Two qq-operational equations and Hahn polynomials

Motivated by Liu's recent work in \cite{Liu2022}. We shall reveal the essential feature of Hahn polynomials by presenting two new $q$-exponential operators. These lead us to use a systematic method to study identities involving Hahn polynomials. As applications, we use the method of $q$-exponential operator to prove the bilinear generating function of Hahn polynomials and Heine's second transformation formula. Moreover, a generalization of $q$-Gaussian summation is given, too

Integrable Open Spin Chains from Flavored ABJM Theory

We compute the two-loop anomalous dimension matrix in the scalar sector of planar ${\cal N}=3$ flavored ABJM theory. Using coordinate Bethe ansatz, we obtain the reflection matrix and confirm that the boundary Yang-Baxter equations are satisfied. This establishes the integrability of this theory in the scalar sector at the two-loop order.Comment: v2, 25 pages, 2 figures, minor corrections, references adde

Marine Ecological Disasters and Their Physical Controlling Mechanisms in Jiangsu Coastal Area

The studies in this chapter are focused on marine ecological disasters in Jiangsu coastal area. Three kinds of algal blooms occurred in this region, namely, red tide associated with Dinoflagellate, green tide associated with Ulvaprolifera and golden tide associated with Sargassum. Numerical model results demonstrated that red tides in Haizhou Bay originated locally, because most of Dinoflagellates near Zhoushan Islands would be transported northeastward by the Changjiang diluted water, and even the lucky ones that entered the south of Jiangsu coastal area would die in the Subei Shoal due to high turbidity there. Due to the Changjiang diluted water and the prevailing southerly wind, Ulvaprolifera could not drift southward, either. Seawater with high turbidity in the Subei Shoal limited sunlight penetration into deep water column, and further inhibited the growth of Ulvaprolifera suspending in the water column. In this chapter, we use drift bottles and satellite-tracked Argos drifters to provide solid direct dynamic evidence that Ulvaprolifera could drift from the Subei Shoal to Qingdao coastal area and even further north. The sand ridges limited the traveling path of Ulvaprolifera in the Subei Shoal, and wind-driven currents and other baroclinic processes helped Ulvaprolifera travel farther to the north

Vernier spectrometer using counter-propagating soliton microcombs

Acquisition of laser frequency with high resolution under continuous and abrupt tuning conditions is important for sensing, spectroscopy and communications. Here, a single microresonator provides rapid and broad-band measurement of frequencies across the optical C-band with a relative frequency precision comparable to conventional dual frequency comb systems. Dual-locked counter-propagating solitons having slightly different repetition rates are used to implement a Vernier spectrometer. Laser tuning rates as high as 10 THz/s, broadly step-tuned lasers, multi-line laser spectra and also molecular absorption lines are characterized using the device. Besides providing a considerable technical simplification through the dual-locked solitons and enhanced capability for measurement of arbitrarily tuned sources, this work reveals possibilities for chip-scale spectrometers that greatly exceed the performance of table-top grating and interferometer-based devices

Demonstration of efficient scheme for generation of "Event Ready" entangled photon pairs from single photon source

We present a feasible and efficient scheme, and its proof-of-principle demonstration, of creating entangled photon pairs in an event-ready way using only simple linear optical elements and single photons. The quality of entangled photon pair produced in our experiment is confirmed by a strict violation of Bell's inequality. This scheme and the associated experimental techniques present an important step toward linear optics quantum computation.Comment: 4 pages, 4 figure

Prompt-based Node Feature Extractor for Few-shot Learning on Text-Attributed Graphs

Text-attributed Graphs (TAGs) are commonly found in the real world, such as social networks and citation networks, and consist of nodes represented by textual descriptions. Currently, mainstream machine learning methods on TAGs involve a two-stage modeling approach: (1) unsupervised node feature extraction with pre-trained language models (PLMs); and (2) supervised learning using Graph Neural Networks (GNNs). However, we observe that these representations, which have undergone large-scale pre-training, do not significantly improve performance with a limited amount of training samples. The main issue is that existing methods have not effectively integrated information from the graph and downstream tasks simultaneously. In this paper, we propose a novel framework called G-Prompt, which combines a graph adapter and task-specific prompts to extract node features. First, G-Prompt introduces a learnable GNN layer (\emph{i.e.,} adaptor) at the end of PLMs, which is fine-tuned to better capture the masked tokens considering graph neighborhood information. After the adapter is trained, G-Prompt incorporates task-specific prompts to obtain \emph{interpretable} node representations for the downstream task. Our experiment results demonstrate that our proposed method outperforms current state-of-the-art (SOTA) methods on few-shot node classification. More importantly, in zero-shot settings, the G-Prompt embeddings can not only provide better task interpretability than vanilla PLMs but also achieve comparable performance with fully-supervised baselines.Comment: Under revie

Research progress on the premature ovarian failure caused by cisplatin therapy.

Cisplatin is a common anticancer drug able to kill tumor cells, but it causes adverse reactions in the kidney, digestive tract, and other systems. The antitumor effects of cisplatin are mainly due to its ability to bind to the DNA in tumor cells to prevent replication, thereby reducing RNA and protein syntheses, leading to cell damage and death. Cisplatin has a wide range of applications; it can be used to treat cervical, thyroid, ovarian, and other cancers. Cisplatin has a beneficial therapeutic effect, but its therapeutic selectivity is poor. In addition to eliminating diseased target cells, cisplatin can damage normal cells; in women of reproductive age being treated for cancer, cisplatin can lead to ovarian function impairment, premature ovarian failure (POF), and/or infertility. Therefore, reducing the adverse effects of cisplatin on ovarian function is an important topic in clinical research. In this paper, we explore the research progress on the POF caused by cisplatin treatment

Neuronal representation of working memory in the medial prefrontal cortex of rats

Working memory is a process for short-term active maintenance of information. Behavioral neurophysiological studies in monkeys have demonstrated that the dorsolateral prefrontal cortex (dlPFC) is a key cortical region for working memory. The medial prefrontal cortex (mPFC) in rats is a cortical area similar to the dlPFC in monkeys in terms of anatomical connections, and is also required for behavioral performance on working-memory tasks. However, it is still controversial regarding whether and how mPFC neurons encode working memory. In the present study, we trained rats on a two-choice spatial delayed alternation task in Y maze, a typical working memory task for rodents, and investigated neuronal activities in the mPFC when rats performed the task. Our results show that, (1) inactivation of the mPFC severely impaired the performance of rats on the task, consistent with previous studies showing the importance of the mPFC for working-memory tasks; (2) 93.7% mPFC cells (449 in 479) exhibited changes in spiking frequency that were temporally locked with the task events, some of which, including delay-related cells, were tuned by spatial information; (3) differential delay activities in individual mPFC cells appeared transiently and sequentially along the delay, especially during the early phase of the delay; (4) some mPFC cells showed no change in discharge frequency but exhibited differential synchronization in firing during the delay. The present results suggest that mPFC neurons in rats are involved in encoding working memory, via increasing firing frequency or synchronization

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

As the focus on Large Language Models (LLMs) in the field of recommendation intensifies, the optimization of LLMs for recommendation purposes (referred to as LLM4Rec) assumes a crucial role in augmenting their effectiveness in providing recommendations. However, existing approaches for LLM4Rec often assess performance using restricted sets of candidates, which may not accurately reflect the models' overall ranking capabilities. In this paper, our objective is to investigate the comprehensive ranking capacity of LLMs and propose a two-step grounding framework known as BIGRec (Bi-step Grounding Paradigm for Recommendation). It initially grounds LLMs to the recommendation space by fine-tuning them to generate meaningful tokens for items and subsequently identifies appropriate actual items that correspond to the generated tokens. By conducting extensive experiments on two datasets, we substantiate the superior performance, capacity for handling few-shot scenarios, and versatility across multiple domains exhibited by BIGRec. Furthermore, we observe that the marginal benefits derived from increasing the quantity of training samples are modest for BIGRec, implying that LLMs possess the limited capability to assimilate statistical information, such as popularity and collaborative filtering, due to their robust semantic priors. These findings also underline the efficacy of integrating diverse statistical information into the LLM4Rec framework, thereby pointing towards a potential avenue for future research. Our code and data are available at https://github.com/SAI990323/Grounding4Rec.Comment: 17 page