A Dynamic Growth Model for Flows of Foreign Direct Investment

In this work, we for the first time study the dynamic flows of the foreign direct investment (FDI) with a dynamic growth theory. We define the FDI flow as a process which transmits throughout a given social system by way of diverse communication channels. In model formulation, seven assumptions are thus proposed and the foreign capital policy of the host country is considered as an external influence; in addition, the investment policy of the investing country is modeled as an internal influence. Classification of influences is mainly according to the operational strategy as well as the consideration of economical/financial factors. The dynamic model of FDI flow is a differential equation which is solved numerically and verified with collected realistic data. Application of the developed model to explore, taking the electronics industry in Taiwan as an example, Taiwanese direct investment (TDI) in China (i.e. FDI flows from Taiwan to China) since 2001 is conducted. Our preliminary results successfully account for the dynamics of FDI flow for different amount of TDI outflows. It is found that the internal influence dominates the growth of TDI flow from Taiwan to China during 2001-2006.Foreign direct investment, dynamic flow theory, growth model, and numerical simulation

Examining Forgetting in Continual Pre-training of Aligned Large Language Models

Recent advances in Large Language Models (LLMs) have exhibited remarkable proficiency across various tasks. Given the potent applications of LLMs in numerous fields, there has been a surge in LLM development. In developing LLMs, a common practice involves continual pre-training on previously fine-tuned models. However, this can lead to catastrophic forgetting. In our work, we investigate the phenomenon of forgetting that occurs during continual pre-training on an existing fine-tuned LLM. We evaluate the impact of continuous pre-training on the fine-tuned LLM across various dimensions, including output format, knowledge, and reliability. Experiment results highlight the non-trivial challenge of addressing catastrophic forgetting during continual pre-training, especially the repetition issue.Comment: Work in progres

Gene expression in early and progression phases of autosomal dominant polycystic kidney disease

<p>Abstract</p> <p>Background</p> <p>Little is known about the genes involved in the initial cyst formation and disease progression in autosomal dominant polycystic kidney disease (ADPKD); however, such knowledge is necessary to explore therapeutic avenues for this common inherited kidney disease.</p> <p>Findings</p> <p>To uncover the genetic determinants and molecular mechanisms of ADPKD, we analyzed 4-point time-series DNA microarrays from <it>Pkd1</it>^{<it>L</it>3/<it>L</it>3}mice to generate high resolution gene expression profiles at different stages of disease progression. We found different characteristic gene expression signatures in the kidneys of <it>Pkd1</it>^{<it>L</it>3/<it>L</it>3}mice compared to age-matched controls during the initial phase of the disease. By postnatal week 1, the <it>Pkd1</it>^{<it>L</it>3/<it>L</it>3}kidney already had a distinctive gene expression pattern different from the corresponding normal controls.</p> <p>Conclusion</p> <p>The genes differentially expressed, either induced or repressed, in ADPKD are important in immune defense, cell structure and motility, cellular proliferation, apoptosis and metabolic processes, and include members of three pathways (Wnt, Notch, and BMP) involved in morphogenetic signaling. Further analysis of the gene expression profiles from the early stage of cystogenesis to end stage disease identified a possible gene network involved in the pathogenesis of ADPKD.</p

The mediating effect of internal service quality on employee turnover – empirical evidence from Taiwanese nurses

Informed by social exchange theory (SET) this study examines the role of trust in strategic alliances. Interviews were conducted with 17 participants who were strategic alliance managers in their organization. The study finds that trust is important to strategic alliance managers, and without it alliance managers would find it difficult to keep their alliance going. Trust is built over time, and based on the past experiences that the alliance manager has with their partner. The study found that prior networks, timely and appropriate communication and information exchange, fairness preservation and inter-firm adaptation were important in developing trust in the strategic alliance