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Liver cancer has a high incidence rate, but primary healthcare settings often lack experienced doctors. Advances in large models and AI technologies offer potential assistance. This work aims to address limitations in liver cancer diagnosis models, such as poor understanding of medical images, insufficient consideration of liver blood vessels, and ensuring accurate medical information. We propose a specialized diagnostic assistant to improve the diagnostic capabilities of less experienced doctors. Our framework combines large and small models, using optimized small models for precise patient image perception. Specifically, a segmentation network iteratively removes ambiguous pixels for liver tumor segmentation, and a multi-scale, multi-level differential network segments liver vessels. Features from these segmentations and medical records form a patient's personalized knowledge base. For diagnosis, Chain of Thought (COT) technology designs prompts mimicking experienced doctors' thought patterns, and Retrieval-Augmented Generation (RAG) technology provides answers based on reliable domain knowledge and trusted cases. Our small model methods improve liver tumor and vessel segmentation performance, resulting in more accurate information extraction. The large model component scores over 1 point higher on a 10-point scale in evaluations by doctors compared to control methods. Our method enhances semantic perception of medical images, improves classification of ambiguous pixels, and optimizes small object perception. It considers blood vessel positions for specific treatments and improves response credibility and interpretability by mimicking experienced doctors' thought processes using reliable resources. This approach has been recognized by doctors and benefits liver cancer auxiliary diagnosis.

This study examines the extent to which students obtain postsecondary credentials in the career technical education (CTE) fields of focus they choose in high school. Using school fixed effects models, we find that focusing on a particular CTE field in high school is associated with an increased probability of enrolling and obtaining a postsecondary credential in that field. The secondary-postsecondary relationship varies across focus areas, and it is strongest in health (increase of 12.5 percentage points), which is disproportionately chosen by females. Across all fields of focus, however, most students enroll and obtain a postsecondary credential in fields that are different from what they focused on in high school.

Reading has been at the forefront of early-grade educational interventions, but addressing the educational needs of students in math early on is also critical given that early gaps in math skills widen further over the course of schooling. In this study, we examine the effects of Kentucky's Math Achievement Fund -- a unique state-level program that combines targeted interventions, peer-coaching, and close collaboration among teachers to improve math achievement in grades K-3 -- on student outcomes and the costs associated with this policy. We find significant positive effects of the program not only on math achievement, but also on test scores in reading and non-test outcomes including student attendance and disciplinary incidents. The benefits exist across racial/ethnic groups and students from different socioeconomic statuses, and they are slightly higher for racial minorities. These findings, along with the cost estimate of the program, suggest that this program could provide a cost-effective blueprint to address the educational needs of students in math in early grades.

Believe and Prepare is a teacher preparation reform implemented by the Louisiana Department of Education in collaboration with school systems and teacher preparation programs across the state. It was piloted in the 2014/15 school year and became mandatory in July 2018 for incoming teacher candidates in all 18 institutions of higher education that offer traditional teacher preparation programs. The reform focused on competency-based curricula, extended clinical experiences, and rigorous mentor teacher training. A central requirement of the reform is that teacher candidates must participate in a yearlong residency with a mentor teacher. This replaced the prior shorter-term student teaching requirement, typically six weeks. To explore the extent to which the reform is contributing to expected improvement in outcomes for early career teachers, this study examined the association between the reform and in-service teacher performance ratings, teacher retention, student test scores, teacher competency, and the likelihood of three placement outcomes (being placed in the school where the teacher completed a residency, filling a teaching position in a shortage area, and being placed in a rural school). Teachers who completed a program that had implemented Believe and Prepare were 2 percentage points more likely than teachers who completed a program that had not implemented it to stay in Louisiana for at least one year and 7 percentage points more likely to stay in the same school district for at least three years. Grade 4-8 students whose teachers completed a preparation program that had implemented Believe and Prepare during the pilot years scored 0.04 standard deviation lower on English language arts tests than students whose teachers completed a program that had not implemented it. Other teacher outcomes such as in-service performance ratings, competency as measured by Praxis II scores, school placement, and job assignment were not statistically different between teachers who completed a program that had implemented Believe and Prepare and teachers who completed other programs. [For the Study Snapshot, see ED624403. For the appendixes, see ED624404.]

The image source method (ISM) is often used to simulate room acoustics due to its ease of use and computational efficiency. The standard ISM is limited to simulations of room impulse responses between point sources and omnidirectional receivers. In this work, the ISM is extended using spherical harmonic directivity coefficients to include acoustic diffraction effects due to source and receiver transducers mounted on physical devices, which are typically encountered in practical situations. The proposed method is verified using finite element simulations of various loudspeaker and microphone configurations in a rectangular room. It is shown that the accuracy of the proposed method is related to the sizes, shapes, number, and positions of the devices inside a room. A simplified version of the proposed method, which can significantly reduce computational effort, is also presented. The proposed method and its simplified version can simulate room transfer functions more accurately than currently available image source methods and can aid the development and evaluation of speech and acoustic signal processing algorithms, including speech enhancement, acoustic scene analysis, and acoustic parameter estimation., Comment: The following article has been submitted to the Journal of the Acoustical Society of America (JASA). After it is published, it will be found at http://asa.scitation.org/journal/jas

In this descriptive study, we use longitudinal student-level administrative records from 4 cohorts of high school graduates in Kentucky to examine the extent to which students persist and attain post-secondary credentials in the CTE fields of concentration they choose in high school. To our knowledge, this is the first paper to use student-level administrative data to examine how different fields of concentration in high school CTE are related to future postsecondary outcomes. We find that concentrating in a particular CTE field in high school is associated with both continuing on with that same field in college and obtaining a postsecondary credential in that field; this relationship is especially strong in health fields and especially for women in health. The secondary-postsecondary connection is the weakest among students concentrating in occupational fields in high school, who are also the most disadvantaged socioeconomically and academically before high school. Despite the existence of secondary-postsecondary pipelines of career interests, most students enroll and obtain credentials in fields that are "different" from the field of concentration in high school. In addition, relative to students with similar pre-high-school achievement as measured by grades and test scores, we find that CTE concentration in high school is strongly associated with being more likely to enroll in a two-year college and less likely to enroll in a four-year college.

A number of school districts and states have implemented transition intervention programs designed to help high school students graduate ready for college. This study estimates the effectiveness of a transition program implemented statewide in Kentucky for high school seniors called Targeted Interventions (TI). Using 11 years of linked panel data, this study tracks the college progression of seven cohorts of students as they move from high school into college. Using a difference-in-regression discontinuity design, we estimate the program's impact on college credit attainment and transfer as well as the extent to which the program has helped reshape pathways through college. We find that the TI program significantly increased the likelihood that students would take at least 15 credits during the first term in college, a key measure that has been shown to be predictive of college completion. These early effects, however, do not translate into statistically significant impacts on the likelihood of transfers from a 2-year to a 4-year college, or the likelihood of earning enough credits to graduate from college. We discuss some possible explanations for why the TI program did not lead to observable improvements in college transfer or credit accumulation.

This study adds to the currently limited evidence base on the efficacy of interventions targeting non-college-ready high school students by examining the impact of Kentucky's Targeted Interventions (TI) program. We focus on interventions that students received under TI in the senior year of high school based on their 11th grade ACT test scores. Using difference-in-regression discontinuity and difference-in-difference designs with seven cohorts of 11th grade students, we find that, for an average per-student cost of about $600, TI significantly reduces the likelihood that students enroll in remedial course in both 2- and 4-year postsecondary institutions by 5-10 percentage points in math and 3-4 percentage points in English. These effects are similar among students who are eligible for free-or reduced-price lunch, Black and Hispanic students, students with remediation needs in multiple subjects, and students in lower-performing schools. Evidence also shows that TI increases the likelihood that students enroll in and pass college math before the end of the first year by four percentage points in 4-year universities. However, little evidence exists for TI affecting credit accumulation or persistence.

We describe the postsecondary transitions of students taking CTE courses in high school using administrative data on one cohort of high school graduates in Washington State. Conditional on observable characteristics, CTE concentrators--high school graduates who complete at least four CTE credits--are about 4 percentage points less likely to enroll in college than other high school graduates. However, CTE students are significantly more likely to enroll in and complete vocational programs, especially in certificate programs in applied STEM and public safety fields. Among students not enrolled in college, CTE students are also more likely to obtain full-time employment--and to work more intensively--within the first three years following high school graduation. Although the improvements in employment outcomes do not offset reductions in college enrollment, the higher completion rates of vocational credentials among CTE concentrators indicate some important positive outcomes for this population.

Long-time coherent integration (LTCI) is one of the most important techniques to improve radar detection performance of weak targets. However, for the targets moving with constant Cartesian velocities (CCV), the existing LTCI methods based on polynomial motion models suffer from limited integration time and coverage of target speed due to model mismatch. Here, a novel generalized Radon Fourier transform method for CCV targets is presented, based on the accurate range evolving model, which is a square root of a polynomial with terms up to the second order with target speed as the factor. The accurate model instead of approximate polynomial models used in the proposed method enables effective energy integration on characteristic invariant with feasible computational complexity. The target samplings are collected and the phase fluctuation among pulses is compensated according to the accurate range model. The high order range migration and complex Doppler frequency migration caused by the highly nonlinear signal are eliminated simultaneously. Integration results demonstrate that the proposed method can not only achieve effective coherent integration of CCV targets regardless of target speed and coherent processing interval, but also provide additional observation and resolution in speed domain.

In this paper we estimate the impacts of the "pathways" chosen by community college students--in terms of desired credentials and fields of study, as well as other choices and outcomes along the paths--on the attainment of credentials with labor market value. We focus on the extent to which there are recorded changes in students' choices over time, whether students make choices informed by their chances of success and by labor market value of credentials, and the impacts of choices on outcomes. We find that several characteristics of chosen pathways, such as field of study and desired credential as well as early "momentum," affect outcomes. Student choices of pathways are not always driven by information about later chances of success, in terms of probabilities of completing programs and attaining strong earnings. Students also change pathways quite frequently, making it harder to accumulate the credits needed in their fields. Attainment of credentials with greater market value could thus likely be improved by appropriate guidance and supports for students along the way, and perhaps by broader institutional changes as well. [Financial support for this report was provided by the Economic Self-Sufficiency Policy Research Institute (ESSPRI) at UC Irvine.]

Policies that require the use of information about student achievement to evaluate teacher performance are becoming increasingly common across the United States, but there is some question as to how or whether to use student test-based teacher evaluations when student assessments change. We bring empirical evidence to bear on this issue. Specifically, we examine how estimates of teacher value-added are influenced by assessment changes across 12 test transitions in two subjects and five states. In all of the math transitions we study, value-added measures from test change years and stable regime years are broadly similar in terms of their statistical properties and informational content. This is also true for "some" of the reading transitions; we do find, however, some cases in which an assessment change in reading meaningfully alters value-added measures. Our study directly informs contemporary policy debates about how to evaluate teachers when new assessments are introduced and provides a general analytic framework for examining employee evaluation policies in the face of changing evaluation metrics. [This paper was published in "Economics of Education Review" v62 p48-65 2018.]

In this article, we first survey the current situation of video processing on the edge for multimedia Internet-of-Things (M-IoT) systems in three typical scenarios, i.e., smart cities, satellite networks, and Internet-of-Vehicles. By summarizing a general model of the edge video processing, the importance of developing an edge computing platform is highlighted. Then, we give a method of implementing cooperative video processing on an edge computing platform based on light-weighted virtualization technologies. Performance evaluation is conducted and some insightful observations can be obtained. Moreover, we summarize challenges and opportunities of realizing effective edge video processing for M-IoT systems., Comment: 7 pages, 5 figures, one table