Free Trade and Investment in the Fisheries Sector of the Asia-Pacific Region: An Economic Analysis of Tariffs

This paper was commissioned by the APEC Working Group on Fisheries to examine the economic impact of eliminating tariffs on fish and fish products in APEC economies. Chapter II provides a qualitative assessment of the impacts of liberalization of fisheries trade drawing on the available data and economic theory. Chapter III presents specific quantitative estimates of the impact on trade flows of fish and fish products using an econometrically estimated model of fisheries trade liberalization. Chapter IV summarizes the study’s overall conclusions. These are that the economic impact of the removal of tariffs on fish and fish products in the APEC region would be significant, but modest. It is estimated that, in value terms, the long- run increase in imports in the region, arising from the elimination of tariffs, would be less than 5 per cent of the 1995 level in value. The corresponding increase in exports would be equal to slightly less than 3 per cent of the 1995 level.international trade in fish and fish products, APEC region, impact of tariffs

The Impact of State Preemption of Local Smoking Restrictions on Public Health Protections and Changes in Social Norms

Introduction. Preemption is a legislative or judicial arrangement in which a higher level of government precludes lower levels of government from exercising authority over a topic. In the area of smoke-free policy, preemption typically takes the form of a state law that prevents communities from adopting local smoking restrictions. Background. A broad consensus exists among tobacco control practitioners that preemption adversely impacts tobacco control efforts. This paper examines the effect of state provisions preempting local smoking restrictions in enclosed public places and workplaces. Methods. Multiple data sources were used to assess the impact of state preemptive laws on the proportion of indoor workers covered by smoke-free workplace policies and public support for smoke-free policies. We controlled for potential confounding variables. Results. State preemptive laws were associated with fewer local ordinances restricting smoking, a reduced level of worker protection from secondhand smoke, and reduced support for smoke-free policies among current smokers. Discussion. State preemptive laws have several effects that could impede progress in secondhand smoke protections and broader tobacco control efforts. Conclusion. Practitioners and advocates working on other public health issues should familiarize themselves with the benefits of local policy making and the potential impact of preemption

Automatically Generating CS Learning Materials with Large Language Models

Recent breakthroughs in Large Language Models (LLMs), such as GPT-3 and Codex, now enable software developers to generate code based on a natural language prompt. Within computer science education, researchers are exploring the potential for LLMs to generate code explanations and programming assignments using carefully crafted prompts. These advances may enable students to interact with code in new ways while helping instructors scale their learning materials. However, LLMs also introduce new implications for academic integrity, curriculum design, and software engineering careers. This workshop will demonstrate the capabilities of LLMs to help attendees evaluate whether and how LLMs might be integrated into their pedagogy and research. We will also engage attendees in brainstorming to consider how LLMs will impact our field.Comment: In Proceedings of the 54th ACM Technical Symposium on Computing Science Educatio

Comparing Code Explanations Created by Students and Large Language Models

Reasoning about code and explaining its purpose are fundamental skills for computer scientists. There has been extensive research in the field of computing education on the relationship between a student's ability to explain code and other skills such as writing and tracing code. In particular, the ability to describe at a high-level of abstraction how code will behave over all possible inputs correlates strongly with code writing skills. However, developing the expertise to comprehend and explain code accurately and succinctly is a challenge for many students. Existing pedagogical approaches that scaffold the ability to explain code, such as producing exemplar code explanations on demand, do not currently scale well to large classrooms. The recent emergence of powerful large language models (LLMs) may offer a solution. In this paper, we explore the potential of LLMs in generating explanations that can serve as examples to scaffold students' ability to understand and explain code. To evaluate LLM-created explanations, we compare them with explanations created by students in a large course ($n \approx 1000$) with respect to accuracy, understandability and length. We find that LLM-created explanations, which can be produced automatically on demand, are rated as being significantly easier to understand and more accurate summaries of code than student-created explanations. We discuss the significance of this finding, and suggest how such models can be incorporated into introductory programming education.Comment: 8 pages, 3 figures. To be published in Proceedings of the 2023 Conference on Innovation and Technology in Computer Science Education V.

Decoding Logic Errors: A Comparative Study on Bug Detection by Students and Large Language Models

Identifying and resolving logic errors can be one of the most frustrating challenges for novices programmers. Unlike syntax errors, for which a compiler or interpreter can issue a message, logic errors can be subtle. In certain conditions, buggy code may even exhibit correct behavior -- in other cases, the issue might be about how a problem statement has been interpreted. Such errors can be hard to spot when reading the code, and they can also at times be missed by automated tests. There is great educational potential in automatically detecting logic errors, especially when paired with suitable feedback for novices. Large language models (LLMs) have recently demonstrated surprising performance for a range of computing tasks, including generating and explaining code. These capabilities are closely linked to code syntax, which aligns with the next token prediction behavior of LLMs. On the other hand, logic errors relate to the runtime performance of code and thus may not be as well suited to analysis by LLMs. To explore this, we investigate the performance of two popular LLMs, GPT-3 and GPT-4, for detecting and providing a novice-friendly explanation of logic errors. We compare LLM performance with a large cohort of introductory computing students $(n=964)$ solving the same error detection task. Through a mixed-methods analysis of student and model responses, we observe significant improvement in logic error identification between the previous and current generation of LLMs, and find that both LLM generations significantly outperform students. We outline how such models could be integrated into computing education tools, and discuss their potential for supporting students when learning programming

Experiences from Using Code Explanations Generated by Large Language Models in a Web Software Development E-Book

Advances in natural language processing have resulted in large language models (LLMs) that are capable of generating understandable and sensible written text. Recent versions of these models, such as OpenAI Codex and GPT-3, can generate code and code explanations. However, it is unclear whether and how students might engage with such explanations. In this paper, we report on our experiences generating multiple code explanation types using LLMs and integrating them into an interactive e-book on web software development. We modified the e-book to make LLM-generated code explanations accessible through buttons next to code snippets in the materials, which allowed us to track the use of the explanations as well as to ask for feedback on their utility. Three different types of explanations were available for students for each explainable code snippet; a line-by-line explanation, a list of important concepts, and a high-level summary of the code. Our preliminary results show that all varieties of explanations were viewed by students and that the majority of students perceived the code explanations as helpful to them. However, student engagement appeared to vary by code snippet complexity, explanation type, and code snippet length. Drawing on our experiences, we discuss future directions for integrating explanations generated by LLMs into existing computer science classrooms

Free Trade and Investment in the Fisheries Sector of the Asia-Pacific Region: An Economic Analysis of Tariffs

This paper was commissioned by the APEC Working Group on Fisheries to examine the economic impact of eliminating tariffs on fish and fish products in APEC economies. Chapter II provides a qualitative assessment of the impacts of liberalization of fisheries trade drawing on the available data and economic theory. Chapter III presents specific quantitative estimates of the impact on trade flows of fish and fish products using an econometrically estimated model of fisheries trade liberalization. Chapter IV summarizes the study’s overall conclusions. These are that the economic impact of the removal of tariffs on fish and fish products in the APEC region would be significant, but modest. It is estimated that, in value terms, the long- run increase in imports in the region, arising from the elimination of tariffs, would be less than 5 per cent of the 1995 level in value. The corresponding increase in exports would be equal to slightly less than 3 per cent of the 1995 level

Free Trade and Investment in the Fisheries Sector of the Asia-Pacific Region: An Economic Analysis of Tariffs

This paper was commissioned by the APEC Working Group on Fisheries to examine the economic impact of eliminating tariffs on fish and fish products in APEC economies. Chapter II provides a qualitative assessment of the impacts of liberalization of fisheries trade drawing on the available data and economic theory. Chapter III presents specific quantitative estimates of the impact on trade flows of fish and fish products using an econometrically estimated model of fisheries trade liberalization. Chapter IV summarizes the study’s overall conclusions. These are that the economic impact of the removal of tariffs on fish and fish products in the APEC region would be significant, but modest. It is estimated that, in value terms, the long- run increase in imports in the region, arising from the elimination of tariffs, would be less than 5 per cent of the 1995 level in value. The corresponding increase in exports would be equal to slightly less than 3 per cent of the 1995 level

High-throughput testing in head and neck squamous cell carcinoma identifies agents with preferential activity in human papillomavirus-positive or negative cell lines.

Head and neck squamous cell carcinoma (HNSCC) is a common cancer diagnosis worldwide. Despite advances in treatment, HNSCC has very poor survival outcomes, emphasizing an ongoing need for development of improved therapeutic options. The distinct tumor characteristics of human papillomavirus (HPV)-positive vs. HPV-negative disease necessitate development of treatment strategies tailored to tumor HPV-status. High-throughput robotic screening of 1,433 biologically and pharmacologically relevant compounds at a single dose (4 μM) was carried out against 6 HPV-positive and 20 HPV-negative HNSCC cell lines for preliminary identification of therapeutically relevant compounds. Statistical analysis was further carried out to differentiate compounds with preferential activity against cell lines stratified by the HPV-status. These analyses yielded 57 compounds with higher activity in HPV-negative cell lines, and 34 with higher-activity in HPV-positive ones. Multi-point dose-response curves were generated for six of these compounds (Ryuvidine, MK-1775, SNS-032, Flavopiridol, AZD-7762 and ARP-101), confirming Ryuvidine to have preferential potency against HPV-negative cell lines, and MK-1775 to have preferential potency against HPV-positive cell lines. These data comprise a valuable resource for further investigation of compounds with therapeutic potential in the HNSCC

Repurposing Albendazole: new potential as a chemotherapeutic agent with preferential activity against HPV-negative head and neck squamous cell cancer.

Albendazole is an anti-helminthic drug that has been shown to exhibit anti-cancer properties, however its activity in head and neck squamous cell cancer (HNSCC) was unknown. Using a series of in vitro assays, we assessed the ability of albendazole to inhibit proliferation in 20 HNSCC cell lines across a range of albendazole doses (1 nM-10 μM). Cell lines that responded to treatment were further examined for cell death, inhibition of migration and cell cycle arrest. Thirteen of fourteen human papillomavirus-negative HNSCC cell lines responded to albendazole, with an average IC50 of 152 nM. In contrast, only 3 of 6 human papillomavirus-positive HNSCC cell lines responded. Albendazole treatment resulted in apoptosis, inhibition of cell migration, cell cycle arrest in the G2/M phase and altered tubulin distribution. Normal control cells were not measurably affected by any dose tested. This study indicates that albendazole acts to inhibit the proliferation of human papillomavirus-negative HNSCC cell lines and thus warrants further study as a potential chemotherapeutic agent for patients suffering from head and neck cancer