Structural and magnetic properties of CeZnAl3_3 single crystals

We have synthesized single crystals of CeZnAl$_3$, which is a new member of the family of the Ce-based intermetallics Ce$TX_3$ ($T$ = transition metal, $X$= Si, Ge, Al), crystallizing in the non-centrosymmetric tetragonal BaNiSn$_3$-type structure. Magnetization, specific heat and resistivity measurements all show that CeZnAl$_3$ orders magnetically below around 4.4 K. Furthermore, magnetization measurements exhibit a hysteresis loop at low temperatures and fields, indicating the presence of a ferromagnetic component in the magnetic state. This points to a different nature of the magnetism in CeZnAl$_3$ compared to the other isostructural Ce$T$Al$_3$ compounds. Resistivity measurements under pressures up to 1.8 GPa show a moderate suppression of the ordering temperature with pressure, suggesting that measurements to higher pressures are required to look for quantum critical behavior.Comment: 6 pages, 5 figure

Nonlinear saturation of reversed shear Alfven eigenmode via high-frequency quasi-mode generation

A nonlinear saturation mechanism for reversed shear Alfven eigenmode (RSAE) is proposed and analysed, and is shown to be of relevance to typical reactor parameter region. The saturation is achieved through the generation of high-frequency quasi-mode due to nonlinear coupling of two RSAEs, which is then damped due to coupling with the shear Alfven continuum, and leads to the nonlinear saturation of the primary RSAEs . An estimation of the nonlinear damping rate is also provided.Comment: submitted to Plasma Physics and Technolog

A network SIS meta-population model with transportation flow

This paper considers a deterministic Susceptible-Infected-Susceptible (SIS) metapopulation model for the spread of a disease in a strongly connected network, where each node represents a large population. Individuals can travel between the nodes (populations). We derive a necessary and sufficient condition for the healthy equilibrium to be the unique equilibrium of the system, and then in fact it is asymptotically stable for all initial conditions (a sufficient condition for exponential stability is also given). If the condition is not satisfied, then there additionally exists a unique endemic equilibrium which is exponentially stable for all nonzero initial conditions. We then consider time-delay in the travel between nodes, and further investigate the role of the mobility rate that governs the flow of individuals between nodes in determining the convergence properties. We find that sometimes, increasing mobility helps the system converge to the healthy equilibrium.</p

Compositional Exemplars for In-context Learning

Large pretrained language models (LMs) have shown impressive In-Context Learning (ICL) ability, where the model learns to do an unseen task via a prompt consisting of input-output examples as the demonstration, without any parameter updates. The performance of ICL is highly dominated by the quality of the selected in-context examples. However, previous selection methods are mostly based on simple heuristics, leading to sub-optimal performance. In this work, we formulate in-context example selection as a subset selection problem. We propose CEIL (Compositional Exemplars for In-context Learning), which is instantiated by Determinantal Point Processes (DPPs) to model the interaction between the given input and in-context examples, and optimized through a carefully-designed contrastive learning objective to obtain preference from LMs. We validate CEIL on 12 classification and generation datasets from 7 distinct NLP tasks, including sentiment analysis, paraphrase detection, natural language inference, commonsense reasoning, open-domain question answering, code generation, and semantic parsing. Extensive experiments demonstrate not only the state-of-the-art performance but also the transferability and compositionality of CEIL, shedding new light on effective and efficient in-context learning. Our code is released at https://github.com/HKUNLP/icl-ceil.Comment: Accepted in ICML 202

AIGC Empowering Telecom Sector White Paper_chinese

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the telecom sector provides infrastructure support for the development of AI, and even takes the lead in the implementation of AI applications. How to enable the application of AIGC (GPT) and implement AIGC in the telecom sector are questions that telecom practitioners must ponder and answer. Through the study of GPT, a typical representative of AIGC, the authors have analyzed how GPT empowers the telecom sector in the form of scenarios, discussed the gap between the current GPT general model and telecom services, proposed for the first time a Telco Augmented Cognition capability system, provided answers to how to construct a telecom service GPT in the telecom sector, and carried out various practices. Our counterparts in the industry are expected to focus on collaborative innovation around telecom and AI, build an open and shared innovation ecosystem, promote the deep integration of AI and telecom sector, and accelerate the construction of next-generation information infrastructure, in an effort to facilitate the digital transformation of the economy and society

Coevolutionary Dynamics of Actions and Opinions in Social Networks

Empirical studies suggest a deep intertwining between opinion formation and decision-making processes, but these have been treated as separate problems in the study of dynamical models for social networks. In this paper, we bridge the gap in the literature by proposing a novel coevolutionary model, in which each individual selects an action from a binary set and has an opinion on which action they prefer. Actions and opinions coevolve on a two-layer network. For homogeneous parameters, undirected networks, and under reasonable assumptions on the asynchronous updating mechanics, we prove that the coevolutionary dynamics is an ordinal potential game, enabling analysis via potential game theory. Specifically, we establish global convergence to the Nash equilibria of the game, proving that actions converge in a finite number of time steps, while opinions converge asymptotically. Next, we provide sufficient conditions for the existence of, and convergence to, polarized equilibria, whereby the population splits into two communities, each selecting and supporting one of the actions. Finally, we use simulations to examine the social psychological phenomenon of pluralistic ignorance.</p

Spatial convergence characteristics of low carbon economy and economic growth quality: based on Guangdong urban data

As China's economy transitions from a stage of high-speed growth to a stage of high-quality development, the concept of low-carbon and green economic development has gained increasing popularity. Mastering the regional differences and changing patterns of low-carbon economy and economic growth quality is an important prerequisite for further promoting low-carbon economic development and improving the quality of economic growth. Taking the data of 21 prefecture-level cities in Guangdong Province from 2008 to 2019 as examples, we calculated the low-carbon economy and the quality index of economic growth, and analyzed the convergences between them through coefficient of variation analysis and a panel data convergence model with fixed effects. The results showed that: First, the convergence of low-carbon economy was better than the convergence of economic growth quality. Second, the low-carbon economy of Guangdong Province had σ convergence, and the imbalance between regions of low-carbon economy was alleviated, but the quality of economic growth of Guangdong Province did not have σ convergence. Third, there was absolute and conditional β convergence in the quality of low-carbon economy and economic growth in Guangdong Province. Fourth, the convergence rate of low-carbon economy in Guangdong Province showed "club difference"; the same was true of σ convergence, absolute β convergence, conditional β convergence, and dimensional convergence of economic growth quality in various regions of Guangdong Province. The exploration conducted in this article was conducive to better grasping the changing patterns of low-carbon economy and economic growth quality, enriching relevant research. The conclusions of this paper can provide decision-making basis for China to formulate urban and regional economic policies, achieve high-quality economic development, and "double carbon goal"

A Review of Sipuleucel-T in Combination with Other Therapies for Metastatic Castration-Resistant Prostate Cancer

Recent research has expanded the therapeutic landscape for sipuleucel-T by introducing several combination treatments. These include innovative hormone therapies (enzalutamide and abiraterone), immunomodulatory agents (including IL-15, IL-7, atezolizumab, ipilimumab, and indoximod), DNA vaccines, and radiopharmaceuticals, many of which have demonstrated enhanced clinical outcomes and received approval from the U.S. Food and Drug Administration (FDA). These combination therapies present novel opportunities to enhance patient survival and quality of life. Sipuleucel-T, a significant autologous cell immunotherapy, was approved by the FDA in 2010 for the treatment of patients with asymptomatic or minimally symptomatic metastatic castration-resistant prostate cancer (mCRPC). Integration of sipuleucel-T with other therapeutic modalities holds promise for advancing mCRPC treatment. Nevertheless, the optimal sequencing and combination strategies for sipuleucel-T with other therapies remain under investigation, with numerous clinical trials currently exploring new treatment paradigms. Incorporation of these therapies, particularly to develop more effective and personalized treatment strategies, necessitates additional research. Future studies should aim to ascertain the optimal timing and sequencing of treatments and to identify biomarkers that can predict treatment responses, thereby enhancing outcomes for patients with mCRPC. This review underscores potential strategies for the integration of sipuleucel-T with other therapies and examines their therapeutic potential in mCRPC