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This paper studies the minimum observability of probabilistic Boolean networks (PBNs), the main objective of which is to add the fewest measurements to make an unobservable PBN become observable. First of all, the algebraic form of a PBN is established with the help of semi-tensor product (STP) of matrices. By combining the algebraic forms of two identical PBNs into a parallel system, a method to search the states that need to be H-distinguishable is proposed based on the robust set reachability technique. Secondly, a necessary and sufficient condition is given to find the minimum measurements such that a given set can be H-distinguishable. Moreover, by comparing the numbers of measurements for all the feasible H-distinguishable state sets, the least measurements that make the system observable are gained. Finally, an example is given to verify the validity of the obtained results.

California voters decided to collect a 50 cent-per-pack tax on cigarette and other tobacco products and use the money to fund early childhood services under Proposition 10, California Children and Families First Act of 1998. In compliance to the legislative requirement of Result-Based Accountability (RBA) on the revenue spending, this report delineates evaluation findings from 39 programs that received over $8.8 million of the annual state investment in Kern County, the third largest county in California by land area. Following the RBA model, this report incorporates qualitative and quantitative analyses to present in-depth success stories and statistical results from extensive assessments of program effectiveness and service integration. A five-chapter structure is adopted to support dissemination of the multilevel findings in Fiscal Year 2021-2022 -- Built on description of the Commission leadership in Chapter 1, Chapter 2 contains assessment findings to address the results-based accountability across programs in Child Health, Family Functioning, and Child Development. Chapter 3 clarifies service partnership building in Systems of Care. Improvement of child wellbeing and family functioning is summarized in Chapter 4 to document the turning the curve process on important indicators of child wellbeing and parent support. The report concludes in Chapter 5 with a review of past recommendations and an introduction to new recommendations for next year. Netdraw, Quanteda in R, SAS and SPSS packages are employed to support data visualization, text analytics, and statistical computing. The report includes two appendices, 33 figures, 77 tables, and 151 reference items. [For "First 5 Kern Annual Report 2020-2021," see ED618879.]

Within the tensor singular value decomposition (T-SVD) framework, existing robust low-rank tensor completion approaches have made great achievements in various areas of science and engineering. Nevertheless, these methods involve the T-SVD based low-rank approximation, which suffers from high computational costs when dealing with large-scale tensor data. Moreover, most of them are only applicable to third-order tensors. Against these issues, in this article, two efficient low-rank tensor approximation approaches fusing randomized techniques are first devised under the order-d (d >= 3) T-SVD framework. On this basis, we then further investigate the robust high-order tensor completion (RHTC) problem, in which a double nonconvex model along with its corresponding fast optimization algorithms with convergence guarantees are developed. To the best of our knowledge, this is the first study to incorporate the randomized low-rank approximation into the RHTC problem. Empirical studies on large-scale synthetic and real tensor data illustrate that the proposed method outperforms other state-of-the-art approaches in terms of both computational efficiency and estimated precision.

The tensor data recovery task has thus attracted much research attention in recent years. Solving such an ill-posed problem generally requires to explore intrinsic prior structures underlying tensor data, and formulate them as certain forms of regularization terms for guiding a sound estimate of the restored tensor. Recent research have made significant progress by adopting two insightful tensor priors, i.e., global low-rankness (L) and local smoothness (S) across different tensor modes, which are always encoded as a sum of two separate regularization terms into the recovery models. However, unlike the primary theoretical developments on low-rank tensor recovery, these joint L+S models have no theoretical exact-recovery guarantees yet, making the methods lack reliability in real practice. To this crucial issue, in this work, we build a unique regularization term, which essentially encodes both L and S priors of a tensor simultaneously. Especially, by equipping this single regularizer into the recovery models, we can rigorously prove the exact recovery guarantees for two typical tensor recovery tasks, i.e., tensor completion (TC) and tensor robust principal component analysis (TRPCA). To the best of our knowledge, this should be the first exact-recovery results among all related L+S methods for tensor recovery. Significant recovery accuracy improvements over many other SOTA methods in several TC and TRPCA tasks with various kinds of visual tensor data are observed in extensive experiments. Typically, our method achieves a workable performance when the missing rate is extremely large, e.g., 99.5%, for the color image inpainting task, while all its peers totally fail in such challenging case.

This report is developed with dual foci: (1) justifying attainment of the grant milestones in Year 2; and (2) supporting ongoing improvement of the program performance, to evaluate the second year operation of a five-year grant, "Promoting Excellence in Graduate Education and Increasing Hispanic STEM Related Degree Completion". Well-rounded findings from quantitative and qualitative approaches are gathered in four sections: Fulfillment of Year 2 benchmark is addressed in Section I to match the original milestones in the grant proposal. Based on conceptualization of a "Rate of Progress" indicator in Year 1 report, Section II is devoted to description of student tracking across program pipelines toward degree completion. Impact stories are gathered in Section III to provide in-depth faculty assessment of profound outcomes in "teaching," "research," and "mentorship" domains. The qualitative inquiry is further expanded in Section IV to support social network analyses of faculty collaboration across academic disciplines. Triangulation of the evaluation findings consistently indicates satisfactory performance of the PPOHA grant in Academic Year 2020-2021. The report concludes with three recommendations for future improvement. [For "PPOHA Project Evaluation: Promoting Program Quality and Accessibility for STEM Graduate Degree Completion (Evaluator Report on Year 1 Operation)," see ED611787.]

For more than two decades, California has been charging a 50 cent-per-pack tax on cigarette and other tobacco products and using the money to fund early childhood services under Proposition 10, California Children and Families First Act of 1998. In response to the legislative requirement of Result-Based Accountability (RBA), this report delineates evaluation findings from 39 programs that received $9.2 million of the annual state investment in Kern County, the third largest county in California by land area. Following the RBA model, this report incorporates qualitative and quantitative analyses to present in-depth success stories and statistical results from extensive assessments of program effectiveness and service integration. A five-chapter structure is adopted to support dissemination of the multilevel findings in Fiscal Year 2020-2021. More specifically, built on description of the Commission leadership in Chapter 1, Chapter 2 contains assessment findings to address the results-based accountability across programs in Child Health, Family Functioning, and Child Development. Chapter 3 clarifies service partnership building in Systems of Care. Improvement of child wellbeing and family functioning is summarized in Chapter 4 to document the turning the curve process on important indicators of child wellbeing and parent support. Despite the extensive impact of COVID-19 on young children and their families, positive results are summarized in Chapter 5 to conclude the report with a review of past recommendations and an introduction to new recommendations for next year. Netdraw, Quanteda in R, SAS and SPSS packages are employed to support data visualization, text analytics, and statistical computing. The report includes two appendices, 35 figures, 73 tables, and 141 reference items. [For "First 5 Kern Annual Report 2019-2020," see ED610410.]

California State University, Bakersfield (CSUB) was awarded a two-year NSF grant, "ADVANCE Catalyst: Organizational Change for Gender Equity in STEM Academic Professions", that began in Fall 2022 to examine potential systemic barriers against female faculty of science, technology, engineering, and mathematics (STEM) in recruitment, retention, and promotion. In the first year, the grant team has made satisfactory progress in the preparation of an organizational self-assessment for identifying STEM faculty inequities. More specifically, the team modeled after the best practice in the instrument design and worked with the Fresno State colleague on dashboard creation. Accompanied by the external partnership building, the grant team made internal adjustments to minimize the impact of an unexpected personnel change. The report concludes with three recommendations for project improvement. The overall evaluation design is guided by a well-established model of Results-Based Accountability and conforms to the utility, feasibility, propriety, and accuracy standards of program evaluation.

Spontaneous emulsification, resulting from the assembly and accumulation of surfactants at liquid-liquid interfaces, is an interfacial instability where microdroplets are generated and diffusively spread from the interface until complete emulsification. Here, we show that an external magnetic field can modulate the assembly of paramagnetic nanoparticle surfactants (NPSs) at liquid-liquid interfaces and trigger an oversaturation in the areal density of the NPSs at the interface, as evidenced by a marked reduction in the interfacial tension, {\gamma}, and corroborated with a magnetostatic continuum theory. Despite the significant reduction in {\gamma}, the presence of the magnetic field does not cause stable interfaces to become unstable. Upon rapid removal of the field, however, an explosive ejection of a plume of microdroplets from the surface occurs, a dynamical interfacial instability which is termed explosive emulsification. This explosive event rapidly reduces the areal density of the NPSs to its pre-field level, stabilizing the interface. The ability to externally suppress or trigger the explosive emulsification and controlled generation of tens of thousands of microdroplets, uncovers an efficient energy storage and release process, that has potential applications for controlled and directed delivery of chemicals and remotely controlled soft microrobots, taking advantage of the ferromagnetic nature of the microdroplets., Comment: Main text and supporting information. See https://berkeley.box.com/s/tmfzh0c1gj2r7aoz7klbsmvmbcakm269 for supporting videos

California State University, Bakersfield (CSUB) has been implementing a Title Vb grant, "Promoting Excellence in Graduate Education and Increasing Hispanic STEM Related Degree Completion," to continue "strengthening the STEM program support" for students of Latino origin and "developing a Graduate School-Going culture" across the campus. In Year 3, the grant team has completed five tasks: (1) Assessing the quality and capacity of the faculty mentoring program; (2) Maintaining weekly management meetings to sustain program operation; (3) Hosting another annual Grad Slam to showcase student research; (4) Participating in 50 Virtual Grad Fairs to promote the graduate programs; and (5) Delivering effective workshops to strengthen student support. In addition, the grant funded a Graduate Student-Faculty Collaborative Research program and supported 12 Faculty Fellows to enhance STEM mentorship for 15 students, of which seven had Hispanic ethnicity. At the institutional level, partnerships have been established between CSUB and two universities to expand education pathways for graduate studies. Guided by the project logic model and a well-established Results-Based Accountability framework, quantitative and qualitative data have been gathered to triangulate evaluation results across different components of the grant support. The report ends with a "Conclusion" section to review the past recommendations and adduce new recommendations for project improvement.

California State University, Bakersfield (CSUB) was awarded a five-year grant, "An Equitable Pathway to In-Demand STEM Careers", that began in Fall 2021 to create and expand a streamlined pathway for Hispanic students to pursue their educational and career goals with servingness culture support. In the first year, the grant team has completed six tasks assured by the grant proposal: (1) Establishing a budget in alignment with federal and district protocols; (2) Pursuing recruitment of key personnel to lead K-12 and community college engagement in strengthening on-ramps into CSUB's STEM programs; (3) Securing campus space to maintain workflow for cross-functional teams; (4) Finalizing internal/external evaluation service agreements and data collection procedures; (5) Launching STEM Careers Council for local partnership building; and (6) Purchasing instructional equipment and supplies in STEM lab building. In addition, quantitative and qualitative data have been gathered to assess the effectiveness of a research program in Summer 2022 and guest speaker presentations in regular semesters. To track the outcome of student learning, an indicator of the "Rate of Progress" is configured to monitor the status of student achievement across milestones of the STEM program pipeline. In the conclusion section, evaluation findings are reviewed to support three recommendations for project improvement. The entire evaluation framework incorporates a "participatory," "utilization-focused," and "program theory-driven" mechanism that conforms to the "utility," "feasibility," "propriety," and "accuracy" standards of program evaluation.

California State University, Bakersfield (CSUB) was awarded a five-year grant, "Promoting Excellence in Graduate Education and Increasing Hispanic STEM Related Degree Completion", that began in Fall 2019. Despite the COVID-19 impact during the first year of grant implementation, the institution has established a co-director leadership structure to complete seven tasks committed in the grant proposal: (1) Establishing physical space for a Graduate Research Center (GRC), (2) Purchasing computers and software for the GRC, (3) Hiring the essential personnel (Project Assistant), (4) Creating mechanism for fiscal management, (5) Organizing the Advisory Committee, (6) Hosting the First Grad Fair, and (7) Facilitating 11 Graduate Student Center workshops. The evaluation outcomes, as illustrated by attainment of the seven milestones, indicate that the program expectation has been met for the first year. Additional accomplishment in formative evaluation is demonstrated by development of a "Rate of Progress" to track student performance toward degree completion. The conclusion section includes three recommendations for improving "program quality," expanding "STEM education capacity," and strengthening "graduate school-going culture" in Year 2 of the grant administration.

California ranks on top of the nation for supporting health and wellbeing of young children with statewide comprehensive programs. As part of the backbone support, voters passed Proposition 10 in 1998 to fund early childhood services with a 50 cent-per-pack tax on cigarette and other tobacco products. This report delineates evaluation findings from 39 programs that received over $10 million of state investment through Proposition 10 in Kern County, California during Fiscal Year 2019-2020. To address results-based accountability of the state funding, this report incorporates qualitative and quantitative analyses to present in-depth success stories and statistical results from extensive assessments of program effectiveness and service integration. A five-chapter structure is adopted to support dissemination of the multilevel findings. More specifically, built on description of the Commission leadership in Chapter 1, Chapter 2 contains assessment findings to address the results-based accountability across programs in Child Health, Family Functioning, and Child Development. Chapter 3 clarifies service partnership building in Systems of Care. Improvement of child wellbeing and family functioning is summarized in Chapter 4 to document the turning the curve process on 26 indicators. Chapter 5 includes the result aggregation to conclude the report with a review of past recommendations and an introduction to new recommendations for next year. Netdraw, Quanteda in R, SAS and SPSS packages are employed to support data visualization, text analytics, and statistical computing. The report includes two appendices, 33 figures, 82 tables, and 157 reference items. [For "First 5 Kern Annual Report: Fiscal Year 2018-2019," see ED602896.]