Chinese FDI: A study of the impact of Chinese infrastructure investments in Kenya, Africa

Over the last century, Chinese Foreign Direct Investments have made great impacts on African countries. Large amounts of FDI from China has flooded into African infrastructure investments, targeting key sectors such as telecommunications, transportation, power plants, and port refurbishments. No doubt China treats itself as an equal and a generous partner of African countries, yet not an uncontroversial one especially from the perspective of foreign observers. There have been many critical voices on China-Africa relations over the years. In order to test the validity of the critiques as well as the praises, two infrastructure construction projects were chosen as case studies in this thesis. They are the Standard Gauge Railroad and A109 national road. Both contracts were signed between the Kenyan government and a Chinese state-owned company, Chinese Road and Bridge Cooperation (CRBC). By analyzing the first hand data and some supplementary second hand data, it indicates that though CRBC as contractor had made some decisions based on self-interests, the critics of labor importation and resource plunder lack supporting evidence. Instead, for these particular projects, they generated positive economic impacts on national development. However, many improvements are highly recommended for both parties to make the projects better in the future

Manipulation and Study of Gene Expression in Neurotoxin- Treated Neuronal PC12 and SH-SY5Y Cells for In Vitro Studies of Parkinson’s Disease

Neuronal PC12 and SH-SY5Y cells are highly suitable in vitro models for study of the neurodegenerative mechanisms occurring in Parkinson’s disease (PD). Differentiated PC12 and SH-SY5Y cells bear many similarities to the neuronal populations affected in PD, and they provide a convenient source of large amounts of homogeneous material for biochemical and molecular downstream applications. In the present review, we describe how to differentiate PC12 and SH-SY5Y cells into neuron-like cells and provide protocols for their transfection with plasmids and infection with viral particles to manipulate gene expression. We also describe how to treat neuronal PC12 and SH-SY5Y cells with the classical PD neurotoxins 6-hydroxydopamine (6-OHDA) and 1-methyl-4-phenyl-pyridinium ion (MPP+). Finally, we give detailed methods for several downstream applications useful for the analysis of cell death pathways in PD

Dominant-negative ATF5 rapidly depletes survivin in tumor cells.

Survivin (BIRC5, product of the BIRC5 gene) is highly expressed in many tumor types and has been widely identified as a potential target for cancer therapy. However, effective anti-survivin drugs remain to be developed. Here we report that both vector-delivered and cell-penetrating dominant-negative (dn) forms of the transcription factor ATF5 that promote selective death of cancer cells in vitro and in vivo cause survivin depletion in tumor cell lines of varying origins. dn-ATF5 decreases levels of both survivin mRNA and protein. The depletion of survivin protein appears to be driven at least in part by enhanced proteasomal turnover and depletion of the deubiquitinase USP9X. Survivin loss is rapid and precedes the onset of cell death triggered by dn-ATF5. Although survivin downregulation is sufficient to drive tumor cell death, survivin over-expression does not rescue cancer cells from dn-ATF5-promoted apoptosis. This indicates that dn-ATF5 kills malignant cells by multiple mechanisms that include, but are not limited to, survivin depletion. Cell-penetrating forms of dn-ATF5 are currently being developed for potential therapeutic use and the present findings suggest that they may pose an advantage over treatments that target only survivin

PIMSIM-NN: An ISA-based Simulation Framework for Processing-in-Memory Accelerators

Processing-in-memory (PIM) has shown extraordinary potential in accelerating neural networks. To evaluate the performance of PIM accelerators, we present an ISA-based simulation framework including a dedicated ISA targeting neural networks running on PIM architectures, a compiler, and a cycleaccurate configurable simulator. Compared with prior works, this work decouples software algorithms and hardware architectures through the proposed ISA, providing a more convenient way to evaluate the effectiveness of software/hardware optimizations. The simulator adopts an event-driven simulation approach and has better support for hardware parallelism. The framework is open-sourced at https://github.com/wangxy-2000/pimsim-nn

SDCL: Self-Distillation Contrastive Learning for Chinese Spell Checking

Due to the ambiguity of homophones, Chinese Spell Checking (CSC) has widespread applications. Existing systems typically utilize BERT for text encoding. However, CSC requires the model to account for both phonetic and graphemic information. To adapt BERT to the CSC task, we propose a token-level self-distillation contrastive learning method. We employ BERT to encode both the corrupted and corresponding correct sentence. Then, we use contrastive learning loss to regularize corrupted tokens' hidden states to be closer to counterparts in the correct sentence. On three CSC datasets, we confirmed our method provides a significant improvement above baselines

Breathing shelter—Relieve citizen pressure with the breath control

In this paper, we propose an interactive breathing shelter which could regulate the breath of city and its dwellers by influencing their breath speed to relieve their stress. An interactive urban shelter expresses the relationship between city and its dwellers through the action of breathing. In Schrödinger's book What is Life?, he originally stated that 'what an organism feeds upon is negative entropy' and that 'the essence of metabolism, in its survival period successfully ridding themselves of organisms, must have all the entropy.’ Cities increase in entropy due to pollution, traffic jams and information overload and so on. Meanwhile, these issues prompt stress in citizens. Breathing is the simplest way to counter the increase of entropy – people are noticeably relaxed and find it easier to concentrate after deep breathing. This city shelter thus aims to transform anxiety to relief – you breathe the city and the city also breathes back at you, in a mutual beneficial connectio

Innovative solutions for language growth: the impact of problem-based learning via DingTalk on Chinese undergraduates’ business vocabulary amid COVID-19

Amidst the COVID-19, which has necessitated the widespread use of distant learning, there has been a notable increase in the recognition and utilization of inventive pedagogical methods and technological tools in the field of language teaching. The primary objective of this research is to assess the effects of DingTalk-based PBL on the business vocabulary growth of Chinese undergraduates during the pandemic, with a particular focus on remote learning environments. This mixed-methods research employed a sample of 58 participants. The study involved both quantitative vocabulary assessments and qualitative interviews. The quantitative assessments aimed to measure the impact on vocabulary scores, while qualitative interviews were conducted to gather insights into participants’ experiences and perceptions regarding DingTalk-based PBL. The quantitative assessment revealed a significant improvement in business vocabulary scores among the participants who underwent DingTalk-based PBL. This result indicates the platform’s potential to enhance language acquisition. The qualitative interviews provided further insights, with participants expressing positive attitudes toward DingTalk-based PBL. They emphasized its capacity to sustain engagement, foster collaboration, and bridge the gap between remote learning and effective language acquisition. These findings underscore the transformative potential of DingTalk-based PBL in language education, especially in the context of challenges posed by the pandemic. While recognizing the constraints of this study, such as its limited duration and restricted contextual applicability, the research encourages further investigation into sustainable vocabulary expansion, the development of multifaceted language abilities, and the integration of these platforms into emerging hybrid educational frameworks. This study makes a valuable contribution to the ongoing discourse regarding novel technology-based methods in language instruction, providing relevant insights applicable to both present and future educational contexts

PIMSYN: Synthesizing Processing-in-memory CNN Accelerators

Processing-in-memory architectures have been regarded as a promising solution for CNN acceleration. Existing PIM accelerator designs rely heavily on the experience of experts and require significant manual design overhead. Manual design cannot effectively optimize and explore architecture implementations. In this work, we develop an automatic framework PIMSYN for synthesizing PIM-based CNN accelerators, which greatly facilitates architecture design and helps generate energyefficient accelerators. PIMSYN can automatically transform CNN applications into execution workflows and hardware construction of PIM accelerators. To systematically optimize the architecture, we embed an architectural exploration flow into the synthesis framework, providing a more comprehensive design space. Experiments demonstrate that PIMSYN improves the power efficiency by several times compared with existing works. PIMSYN can be obtained from https://github.com/lixixi-jook/PIMSYN-NN