did in the classroom on the material of our friends' environmental, in which it should be focused on environmental experience in elementary school. Based on this data, it was necessary to develop an teaching material of electronic module based on outdoor learning so that learning was more meaningful tailored to the students and teacher need of an elementary school in thematic learning.
Neurobiological and Behavioral Studies of Skilled and Impaired Word Reading

Extensive behavioral research over the past several decades has examined the factors that govern the successful acquisition of reading skills and identification of the cause(s) of reading failure (Grigorenko, 2001; Pugh et al., 2000a). Research on the neurobiology of reading acquisition and development in skilled and impaired readers has benefited in recent years from rapid advances in several neuroimaging technologies (e.g., Positron Emission Tomography (PET); functional Magnetic Resonance Imaging (fMRI); Magnetoencephology (MEG)). This chapter will review behavioral studies of skilled reading and reading disability, and will describe how these functional imaging methods have been used in parallel with behavioral research to examine the role of component processes and the functional brain organization for language and reading in children and adults with and without reading disability (Papanicolaou et al., 2004).
Developing maximal neuromuscular power: Part 2 – Training considerations for improving maximal power production

125 1. Role of Strength in Maximal Power Production . 127 2. Movement Pattern Specificity . 129 2.1 Traditional Resistance Training Exercises. 129 2.2 Ballistic Exercises . 129 2.3 Plyometrics . 133 2.4 Weightlifting Exercises . 134 3. Load Specificity . 134 3.1 Heavy Loads . 135 3.2 Light Loads . 136 3.3 The ‘Optimal’ Load . 136 3.4 Combination of Loads . 137 4. Velocity Specificity . 138 4.1 Actual Movement Velocity . 138 4.2 Intention to Move Explosively. 139 4.3 Actual versus Intended Movement Velocity . 140 5. Window of Adaptation . 140 6. Integration of Power Training Modalities . 140 7. Conclusions and Implications. 141 Abstract This series of reviews focuses on the most important neuromuscular function in many sport performances: the ability to generate maximal muscular power. Part 1, published in an earlier issue of Sports Medicine, focused on the factors that affect maximal power production while part 2 explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability to generate maximal power during complex motor skills is of paramount importance to successful athletic REVIEW ARTICLE Sports Med 2011; 41 (2): 125-146 0112-1642/11/0002-0125/$49.95/0This series of reviews focuses on the most important neuromuscular function in many sport performances: the ability to generate maximal muscular power. Part 1, published in an earlier issue of Sports Medicine, focused on the factors that affect maximal power production while part 2 explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability to generate maximal power during complex motor skills is of paramount importance to successful athletic REVIEW ARTICLE Sports Med 2011; 41 (2): 125-146 0112-1642/11/0002-0125/$49.95/0 a 2011 Adis Data Information BV. All rights reserved.
Spatio-Temporal Variability of the Habitat Suitability Index for the Todarodes Pacificus (Japanese Common Squid) around South Korea

The climate-induced changes in marine fishery resources in South Korea have been a big concern over the last decades. The climate regime shift has led to not only a change in the dominant fishery resources, but also a decline in fishery landings in several species. The habitat suitability index (HSI) has been widely used to detect and forecast fishing ground formation. In this study, the catch data of the Todarodes pacificus (Japanese Common Squid) and satellite-derived environmental parameters were used to estimate the HSI for the T. pacificus around South Korea. More than 80% of the total catch was found in regions with a sea surface temperature (SST) of 14.91–27.26 ℃, sea surface height anomaly (SSHA) of 0.05–0.20 m, chlorophyll-a of 0.32–1.35 mg m-3, and primary production of 480.41–850.18 mg C m-2 d-1. Based on these results, the HSI model for T. pacificus was derived. A strong positive relationship (R2 = 0.9260) was found between the HSI and the fishery landings. The climatological monthly mean HSI from 2002 to 2016 showed several hotspots, coinciding with the spawning and feeding grounds of T. pacificus. This outcome implies that our estimated HSI can yield a reliable prediction of the fishing ground for T. pacificus around South Korea. Furthermore, the approach with the simple HSI model used in this study can be applied elsewhere, and will help us to understand the spatial and temporal distribution of fishery resources.
Secoiridoids Metabolism Response to Wounding in Common Centaury (Centaurium erythraea Rafn) Leaves

Centaurium erythraea Rafn produces and accumulates various biologically active specialized metabolites, including secoiridoid glucosides (SGs), which help plants to cope with unfavorable environmental conditions. Specialized metabolism is commonly modulated in a way to increase the level of protective metabolites, such as SGs. Here, we report the molecular background of the wounding-induced changes in SGs metabolism for the first time. The mechanical wounding of leaves leads to a coordinated up-regulation of SGs biosynthetic genes and corresponding JA-related transcription factors (TFs) after 24 h, which results in the increase of metabolic flux through the biosynthetic pathway and, finally, leads to the elevated accumulation of SGs 96 h upon injury. The most pronounced increase in relative expression was detected for secologanin synthase (CeSLS), highlighting this enzyme as an important point for the regulation of biosynthetic flux through the SG pathway. A similar expression pattern was observed for CeBIS1, imposing itself as the TF that is prominently involved in wound-induced regulation of SGs biosynthesis genes. The high degree of positive correlations between and among the biosynthetic genes and targeted TFs expressions indicate the transcriptional regulation of SGs biosynthesis in response to wounding with a significant role of CeBIS1, which is a known component of the jasmonic acid (JA) signaling pathway.
International SDFs in Segmented Markets∗

We characterize international stochastic discount factors (SDFs) under various degrees of market segmentation in a preference-free approach. Our methodology minimizes SDF dispersion subject to international pricing constraints and allows for a factorization into permanent and transitory components. We find that large permanent SDF components are necessary to jointly reconcile well-known exchange rate puzzles, including the low exchange rate volatility, the exchange rate cyclicality and deviations from uncovered interest rate parity. At the same time, segmented stock markets are needed to avoid implausibly large SDF dispersions. These findings demonstrate a trade-off between financial market segmentation, SDF variability and the amount of tradeable exchange rate risk when addressing international asset pricing puzzles.
THERMAL AND DYNAMIC MECHANICAL PROPERTIES OF A POLYPROPYLENE RANDOM COPOLYMER

of a polypropylene (PP) random copolymer with low ethylene content were studied. In order to study the effect of cooling rate on melting, two different cooling rates were applied to the samples. While water-cooled samples revealed a broad single melting endotherm with α-crystalline structure, slow-cooled samples showed a shoulder at lower temperature followed by a sharp melting endotherm and a mixture of α and γ-crystalline phases. The effect of annealing on log E” of the β-relaxation for the PP copolymer showed that the β-transition increased in intensity with increasing annealing temperature. No considerable difference was found in the activation enthalpy of relaxation, ∆H, values for the annealed compared to that of the water-cooled samples using the Arrhenius equation. The isothermal crystallization kinetics was also studied for PP and the values of nucleation constant, Kg, and end-surface free energy of the crystal growth, σe, were calculated using Lauritzen-Hoffman theory. Mohammad Razavi-Nouri
Noise Absorption Modeling of Rib Knitted Fabrics

In recent years, textile goods have come to be widely used as soundproofing, because of their two important advantages, low production costs and light density, in relation to other soundproofing materials. These intrinsic parameters are very important in some industries such as the automobile and aircraft industry. Although, previously, nonwovens had a wide application as soundproofing among textiles, it seems that weft knitted fabrics can also be a suitable substitute due to their pleasant appearance in comparison to nonwoven fabrics. In this paper, by incorporating two theoretical models presented for nonwoven and plain knitted fabrics, a suitable theoretical model is obtained for calculating the sound absorption coefficient of weft knitted fabrics with complex structures and, finally, the results of a theoretical model are compared with experimental results.
Prediction of the vortex yarn tenacity from some process and nozzle parameters based on numerical simulation and artificial neural network

In this study, two methods, the numerical simulation and the artificial neural network, are adopted to predict the vortex yarn tenacity from some process and nozzle parameters. The fiber-airflow interaction and the motional characteristics of the fiber inside the vortex spinning nozzle are analyzed through the numerical simulation method to predict the yarn tenacity from the parameters of the jet orifice diameter and the yarn delivery speed. The back-propagation multilayer perceptron (MLP) neural network is adopted to predict the tenacity of vortex yarn spun from modal fibers. The following parameters are used as inputs: nozzle pressure, jet orifice angle, distance between the guiding needle and the spindle, and spindle cone angle. The predicted and measured tenacities show low relative errors and a high correlation coefficient, indicating the artificial neural network method provides accurate prediction results. In addition, the effects of these parameters on the yarn tenacity are also analyzed.
A preliminary study of care coordination services within a specialized outpatient setting for youth with autism spectrum disorder

Introduction Parents of children with autism spectrum disorder often experience high levels of stress and challenges when organizing medical and behavioral services for their child. Care coordination could alleviate these challenges, however little is known about the effectiveness of this service. This study examined the need, feasibility, and acceptability of a care coordination program. Methods Families of 176 children with autism, seen at a multidisciplinary autism clinic in the United States, participated in a prospective observational study. Families received a three-month structured care coordination program and completed pre- and post-program questionnaires that probed parents’ beliefs about the need and acceptability of the program through structured and open-ended questions. Results Most (≥90%) parents reported both a need for care coordination and satisfaction with the program. Qualitative themes identified valuable aspects and ways to improve the program. Discussion Parents raising a child with autism spectrum disorder experience an unmet need for care coordination. When provided, parents’ demonstrated high uptake of service and high levels of satisfaction with the program.
Immune checkpoint inhibitor therapy and outcomes from SARS-CoV-2 infection in patients with cancer: a joint analysis of OnCovid and ESMO-CoCARE registries

Background As management and prevention strategies against COVID-19 evolve, it is still uncertain whether prior exposure to immune checkpoint inhibitors (ICIs) affects COVID-19 severity in patients with cancer. Methods In a joint analysis of ICI recipients from OnCovid (NCT04393974) and European Society for Medical Oncology (ESMO) CoCARE registries, we assessed severity and mortality from SARS-CoV-2 in vaccinated and unvaccinated patients with cancer and explored whether prior immune-related adverse events (irAEs) influenced outcome from COVID-19. Findings The study population consisted of 240 patients diagnosed with COVID-19 between January 2020 and February 2022 exposed to ICI within 3 months prior to COVID-19 diagnosis, with a 30-day case fatality rate (CFR30) of 23.6% (95% CI 17.8 to 30.7%). Overall, 42 (17.5%) were fully vaccinated prior to COVID-19 and experienced decreased CFR30 (4.8% vs 28.1%, p=0.0009), hospitalization rate (27.5% vs 63.2%, p<0.0001), requirement of oxygen therapy (15.8% vs 41.5%, p=0.0030), COVID-19 complication rate (11.9% vs 34.6%, p=0.0040), with a reduced need for COVID-19-specific therapy (26.3% vs 57.9%, p=0.0004) compared with unvaccinated patients. Inverse probability of treatment weighting (IPTW)-fitted multivariable analysis, following a clustered-robust correction for the data source (OnCovid vs ESMO CoCARE), confirmed that vaccinated patients experienced a decreased risk of death at 30 days (adjusted OR, aOR 0.08, 95% CI 0.01 to 0.69). Overall, 38 patients (15.8%) experienced at least one irAE of any grade at any time prior to COVID-19, at a median time of 3.2 months (range 0.13–48.7) from COVID-19 diagnosis. IrAEs occurred independently of baseline characteristics except for primary tumor (p=0.0373) and were associated with a significantly decreased CFR30 (10.8% vs 26.0%, p=0.0462) additionally confirmed by the IPTW-fitted multivariable analysis (aOR 0.47, 95% CI 0.33 to 0.67). Patients who experienced irAEs also presented a higher median absolute lymphocyte count at COVID-19 (1.4 vs 0.8 109 cells/L, p=0.0098). Conclusion Anti-SARS-CoV-2 vaccination reduces morbidity and mortality from COVID-19 in ICI recipients. History of irAEs might identify patients with pre-existing protection from COVID-19, warranting further investigation of adaptive immune determinants of protection from SARS-CoV-2.
A New Type Butterfly-Shaped Transducer Linear Ultrasonic Motor

This article presents a new type butterfly-shaped transducer linear ultrasonic motor, which utilizes symmetrical modal and anti-symmetric modal of a composite piezoelectric transducer. First, the drive principle of the motor and the formation of the elliptical trajectory of particles on the surface of the driving feet are analyzed. The use of the symmetric modal and anti-symmetric modal of the transducer (stator) realizes the function of driving the slider pressed on the driving feet twice in one cycle. Second, two key problems combined with the design processes of the motor are discussed: frequency consistency adjustment and mounting of the stator to ensure both the high stiffness in the driving direction and elasticity in the direction along which the slider is pressed against the stator. Finally, experimental investigation of the characteristics of the motor is presented. The maximum no-load speed is 870 mm/s, the maximum thrust is 24 N, and the maximum efficiency is 44%.