Our Work

Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory and visual information remain limited. So, we int…

Natural language descriptions can provide rich semantic representations of audio-visual urban scenes, yet datasets that jointly describe both auditory and visual information remain limited. So, we introduce AVSD-Scenes, a paired audio-visual scene description dataset for urban environments. The dataset contains 12,291 audio-visual scene descriptions generated from the TAU Urban Audio-Visual Scenes dataset [1].  The audio-visual dataset examples [1] can be downloaded from  https://zenodo.org/records/4477542  To construct the dataset, we first generate audio- and visual-based descriptions using Qwen2-Audio-7B and Qwen2.5-VL-7B, respectively. These modality specific descriptions are then combined using large language models, namely Qwen3-14B, Mistral-Small-3.2-24B-Instruct-2506, and Gemma-3-27B-it. Please visit our Github repository for codes, paper and more information. There are two files containing descriptions of the TAU Urban Audio-Visual Scenes dataset [1].  (1) master_captions xls : Descriptions when  scene label  is given as an instruction. (2) master_captions_without_scenelabel: Descriptions when  scene label  is not given as an instruction.   The fields in the above files are: scene_label filename_audio audio_caption filename_video visual_caption multimodal_qwen3_caption multimodal_mistral_caption multimodal_gemma_caption   where audio_caption:  audio descriptions using Qwen2-Audio-7B,  visual_caption:  visual descriptions using Qwen2.5-VL-7B, multimodal_model_caption: audio-visual descriptions using models (Qwen3-14B, Mistral-Small-3.2-24B-Instruct-2506, and Gemma-3-27B-it.). [1] Wang, Shanshan, et al. "A curated dataset of urban scenes for audio-visual scene analysis." IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021. (Paper link)

This document describes the CIAO DM (`Data Model') filtering and binning language. It has significant overlap with the on-line ahelp files found by typing `ahelp dm' in CIAO. Users may wish to first …

This document describes the CIAO DM (`Data Model') filtering and binning language. It has significant overlap with the on-line ahelp files found by typing `ahelp dm' in CIAO. Users may wish to first read the User Introduction which gives simple examples, and to use this document in conjuction with the Toolkit User Guide which describes the full DM syntax.

High-amplitude delta Scuti (HADS) stars are typically dominated by one or a few radial pulsation modes and exhibit large photometric amplitudes (ΔV > 0.1 mag). In some cases, these stars disp…

High-amplitude delta Scuti (HADS) stars are typically dominated by one or a few radial pulsation modes and exhibit large photometric amplitudes (ΔV > 0.1 mag). In some cases, these stars display amplitude and phase variability. Proposed explanations include nonlinear mode interaction and beating between closely spaced frequencies, while similarities to the Blazhko effect observed in RR Lyrae stars have also been suggested. The Blazhko effect remains a long-standing unsolved problem in stellar pulsation theory, manifesting as amplitude and/or phase modulation in about half of RR Lyrae stars and exhibiting a rich variety of observational phenomena. Using the light-curve products of the TESS Quick Look Pipeline, we analyse a selected sample of HADS stars showing clear amplitude and phase variability. We present a phenomenological comparison of the modulation-like behaviour observed in HADS and Blazhko RR Lyrae stars, including Fourier side-peak structures and the relationship between amplitude and phase variations.

The goal of study is to identify modifiable behavioral targets for future prevention efforts in children who face increased risk for pediatric obesity. The proposed study will contribute essential inf…

The goal of study is to identify modifiable behavioral targets for future prevention efforts in children who face increased risk for pediatric obesity. The proposed study will contribute essential information to our understanding of the neurocognitive mechanisms supporting eating behavior and resiliency to obesity,.

This document describes how to use the basic CIAO data filtering and binning toolkit, consisting of the programs dmlist, dmcopy and dmextract. It has significant overlap with the on-line ahelp files f…

This document describes how to use the basic CIAO data filtering and binning toolkit, consisting of the programs dmlist, dmcopy and dmextract. It has significant overlap with the on-line ahelp files for those tools. Users may wish to first read the User Introduction which gives simple examples, and to use this document in conjuction with the User Reference which describes the full DM syntax.

This manual describes the filtering and binning language used throughout the CIAO data analysis package, and some of the basic tools used to do simple analysis tasks. The name ``Data Model'' reflects…

This manual describes the filtering and binning language used throughout the CIAO data analysis package, and some of the basic tools used to do simple analysis tasks. The name ``Data Model'' reflects the intent that there be a high level interface which can be used on data files of different formats: we have a single abstract description (`model') that encompasses all the data files we use. Although the event list, source lists and exposure maps produced as output products from X-ray observations are quite different in their information content, they actually have a lot in common in their underlying structure.

Supplumentary data of this journal paper.

This document lists the functions provided by the CXC DataModel API. Some routine descriptions include multiple `contexts' indicating behaviour which may need to be tested separately and which may be …

This document lists the functions provided by the CXC DataModel API. Some routine descriptions include multiple `contexts' indicating behaviour which may need to be tested separately and which may be implemented in different releases. Each context is flagged with the DataModel release number it is expected to be supported in, e.g. (R1.9) for release 1.9.

Boerhavia diffusa is commonly known as Punarnava. It is an importantmedicinal herb belonging to the family Nyctaginaceae. It is widelydistributed throughout tropical and subtropical regions. Ethnomedi…

Boerhavia diffusa is commonly known as Punarnava. It is an importantmedicinal herb belonging to the family Nyctaginaceae. It is widelydistributed throughout tropical and subtropical regions. Ethnomedicinalapplications include the management of urinary disorders, oedema,jaundice, liver ailments, inflammation, digestive problems, asthma,rheumatism and several other health problems. Phytochemicalinvestigations have identified diverse groups of bioactive constituents andstudies showed its pharmacological values. Despite its broad distribution,increasing medicinal demand and destructive harvesting of roots may placepressure on natural populations. Sustainable collection, cultivation,authenticated planting material and conservation of traditional knowledgeare therefore important for its long-term utilization. This chapter highlightsits medicinal importance and draws attention towards its cultivation.