Prompt-based learning has emerged as a successful paradigm in natural language processing, where single general-purpose model can be instructed to perform any task specified by input prompts. Yet specification robotics comes various forms, such imitating one-shot demonstrations, following instructions, and reaching visual goals. They are often considered different tasks tackled specialized models. We show that wide spectrum of robot manipulation expressed with multimodal prompts,...

This paper presents a novel boundary based semiautomatic tool, ByLabel, for accurate image annotation. Given an image, ByLabel first detects its edge features and computes high quality fragments. Current labeling tools require the human to accurately click on numerous points. simplifies this just selecting among fragment proposals that automatically generates. To evaluate performance of By-Label, 10 volunteers, with no experiences annotation, labeled both synthetic real images. Compared...

Periodontitis is a worldwide oral disease induced by the interaction of subgingival bacteria and host response characterized local inflammation, bone resorption, tooth loss. Ginsenoside Rd (Rd) biologically active component derived from Panax ginseng has been demonstrated to exert antibacterial anti-inflammatory activities. This study aims investigate inhibitory efficiency towards Porphyromonas gingivalis ( P. ), periodontal inflammatory response, osteoclastogenesis in vitro further validate...

The ongoing discovery of highly reactive ambiphilic main-group species has significantly advanced the development chemistry, particularly in realms small molecule activation and catalysis. Theoretically, compounds featuring smaller HOMO–LUMO gaps gain stronger ambiphilicity higher reactivity. In this work, we fundamentally demonstrate that Me3Sb holds smallest gap among trimethylpnictines, indicating its outstanding ambiphilicity. Correspondingly, superior reactivity toward deoxygenation...

The stibinidene ArSb

As an important hydrological ecosystem component, the glacier basin has great significance for climate and environment, it is also linked to regional water sustainability. In this paper, sampling isotope analysis of glacial ice, ice-melt water, river (river midstream downstream), groundwater (spring), precipitation were carried out in a year Mingyong Glacier basin, which located at Meili Snow Mountains, Southeastern Tibetan Plateau. At same time, hydrograph separation recharge sources lower...

At present, most pelagic islands rely on the mainland for resource replenishment. And due to limited island area, it is not sufficient simultaneously place enough basic load facilities and new energy generation consumption a single island. Considering are distributed in groups, vigorously developing renewable around can be considered, divided into center Resource use produce transport electric power, fresh water hydrogen which needed The whole group forms cleaner green integrated system....

Recognizing isolated digits of the flight callsign is an important and challenging task for automatic speech recognition (ASR) in air traffic control (ATC). Fortunately, a kind prior ATC knowledge available from dynamic contextual information. In this work, we attempt to utilize improve performance identification by integrating it into language model (LM). The proposed approach named context-aware (CALM), which can be applied both ASR decoding rescoring phase. implemented with...

We present a robot eye-hand coordination learning method that can directly learn visual task specification by watching human demonstrations. Task is represented as function, which learned using inverse reinforcement learning(IRL [1]) inferring reward model from state transitions. The then used continuous feedbacks in an uncalibrated servoing(UVS [2]) controller designed for the execution phase. Our proposed raw videos, removes need hand-engineered specification. Benefiting use of traditional...

Effective therapies for the prevention and control of caries are urgently needed. Cariogenic streptococci play a key role in occurrence progression caries.

In the air traffic control (ATC) domain, automatic speech recognition (ASR) suffers from radio echo, which cannot be addressed by existing echo cancellation due to auditory-oriented optimization and poor generalization ability caused volatile transmission. this work, a contrastive learning-based framework is proposed tackle radio-echo for ASR task based on convolution networks with multiple paths recurrent neural networks. 1) By analyzing communication mechanism of ATC speech, novel...

With the development of Web2.0, micro-blogs gradually become a common essential part public life. The reviews in have huge hidden value. Many machine learning approaches been used to solve sentiment analysis. However, features existing researches are still not enough. To improve accuracy analysis, this paper, we use classification approach two tasks analysis: identifying opinion sentence and judging polarity emotional sentence. And incorporate five kinds features: lexicons-based features,...

Developing a robust Automatic Speech Recognition (ASR) system usually requires large amount of well-annotated samples which is extremely hard to build in the Air Traffic Control (ATC) due domain-specific knowledge. In this brief, we present novel approach improve ASR performance ATC domain by integrating self-supervised learning and multi-task into unified framework. Specifically, proposed framework follows two-stage training paradigm, i.e., (a) universal acoustic representations employing...

Abstract With the widespread popularity of edge computing, energy consumption devices has attracted lots research interests. This paper studies cloud-edge system under solar supply scenario, and optimizes parameter configuration according to photovoltaic power generation, reduce prolong running time. Specifically, we built an video detection based on Raspberry Pi, deeply analyzed model system. Based this, problem dynamically adjusting operating parameters is modeled as a long-term...

Summary We propose a new reinforcement learning method in the framework of Recursive Least Squares‐Temporal Difference (RLS‐TD). Instead using standard mechanism eligibility traces (resulting RLS‐TD( )), we to use forgetting factor commonly used gradient‐based or least‐square estimation, and show that it has similar role as traces. An instrumental variable perspective is adopted formulate algorithm, referred RLS‐TD with (RLS‐TD‐f). interesting aspect proposed algorithm an interpretation...