Scientometrics of Scientometrics: Mapping Historical Footprint and Emerging Technologies in Scientometrics

Scientometrics is the study of quantitative aspects of science, technology, and innovation. This chapter identifies thematic patterns and emerging trends of the published literature in scientometrics using a variety of tools and techniques, including CiteSpace, VOSviewer, and dynamic topic modeling. Using 8098 bibliographic records of published scientometrics research, we explored domain-level citation paths, subject category assignment, keyword co-occurrence, topic models, and document co-citation network to map and characterize the intellectual landscapes of scientometrics. Findings reveal that the domain is multidisciplinary in that a wide range of disciplines contribute to the growth of literature, but only partially interdisciplinary as some works heavily cites from similar domains. Early literature was interested in measuring the impact of a science and evaluating research performance and productivity. Modeling scientometrics laws and indicators is also of greatest interest. Later work explored applications of scientometrics to a variety of domains such as material sciences, medicine, environmental sciences, and social media analytics. Impact measure and science mapping are among the topics receiving consistent attention

Three essays in financial economics

The first essay, Wage Differentials, Firm Investment, and Stock Returns, investigates the effects of labor costs on firms’ capital investments and stock returns. I estimate wage premia across U.S. industries and show that the negative investment-return relation implied by q-theory is steeper for high wage firms than for low wage firms. Using wage premia as a proxy for labor adjustment costs, an extended investment-based model predicts the interaction effect because capital-labor complementarity implies that labor market friction also governs the investment decision. The inflexibility induced by wages offers new insights into asset prices and corporate investments. In the second essay, Anomalies in the Joint Cross Section of Equity and Corporate Bond Returns, we show that many cross-sectional anomalies in equity returns do not appear in the corporate bond returns of the same firms. These puzzling findings are in fact consistent with contingent claim pricing. Corporate bonds typically have low credit risk and their hedge ratios, or the sensitivity of debt to equity, are quite small. As a result, much less than 10% of equity return premia translate to corresponding bond return premia. Exceptions are asset growth, investment, and momentum, in which bond return premia are too large compared with hedge ratios, suggesting that the bond return premia are driven by channels that function independently of changes in underlying firm values. We also document the investor sentiment effect in corporate bonds by showing that expected returns on bond portfolios hedged against equity risk increase with sentiment and are concentrated on the short side of long-short strategies. The third essay, Labor Skills and Technology Change, highlights the importance of labor characteristics for firm behavior and asset prices. The productivity of skilled labor is subjected to aggregate technology innovation, implying that a firm’s usage of skilled labor determines its exposure to the shock. I find that profits are more sensitive to technology shocks in firms depend more on skilled worker. Combined with the positive price of technology risk, high skill firms have higher expected returns than low skill firms

Perspectives on blended learning through the on-line platform, LabLessons, for Chemistry

The effectiveness of blended learning was evaluated through the integration of an online chemistry platform, LabLessons. Two modules, Formation of Hydrogen and Titration, were designed by college mentors alongside classroom chemistry teachers to engage and allow high school students to better comprehend these scientific topics. The pre-lab modules introduced the students to experiments they were expected to perform in class the following day. The modules consisted of an introduction as well as either a visualization and/or simulation specific to each topic. Students and teachers who utilized LabLessons were surveyed to establish a preliminary research on the use of technology in classrooms. Student and teacher surveys demonstrated LabLessons to be an interactive and helpful tool to improve students' understanding of conceptual ideasPeer Reviewe

Knowledge Distillation from Language-Oriented to Emergent Communication for Multi-Agent Remote Control

In this work, we compare emergent communication (EC) built upon multi-agent deep reinforcement learning (MADRL) and language-oriented semantic communication (LSC) empowered by a pre-trained large language model (LLM) using human language. In a multi-agent remote navigation task, with multimodal input data comprising location and channel maps, it is shown that EC incurs high training cost and struggles when using multimodal data, whereas LSC yields high inference computing cost due to the LLM's large size. To address their respective bottlenecks, we propose a novel framework of language-guided EC (LEC) by guiding the EC training using LSC via knowledge distillation (KD). Simulations corroborate that LEC achieves faster travel time while avoiding areas with poor channel conditions, as well as speeding up the MADRL training convergence by up to 61.8% compared to EC

Holographic Gubser-Rocha model does not capture all the transport anomalies of strange metals

In the last decade, motivated by the concept of Planckian relaxation and the possible existence of a quantum critical point in cuprate materials, holographic techniques have been extensively used to tackle the problem of strange metals and high-Tc superconductors. Among the various setups, the Gubser-Rocha model has often been celebrated as a successful holographic model for strange metals since endowed with the famous linear in $T$ resistivity property. As fiercely advocated by Phil Anderson, beyond $T$-linear resistivity, there are several additional anomalies unique to the strange metal phase, as for example a Fermi liquid like Hall angle -- the famous problem of the two relaxation scales. In this short note, we show that the holographic Gubser Rocha model fails in this respect and therefore, at least in its original and simplest form, is not able to capture the transport phenomenology of strange metals. We prove our statement by means of a direct numerical computation, a previously demonstrated scaling analysis and also a hydrodynamic argument. Finally, we conclude with an optimistic discussion on the possible improvements and generalizations which could lead to a holographic model for strange metals in all their glory.Comment: v1: 6 pages, 2 figure

Morphology Transformation of Foldamer Assemblies Triggered by Single Oxygen Atom on Critical Residue Switch

The synthesis of morphologically well-defined peptidic materials via self-assembly is challenging but demanding for biocompatible functional materials. Moreover, switching morphology from a given shape to other predictable forms by molecular modification of the identical building block is an even more complicated subject because the self-assembly of flexible peptides is prone to diverge upon subtle structural change. To accomplish controllable morphology transformation, systematic self-assembly studies are performed using congener short β-peptide foldamers to find a minimal structural change that alters the self-assembled morphology. Introduction of oxygen-containing β-amino acid (ATFC) for subtle electronic perturbation on hydrophobic foldamer induces a previously inaccessible solid-state conformational split to generate the most susceptible modification site for morphology transformation of the foldamer assemblies. The site-dependent morphological switching power of ATFC is further demonstrated by dual substitution experiments and proven by crystallographic analyses. Stepwise morphology transformation is shown by modifying an identical foldamer scaffold. This study will guide in designing peptidic molecules from scratch to create complex and biofunctional assemblies with nonspherical shapes

Pole-skipping points in 2D gravity and SYK model

We represent the first investigation of pole-skipping on both the gravity and field theory sides. In contrast to the higher dimensional models, there is no momentum degree of freedom in $(1+1)-$dimensional bulk theory. Thus, we then consider a scalar field mass as our degree of freedom for the pole-skipping phenomenon instead of momentum. The pole-skipping frequencies of the scalar field in 2D gravity are the same as higher dimensional cases: $\omega=-i2\pi Tn$ for positive integer $n$. At each of these frequencies, there is a corresponding pole-skipping mass, so the pole-skipping points exist in the $(\omega,m)$ space. We also compute the pole-skipping points of the SYK model in $(\omega, h)$ space where $h$ is the dimension of the bilinear primary operator. We find that there is a one-to-one correspondence of the pole-skipping points between the JT gravity and the SYK model. To obtain the pole-skipping points, we need to consider the parameter $\epsilon$ related to chemical potential on the horizon of charged JT gravity and the particle-hole asymmetric parameter $\mathcal{E}$ of the complex SYK model as shift parameters. This highlights the $\epsilon-\mathcal{E}$ correspondence in relation to pole-skipping