Measuring and Advancing Commercial Courts\u27 Internationality

The rise of international commercial courts (“ICCs”) intensified discussions about their “internationality.” However, what “internationality” truly means—whether as a normative matter or its practical manifestation—remains unarticulated in the literature. Our Article addresses this gap by examining the concept of internationality in ICCs both theoretically and empirically, which has further prompted a reevaluation of global dispute resolution paradigms. This Article delivers three key contributions. First, it introduces a nuanced framework to assess an ICC’s internationality. Moving beyond seemingly obvious but ultimately superficial indicators of internationality (e.g., inclusion of foreign judges, use of English as the court language), this new framework is premised on the core objectives which internationalization processes are meant to achieve. This framework draws insights from comparisons with other established dispute resolution mechanisms and integrates foundational values of dispute resolution, such as impartiality, efficiency, diversity, and flexibility. Second, applying this framework, we identify significant discrepancies—both jurisdictional and procedural—between conceptual expectations and actual implementations in ICC judgments from China, Singapore, and the Netherlands. One notable example is the frequent involvement of international judges in cases unrelated to their home country’s legal systems. Third, the Article suggests targeted reforms inspired by these findings, proposing effective strategies for China and the Netherlands to enhance their ICCs’ standing without extensive legislative changes. More broadly, this study highlights the mismatch between normative assumptions and practical outcomes in dispute resolution, emphasizing the need to align theoretical benchmarks with intrinsic values and real-world dynamics of the field. Universit

SNC: A Cloud Service Platform for Symbolic-Numeric Computation using Just-In-Time Compilation

Cloud services have been widely employed in IT industry and scientific research. By using Cloud services users can move computing tasks and data away from local computers to remote datacenters. By accessing Internet-based services over lightweight and mobile devices, users deploy diversified Cloud applications on powerful machines. The key drivers towards this paradigm for the scientific computing field include the substantial computing capacity, on-demand provisioning and cross-platform interoperability. To fully harness the Cloud services for scientific computing, however, we need to design an application-specific platform to help the users efficiently migrate their applications. In this, we propose a Cloud service platform for symbolic-numeric computation - SNC. SNC allows the Cloud users to describe tasks as symbolic expressions through C/C++, Python, Java APIs and SNC script. Just-In-Time (JIT) compilation through using LLVM/JVM is used to compile the user code to the machine code. We implemented the SNC design and tested a wide range of symbolic-numeric computation applications (including nonlinear minimization, Monte Carlo integration, finite element assembly and multibody dynamics) on several popular cloud platforms (including the Google Compute Engine, Amazon EC2, Microsoft Azure, Rackspace, HP Helion and VMWare vCloud). These results demonstrate that our approach can work across multiple cloud platforms, support different languages and significantly improve the performance of symbolic-numeric computation using cloud platforms. This offered a way to stimulate the need for using the cloud computing for the symbolic-numeric computation in the field of scientific research.Comment: 13 pages, 23 figure

The weather affects air conditioner purchases to fill the energy efficiency gap

Energy efficiency improvement is often hindered by the energy efficiency gap. This paper examines the effect of short-run temperature fluctuations on the Energy Star air conditioner purchases in the United States from 2006 to 2019 using transaction-level data. Results show that the probability of purchasing an Energy Star air conditioner increases as the weekly temperature before the transaction deviates from 20–22 °C. A larger response is related to fewer cooling degree days in the previous years, higher electricity prices/income/educational levels/age/rate of owners, more common use of electricity, and stronger concern about climate change. 1 °C increase and decrease from 21 °C would lead to a reduction of total energy expenditure by 35.46 and 17.73 million dollars nationwide (0.13% and 0.06% of the annual total energy expenditure on air conditioning), respectively. Our findings have important policy implications for demand-end interventions to incorporate the potential impact of the ambient physical environment

Skull base metastases from a malignant solitary fibrous tumor of the liver. A case report and literature review

Solitary fibrous tumors (SFTs) of the liver are rarely described; only 38 cases have been reported in literature, most of which have shown benign clinical characteristics, and only 3 of these cases exhibited malignant variants. In this study, we present a 24-year-old woman with a 1-month history of a rapidly enlarging abdominal mass and a CT showing an exophytic heterogeneous liver mass with a firm parietal bone mass. The patient underwent a transcatheter arterial chemoembolization (TACE) before operation, and an extended right hepatectomy and craniectomy with a negative margin was performed under general anesthesia. The masses showed histological features of oval spindle cells haphazardly arranged in the classic short-storiform or so-called patternless pattern of solitary fibrous tumors. The tumor cells showed positive immunohistochemical reactions to CD34 and bcl-2. The tumor recurred in the residual liver 2 months after operation, metastatic osteoblastic lesions in the thoracic and lumbar vertebrae were identified 3 months after the operation, and lumbar vertebrae metastasis 7 months after operation paralyzed the patient. The patient underwent percutaneous ethanol injection therapy (PEI) and chemotherapy, but the patient died because of the uncontrolled tumor 16 months after the initial operation. To our knowledge, this is the first case of malignant solitary fibrous liver tumors with skeletal metastasis

CC2Vec: Combining Typed Tokens with Contrastive Learning for Effective Code Clone Detection

With the development of the open source community, the code is often copied, spread, and evolved in multiple software systems, which brings uncertainty and risk to the software system (e.g., bug propagation and copyright infringement). Therefore, it is important to conduct code clone detection to discover similar code pairs. Many approaches have been proposed to detect code clones where token-based tools can scale to big code. However, due to the lack of program details, they cannot handle more complicated code clones, i.e., semantic code clones. In this paper, we introduce CC2Vec, a novel code encoding method designed to swiftly identify simple code clones while also enhancing the capability for semantic code clone detection. To retain the program details between tokens, CC2Vec divides them into different categories (i.e., typed tokens) according to the syntactic types and then applies two self-attention mechanism layers to encode them. To resist changes in the code structure of semantic code clones, CC2Vec performs contrastive learning to reduce the differences introduced by different code implementations. We evaluate CC2Vec on two widely used datasets (i.e., BigCloneBench and Google Code Jam) and the results report that our method can effectively detect simple code clones. In addition, CC2Vec not only attains comparable performance to widely used semantic code clone detection systems such as ASTNN, SCDetector, and FCCA by simply fine-tuning, but also significantly surpasses these methods in both detection efficiency.Comment: 21 pages, 7 figure