The brain and its time: intrinsic neural timescales are key for input processing

We process and integrate multiple timescales into one meaningful whole. Recent evidence suggests that the brain displays a complex multiscale temporal organization. Different regions exhibit different timescales as described by the concept of intrinsic neural timescales (INT); however, their function and neural mechanisms remains unclear. We review recent literature on INT and propose that they are key for input processing. Specifically, they are shared across different species, i.e., input sharing. This suggests a role of INT in encoding inputs through matching the inputs’ stochastics with the ongoing temporal statistics of the brain’s neural activity, i.e., input encoding. Following simulation and empirical data, we point out input integration versus segregation and input sampling as key temporal mechanisms of input processing. This deeply grounds the brain within its environmental and evolutionary context. It carries major implications in understanding mental features and psychiatric disorders, as well as going beyond the brain in integrating timescales into artificial intelligence.

ASSESSMENT RUBRIC FOR RESEARCH REPORT WRITING: A TOOL FOR SUPERVISION

Purpose – Assessment rubric often lacks rigor and is underutilized. This article reports the effectiveness of the use of several assessment rubrics for a research writing course. Specifically, we examined students’ perceived changes and observed changes in their Chapter 1 thesis writing as assessed by supervisors using an existing departmental rubric and a new task-specific rubric. Methodology – Using action research methodology, two of the authors played active roles as the course supervisors, i.e., the practitioners. Two final year undergraduate students from a communication department (one from each supervisor) participated by writing three drafts of the first chapter of their research: (1) without a rubric, (2) with an existing departmental rubric, and (3) with a revised rubric. We collected artefacts of students’ writing drafts; students’ interviews; and supervisors’ reflections over the course of four months. We employed content analysis to evaluate students’ writing, while thematic analysis to analyze the students’ semi-structured interview and supervisors’ reflections. Findings – The findings suggest substantial improvements between the three drafts of students’ writing. Each student-supervisor pair acknowledged the improvements in the student’s writing after the introduction of the departmental rubric. With the newly revised rubric, they noted additional and more specific improvements especially in the scope of literature searches, problem statements, formulation of research questions, and operational definitions of variables; more generally, they also indicated improvements in the clarity of writing by using examples and providing relevant explanations tailored to the research topics. Significance – With effective scaffolding in supervision, students will regulate their learning and assess the quality of their own research report writing. We demonstrated the importance and benefits of a properly designed and validated rubric tailored to the program and course objectives to help students improve their writing drafts. Collective collaboration and input-sharing from faculty and instructors in developing and improving a rubric specific to the course and program objectives will produce quality assignments, provide constructive learning experiences for students, and achieve better grading for the program and department.

Research on operating efficiency of incubators based on DEA: A case study of China’s yangtze river economic belt

Data envelopment analysis (DEA) was used to measure the comprehensive efficiency, pure technical efficiency and scale efficiency of science and technology business incubators in 11 provinces and cities of the Yangtze River economic belt from 2011 to 2017, and the situation of incubators in the Yangtze River economic belt was analyzed from the overall, horizontal and vertical perspectives. Results show that the overall operation efficiency of science and technology business incubators in the Yangtze River economic belt is relatively high, but it shows a downward trend in the sample period, and it is found that the development of science and technology business incubators in the Yangtze River economic belt is unbalanced, there are regional differences, and some provinces and cities have serious redundancy of incubator personnel and incubation funds. On this basis, some suggestions are put forward, such as reducing the number of managers and tutors, adjusting the dominant position of government investment in science and technology business incubators, and creating resource input sharing enterprise output circulation chain.

Tales of the city: what do agglomeration cases tell us about agglomeration in general?

This article considers the heterogeneous microfoundations of agglomeration economies. It studies the co-location of industries to look for evidence of labour pooling, input sharing and knowledge spillovers. The novel contribution of the article is that it estimates single-industry models using a common empirical framework that exploits the cross-sectional variation in how one industry co-locates with the other industries in the economy. This unified approach yields evidence on the relative importance of the Marshallian microfoundations at the single-industry level, allowing for like-for-like cross-industry comparisons on the determinants of agglomeration. Using UK data, we estimate such microfoundation models for 97 manufacturing sectors, including the classic agglomeration cases of automobiles, computers, cutlery and textiles. These four cases—as with all of the individual industry models we estimate—clearly show the importance of the Marshallian forces. However, they also highlight how the importance of these forces varies across industries—implying that extrapolation from cases should be viewed with caution. The article concludes with an investigation of the pattern of heterogeneity. The degree of an industry’s clustering (localisation), entrepreneurship, incumbent firm size and worker education are shown to contribute to the pattern of heterogeneous microfoundations.

Agglomeration and Urban Manufacture Labor Productivity in Indonesia

Agglomeration, the spatial concentration of industries in a specific location, has been argued to improve productivity since it could provide positive externalities such as knowledge spillover, input sharing, and labor pooling. This paper examines the effect of large and medium manufacturing industry (LMI) agglomeration on labor productivity. Measuring the output and labor density as agglomeration effect by using 2009-2014 panel data from 44 cities and regions across the metropolitan areas of Indonesia, this study shows that in terms of output share, agglomeration positively contributes to labor productivity. On the other hand, in terms of labor density, agglomeration results in a negative impact on productivity. These findings suggest the government should expand industrial clusters in less densely populated areas, especially outside the island of Java, by providing necessary infrastructures such as electricity, ports, and roads, so that this development creates favorable economic conditions for investment and industrial development in such areas.

DETERMINANTS OF AGGLOMERATION IN KOREAN MANUFACTURING INDUSTRIES

Despite accumulated findings on the effects of agglomeration on productivity of manufacturing industries in Korea, little is known about the determinants of agglomeration. Employing an approach similar to Rosenthal and Strange (2001) [Rosenthal, S and W Strange (2001). The determinants of agglomeration. Journal of Urban Economics, 50(2), 191–229.], but using a different agglomeration index, this study examines whether the three microfoundations of agglomeration economies are important to the geographical concentration of Korean manufacturing industries. While estimation results generally confirm that labor market pooling, input sharing and knowledge spillovers contribute to agglomeration, we found some differences with the previous literature. First, non-manufactured inputs are more influential on agglomeration than manufactured inputs. Secondly, aggregate innovation activities, rather than their share of shipments, are a better measure of knowledge spillovers to explain agglomeration. Thirdly, agglomeration of newly established firms is also influenced by the Marshallian externalities with labor market pooling having a stronger and consistent effect. These results are robust to instrumental variables estimation to control for endogeneity related to knowledge spillovers and labor market pooling.