Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Resolution Limits and the Complexified

Array resolution limits and accuracy bounds on the multitude of signal parameters (e.g., azimuth, elevation, Doppler, range, cross-range, depth, frequency, chirp, polarization, ampli- tude, phase, etc.) estimated by array processing algorithms are es- sential tools in the evaluation of system performance. The case in which the complex amplitudes of the signals are unknown is of particular practical interest. A computationally efficient formula- tion of these bounds (from the perspective of derivations and anal- ysis) is presented for the case of deterministic and unknown signal amplitudes. A new derivation is given using the unknown com- plex signal parameters and their complex conjugates. The new for- mula is readily applicable to obtaining either symbolic or numer- ical solutions to estimation bounds for a very wide class of prob- lems encountered in adaptive sensor array processing. This for- mula is shown to yield several of the standard Cramer-Rao results for array processing, along with new results of fundamental in- terest. Specifically, a new closed-form expression for the statistical resolution limit of an aperture for any asymptotically unbiased su- perresolution algorithm (e.g., MUSIC, ESPRIT) is provided. The statistical resolution limit is defined as the source separation that equals its own Cramer-Rao bound, providing an algorithm-inde- pendent bound on the resolution of any high-resolution method. It is shown that the statistical resolution limit of an array or co- herent integration window is about SNR relative to the Fourier resolution limit of radians (large number of array elements). That is, the highest achievable resolution is pro- portional to the reciprocal of the fourth root of the signal-to-noise ratio (SNR), in contrast to the square-root SNR dependence of standard accuracy bounds. These theoretical results are con- sistent with previously published bounds for specific superresolu- tion algorithms derived by other methods. It is also shown that the potential resolution improvement obtained by separating two collinear arrays (synthetic ultra-wideband), each with a fixed aper- ture wavelengths by wavelengths (assumed large), is approx- imately , in contrast to the resolution improvement of for a full aperture. Exact closed-form results for these prob- lems with their asymptotic approximations are presented.
Implementation of a realistic mathematics learning approach (PMR) and analytical thinking: The impact on students' understanding of mathematical concepts in Indonesia

Understanding of concepts is a fundamental ability to learn mathematics in a more meaningful way. Understanding concepts is one of the goals to be achieved in learning mathematics. This study aims to determine the impact of a realistic mathematics learning approach (PMR) and analytical thinking on students' understanding of mathematical concepts. This experimental research uses a posttest-only control design. The population in this study included students XI in Kasui sub-district, Way Kanan district, Lampung, Determination of the sample using cluster random sampling technique. The research sample was 72 students (36 in the experimental class and 36 in the control class). Hypothesis testing using ancova test. Based on the research results, it can be concluded that the realistic mathematics learning approach (PMR) has an influence on students' understanding of mathematical concepts by controlling analytical thinking, analytical thinking has an influence on students' understanding of mathematical concepts, and there is a simultaneous influence between the PMR approach and analytical thinking on understanding mathematical concepts student.
A Galerkin Solution for Burgers' Equation Using Cubic B-Spline Finite Elements

Numerical solutions for Burgers’ equation based on the Galerkins’ method using cubic B-splines as both weight and interpolation functions are set up. It is shown that this method is capable of solving Burgers’ equation accurately for values of viscosity ranging from very small to large. Three standard problems are used to validate the proposed algorithm. A linear stability analysis shows that a numerical scheme based on a Cranck-Nicolson approximation in time is unconditionally stable.
Flow Structure on Nonslender Delta Wing: Reynolds Number Dependence and Flow Control

The flow structure over a 35 deg swept delta wing is characterized in a low-speed wind tunnel using techniques of laser-illuminated smoke visualization, laser Doppler anemometry, and surface-pressure measurements. The effects of Reynolds numbers and attack angles on the evaluation of flow patterns are addressed within the broad range of Reynolds number 104<Re<105 and attack angle 3 deg<α<10 deg. In addition, the effect of steady blowing through the leading edges of the wing on flow structure is studied to delay three-dimensional surface separation. A comparison of two different blowing patterns, uniform blowing and decreasing blowing, is used to identify the effective regions on leading edges considering the ultimate influence of flow control. The results indicate that the effect of Reynolds number on flow structure is limited, such that beyond a certain Reynolds number, the flow structure demonstrates minimal variations with further increase in Reynolds number. Considering the results of the flow-contr.
Facilitators and Barriers to HPV Self-Sampling as a Cervical Cancer Screening Option among Women Living with HIV in Rural Uganda

Abstract Background: There is a paucity of studies exploring women living with HIV’s (WLWH) experiences relating to human papillomavirus (HPV) self-sampling as cervical cancer (CC) screening approach, either at the clinic or at the home setting, using qualitative methods. Our study explored facilitators and barriers to HPV self-sampling as a CC screening approach among human immunodeficiency virus (HIV)-infected women, as supported by the new WHO guidelines of using the HPV test as a screening modality. Methods: The study was guided by the health promotion model (HPM), which helps individuals achieve higher levels of well-being. The phenomenology design was used to explore the deeper facilitators and barriers of women regarding self-sampling, either at home or in clinical settings, at Luweero District Hospital, Uganda. The in-depth interview (IDI) guide was translated from English to Luganda. Qualitative data analysis was guided by content analysis techniques. The transcripts were coded in NVivo 20.7. 0. The coded text was used to generate categories of analytically meaningful data that guided the formation of themes, the interpretation of results, and the final write-up. Results: WLWH were motivated to screen for HPV using the clinic-based approach because of perceived early diagnosis and treatment, visualization of the cervix, and free service, while reduced distance, privacy and the smooth sample collection kit were motivators for the home-based approach. A barrier that cut across the two HPV self-sampling approaches was a lack of knowledge about HPV. The barriers to clinic-based HPV self-sampling screening included lack of privacy, perceived painful procedures for visual inception under acetic acid (VIA), and fear of finding the disease. Stigma and discrimination were reported as the major barriers to the home-based HPV self-sampling approach. The major reasons why some WLWH refused to screen were fear of finding the disease, stress, and financial disruptions related to being diagnosed with CC disease. Conclusions: Therefore, early diagnosis for HPV and CC enhances clinic-based HPV self-sampling, while privacy enhances the home-based HPV self-sampling approach. However, fear of finding a disease and the lack of knowledge of HPV and CC hinders HPV self-sampling. Finally, designing pre- and post-testing counselling programs in HIV care is likely to increase the demand for HPV self-sampling.
Satellite quantification of methane emissions and oil–gas methane intensities from individual countries in the Middle East and North Africa: implications for climate action

Abstract. We use 2019 TROPOMI satellite observations of atmospheric methane in an analytical inversion to quantify methane emissions from the Middle East and North Africa at up to ∼25 km × 25 km resolution, using spatially allocated national United Nations Framework Convention on Climate Change (UNFCCC) reports as prior estimates for the fuel sector. Our resulting best estimate of anthropogenic emissions for the region is 35 % higher than the prior bottom-up inventories (+103 % for gas, +53 % for waste, +49 % for livestock, −14 % for oil) with large variability across countries. Oil and gas account for 38 % of total anthropogenic emissions in the region. TROPOMI observations can effectively optimize and separate national emissions by sector for most of the 23 countries in the region, with 6 countries accounting for most of total anthropogenic emissions including Iran (5.3 (5.0–5.5) Tg a−1; best estimate and uncertainty range), Turkmenistan (4.4 (2.8–5.1) Tg a−1), Saudi Arabia (4.3 (2.4–6.0) Tg a−1), Algeria (3.5 (2.4–4.4) Tg a−1), Egypt (3.4 (2.5–4.0) Tg a−1), and Turkey (3.0 (2.0–4.1) Tg a−1). Most oil–gas emissions are from the production (upstream) subsector, but Iran, Turkmenistan, and Saudi Arabia have large gas emissions from transmission and distribution subsectors. We identify a high number of annual oil–gas emission hotspots in Turkmenistan, Algeria, and Oman and offshore in the Persian Gulf. We show that oil–gas methane emissions for individual countries are not related to production, invalidating a basic premise in the construction of activity-based bottom-up inventories. Instead, local infrastructure and management practices appear to be key drivers of oil–gas emissions, emphasizing the need for including top-down information from atmospheric observations in the construction of oil–gas emission inventories. We examined the methane intensity, defined as the upstream oil–gas emission per unit of methane gas produced, as a measure of the potential for decreasing emissions from the oil–gas sector and using as reference the 0.2 % target set by the industry. We find that the methane intensity in most countries is considerably higher than this target, reflecting leaky infrastructure combined with deliberate venting or incomplete flaring of gas. However, we also find that Kuwait, Saudi Arabia, and Qatar meet the industry target and thus show that the target is achievable through the capture of associated gas, modern infrastructure, and the concentration of operations. Decreasing methane intensities across the Middle East and North Africa to 0.2 % would achieve a 90 % decrease in oil–gas upstream emissions and a 26 % decrease in total anthropogenic methane emissions in the region, making a significant contribution toward the Global Methane Pledge.
Wellness Counseling to Improve the Psychological Well-Being

The changes in the learning system during the COVID-19 pandemic in Indonesia affected the psychological well-being of students. The purpose of this study was to examine the effectiveness of the wellness group counseling to improve students’ psychological well-being at the Madrasah Tsanawiyah in Cianjur, West Java, Indonesia. Psychological well-being in this research is defined as the functioning of individual psychological aspects as indicated by self-acceptance, positive relations with others, autonomy, environmental mastery, purpose in life and personal growth. This research uses quantitative approach. It adopted quasi-experimental pre-test post-test control group design and the instrument was adapted from Ryff and Singer (1996). The population of the research is the 8th grade students of Madrasah Tsanawiyah Assa’idiyyah Cianjur Class of 2021/2022 academic year and 14 students as samples with purposive sampling. The research result showed that the wellness group counseling has a significant influence to improve the psychological well-being of the students.
ATTITUDES OF GREEK GENERAL EDUCATION TEACHERS CONCERNING INCLUSION POLICY

The school community consists of an environment where every child has the right to participate and share the good of the educational process. In that thinking, students dispose of different needs that have to be satisfied in a context where the values of respect and equality emerge as basic foundations of the instructive environment. Consequently, inclusion practices appear to be as the prerequisite of education for all in the general school surroundings. Teachers who are responsible for planning and applying the educational process play an important role in the implementation of inclusive practices. Especially, these educational methods are influenced by educators’ attitudes and determine the extent and the level of inclusion strategies. In the present study, participated 154 teachers of primary and secondary general education in Greece. The participants completed the Multidimensional Attitudes towards Inclusive Education Scale (MATIES) (Mahat, 2008). In general, according to the results, teachers expressed positive attitudes toward inclusion. Correlations were calculated in relation to other variables that affect teachers’ attitudes according to the research. The results emerged as directions of providing support services in the school community and organizing suitable education programs for in-service teachers in the school and academic domain. Article visualizations:
Comparison of dynamical cores for NWP models

We present a range of numerical tests comparing the dynamical cores of the operationally used numerical weather prediction (NWP) model COSMO and the university code Dune, focusing on their efficiency and accuracy for solving benchmark test cases for NWP. The dynamical core of COSMO is based on a finite difference method whereas the Dune core is based on a Discontinuous Galerkin method. Both dynamical cores are briefly introduced stating possible advantages and pitfalls of the different approaches. Their efficiency and effectiveness is investigated, based on three numerical test cases, which require solving the compressible viscous and non-viscous Euler equations. The test cases include the density current (Straka et al. in Int J Numer Methods Fluids 17:1–22, 1993), the inertia gravity (Skamarock and Klemp in Mon Weather Rev 122:2623–2630, 1994), and the linear hydrostatic mountain waves of (Bonaventura in J Comput Phys 158:186–213, 2000).
‘So basically I have to speak less and give students some freedom’: how committing to a value influences a teacher’s enactment of an inquiry-based science unit

ABSTRACT Teachers’ practices and interactions with curriculum materials are influenced by a host of factors, which include their values. The mechanisms of this influence may benefit from elucidation. Here, we describe a case of a teacher enacting an inquiry-based learning unit (LU) as part of a school science enrichment programme. The teacher’s interactions with the LU appear to be influenced by her self-stated idea of giving students ‘freedom’. We track these influences through the course of the teacher’s planning, enactment, and reflection of the LU. Because of how ‘freedom’ guides her actions, we argue that it serves the function of a value. Furthermore, we contend that the teacher’s commitment to ‘freedom’ represents an exercise of her deliberative agency. This commitment to ‘freedom’ is supported by her interactions with her context, which include labelling of her preliminary ideas with the term ‘freedom’, being asked to choose between curriculum materials, reflective conversations with the researcher, and reframing the site of enactment. We also describe challenges that the teacher faces with respect to student guidance, resulting from her commitment to ‘freedom’. From this work, we suggest implications for the design of curriculum materials and teacher professional development.
CAR T Cell Therapy: Evolutions and Emergent Improvements

One of the latest developments in the field of anti-cancer immunotherapy is chimeric antigen receptor (CAR) T cell therapy, which is considered magnificent and impressive owing to its superior response rates and efficacy. It has been proven to exhibit great efficacy in curing patients with B cell lymphoma and leukemia, and sometimes multiple myeloma as well. Nevertheless, despite the significant outcomes it has displayed, several limitations and restrictions still deeply restrain CAR T cell therapy from being widely used throughout the world. Particular challenges associated with T cells range from severe cytokine-related toxicities, the on-target off-tumor effect, and antigen escape, to inferior CAR T cell trafficking and immunosuppressive tumor microenvironment. To address the related problems, investigators learn from the evolutions of CAR design and incessantly attempt to modify and ameliorate CAR constructs and launch it to the wider extent of solid tumors and malignancies. A large array of methods and strategies have been adopted by investigators to fulfill this goal, ameliorating the efficacy, security, and applicability of CAR constructs. In this review, we will concentrate on the evolutions of CAR designs, and several limitations CAR T cell therapy recently faces, along with some innovative strategies come up by researchers to tackle them and explore the clinical benefits of this therapy against various cancers.
Physics of drift Alfvén instabilities and energetic particles in fusion plasmas

Shear Alfvén wave (SAW)/drift Alfvén wave (DAW) fluctuations can be destabilized by energetic particles (EPs) as well as thermal plasma components, which play a key role in the EP energy and momentum transport processes in burning fusion plasmas. The drift Alfvén energetic particle stability (DAEPS) code, which is an eigenvalue code using the finite element method, was developed to analyze Alfvén instabilities excited by EPs. The model equations, consisting of the quasineutrality condition and the Schrödinger-like form of the vorticity equation, are derived within the general fishbone-like dispersion relation theoretical framework, which is widely used to analyze SAW/DAW physics. The mode structure decomposition approach and asymptotic matching between the inertial/singular layer and ideal regions are adopted. Therefore, the DAEPS code can provide not only frequency and growth/damping rate but also the parallel mode structure as well as the asymptotic behavior corresponding to the singular-layer contribution. Thus, it fully describes fluid and kinetic continuous spectra as well as unstable and damped modes. The model equations have been extended to include general axisymmetric geometry and to solve for the response of circulating and trapped particles by means of the action-angle approach. In this work, we discuss linear dispersion relation and parallel mode structure of drift Alfvén instabilities excited by EPs, computed with the DAEPS code with realistic experimental plasma profile and magnetic configuration. We compare DAEPS results with FALCON/LIGKA to provide a verification of the code. We then adopt the Dyson–Schrödinger model (DSM) to further analyze the EP energy and momentum flux. We will briefly discuss how the parallel mode structure of the drift Alfvén instabilities can be used in the DSM to calculate the nonlinear radial envelope evolution and the EP transport.
Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study

Simple Summary Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. However, there are no reliable tools available for achieving this goal. Data-driven deep-learning techniques have been widely used in disease diagnosis, prognosis assessment, and treatment response prediction by identifying subtle patterns in digitized histopathological images. In this study, we developed a weakly-supervised model based on multiple instance learning and attention mechanism for predicting LNM status in MIBC patients, demonstrating decent performance in three independent cohorts. The visualization technique revealed that the stroma surrounding the tumor with lymphocytic inflammation seemed to be the critical feature for predicting LNM. This deep learning-based study provides a non-invasive and low-cost preoperative prediction tool for identifying MIBC patients with a high risk of LNM. Abstract Background: Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC. Methods: We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets. Results: In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771–0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661–0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827–0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725–0.801) and 0.746 (95% CI, 0.687–0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence. Conclusions: Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.
Progressive Failure in a Model Heterogeneous Medium

The difficulties of testing brittle heterogeneous materials are considered in the context of obtaining representative data to complement theoretical studies. It is suggested that many of these difficulties can be avoided by using a model material which can be specified numerically and examined by computation. A model of this sort is described, consisting of a plane pin-jointed random network structure of linear elastic brittle members having a range of different strengths and stiffnesses. Results of calculations simulating uniaxial extension tests are given. These show that the model material softens under increasing strain in much the same way as a range of physical materials including rock, concrete, and nonwoven fabrics. The model is used to demonstrate the effect of changes in heterogeneity on the form of the stress-strain curve, the existence of size effects and the possibility of localized failure. Results support the view that the model will be useful in a further investigation of behavior under more general deformation conditions.
Radii of Starlikeness and Convexity for Analytic Functions with Fixed Second Coefficient Satisfying Certain Coefficient Inequalities

For functions f(z) = z + a2z 2 + a3z 3 + ¢¢¢ with ja2j = 2b, b ‚ 0, sharp radii of starlikeness of order fi (0 • fi 0). Radii constants in other instances are also obtained.