Miracle-dz/UniFAR-FTUs huggingface dataset:
A Video is Worth 10, 000 Words: Training and Benchmarking with Diverse Captions for Better Long Video Retrieval

Existing long video retrieval systems are trained and tested in the paragraph-to-video retrieval regime, where every long video is described by a single long paragraph. This neglects the richness and variety of possible valid descriptions of a video, which could be described in moment-by-moment detail, or in a single phrase summary, or anything in between. To provide a more thorough evaluation of the capabilities of long video retrieval systems, we propose a pipeline that leverages state-of-the-art large language models to carefully generate a diverse set of synthetic captions for long videos. We validate this pipeline's fidelity via rigorous human inspection. We then benchmark a representative set of video language models on these synthetic captions using a few long video datasets, showing that they struggle with the transformed data, especially the shortest captions. We also propose a lightweight fine-tuning method, where we use a contrastive loss to learn a hierarchical embedding loss based on the differing levels of information among the various captions. Our method improves performance both on the downstream paragraph-to-video retrieval task (+1.1% R@1 on ActivityNet), as well as for the various long video retrieval metrics we compute using our synthetic data (+3.6% R@1 for short descriptions on ActivityNet). For data access and other details, please refer to our project website at https://mgwillia.github. io/10k-words.
Advancements and Trends in Ultra-High-Resolution Image Processing: An Overview

Currently, to further improve visual enjoyment, Ultra-High-Definition (UHD) images are catching wide attention. Here, UHD images are usually referred to as having a resolution greater than or equal to $3840 \times 2160$. However, since the imaging equipment is subject to environmental noise or equipment jitter, UHD images are prone to contrast degradation, blurring, low dynamic range, etc. To address these issues, a large number of algorithms for UHD image enhancement have been proposed. In this paper, we introduce the current state of UHD image enhancement from two perspectives, one is the application field and the other is the technology. In addition, we briefly explore its trends.
Dagger groups and $p$-adic distribution algebras

Let $(G,\omega)$ be a $p$-saturated group and $K/\mathbb{Q}_p$ a finite extension. In this paper we introduce the space of $K$-valued overconvergent functions $\mathcal{C}^\dagger(G,K)$. In the process we promote the rigid analytic group attached to $(G,\omega)$ in a previous work of the first two authors to a dagger group. A main result of this article is that under certain assumptions (satisfied for example when $G$ is a uniform pro-$p$ group) the distribution algebra $D^\dagger(G,K)$, i.e. the strong dual of $\mathcal{C}^\dagger(G,K)$, is a Fr\'{e}chet-Stein algebra in the sense of Schneider and Teitelbaum. In the last section we introduce overconvergent representations and show that there is an anti-equivalence of categories between overconvergent $G$-representations of compact type and continuous $D^\dagger(G, K)$-modules on nuclear Fr\'{e}chet spaces. This is analogous to the anti-equivalence between locally analytic representations and modules over the locally analytic distribution algebra as proved by Schneider and Teitelbaum.
The colored Jones polynomial of the figure-eight knot and an $\operatorname{SL}(2;\mathbb{R})$-representation

We study the asymptotic behavior of the $N$-dimensional colored Jones polynomial of the figure-eight knot, evaluated at $\exp\bigl((u+2p\pi\sqrt{-1})/N\bigr)$ as $N$ tends to infinity, where $u>\operatorname{arccosh}(3/2)$ is a real number and $p\ge1$ is an integer. It turns out that it corresponds to an $\operatorname{SL}(2;\mathbb{R})$ representation of the fundamental group of the knot complement. Moreover, it defines the adjoint Reidemeister torsion and the Chern--Simons invariant associated with the representation.
Degree of Migration and its Way: A Case Study of Potwar

Migration both in and out of the county has been playing an imperative function in reshaping the dimensions of distribution as well as redistribution of human settlement. Since independence in 1947 till now, Pakistan has been receiving a huge number of migrants from neighboring countries. These immigrants have added considerably to urbanization and growth of population in Pakistan, particularly in the Punjab and Sindh provinces.
Rethinking Detection Based Table Structure Recognition for Visually Rich Documents

Table Structure Recognition (TSR) is a widely discussed task aiming at transforming unstructured table images into structured formats, such as HTML sequences. One type of popular solution is using detection models to detect components of a table, such as columns and rows, then applying a rule-based post-processing method to convert detection results into HTML sequences. However, existing detection-based studies often have the following limitations. First, these studies usually pay more attention to improving the detection performance, which does not necessarily lead to better performance regarding cell-level metrics, such as TEDS, after the post-processing. Second, some solutions over-simplify the problem and can miss some critical information. Lastly, even though some studies defined the problem to detect six components, including table, row, column, spanning cell, projected row header, and column header, to provide as much information as other types of solutions, these studies ignore the fact this problem definition is a multi-label detection because row, projected row header and column header can share identical bounding boxes. Besides these limitations, there is often a performance gap between two-stage and transformer-based detection models regarding the structure-only TEDS, even though they have similar performance regarding the COCO metrics. Therefore, in this study, we revisit the limitations of existing detection-based solutions, compare two-stage and transformer-based detection models, and identify the key design aspects for the success of a two-stage detection model for the TSR task, including the multi-class problem definition, the aspect ratio for anchor box generation, and the feature generation of the backbone network. Without proposing sophisticated new components, we applied simple methods to improve these aspects of the Cascade R-CNN model, achieved state-of-the-art performance, and improved the baseline Cascade R-CNN model by 19.32%, 11.56% and 14.77% regarding the structure-only TEDS on SciTSR, FinTabNet, and PubTables1M datasets.
Minimalinvasive Wirbelsäulenchirurgie und aufkommende neue Techniken: Navigation, Robotik und Augmented Reality

Zusammenfassung Minimalinvasive Operationstechniken haben sich in den letzten Jahrzehnten kontinuierlich weiterentwickelt und bedeutende technische sowie technologische Fortschritte vollzogen. So konnte sich die minimalinvasive Wirbelsäulenchirurgie von gezielten Dekompressionsverfahren bis hin zu umfangreichen Stabilisierungsoperationen in weiten Anwendungsbereichen der Wirbelsäulenchirurgie bewähren. Die Vorteile liegen in reduziertem Zugangstrauma, niedrigeren Infektionsraten und schnellerer Genesung und somit verringerter Morbidität. Zur zunehmenden Verbreitung minimalinvasiver Techniken haben die sich ebenfalls stetig weiterentwickelnde intraoperative Bildgebung und Navigation entscheidend beigetragen. Schließlich ermöglichen diese eine Orientierung mit Detektion verdeckt liegender und nicht direkt visualisierbarer Strukturen und anatomischer Landmarken. Als neue Trends der letzten Jahre kommen nun auch im Bereich der Wirbelsäulenchirurgie die Robotik und Augmented Reality zum Einsatz. Dieser Übersichtsartikel befasst sich mit den intraoperativen Techniken der Navigation, Robotik und Augmented Reality bei minimalinvasiven Wirbelsäulenoperationen.
Discovery of high-pressure pelitic granulite in Ailaoshan orogenic belt,southeastern Tibet,and its tectonic implications

High-pressure pelitic granulite containing porphyroblasts of garnet(Grt),sillimanite(Sil),K-feldspar(Kf) and plagioclase(Pl),and inclusions of spinel(Spl),kyanite(Ky),sapphirine(Spr) and rutile(Rut) have been found from the Ailaoshan orogenic belt,southeastern Tibet,regarded as a key indicator for identification of the boundary between the Indochina and South China blocks.The temperatures and pressures calculated by garnet-biotite-plagioclase-quartz geothermobarometery and hightemperature equilibrium spinel + quartz assemblage show the formation and evolution of the graunlite had experienced clockwise P-T path from high-pressure/-temperature to mid-temperature and low-pressure metamorphism.That are:1) the high-pressure/-temperature metamorphism(HP/HT) is characterized by an assemblage of Ky + Sil + Grt1 + Kf1 + Pl1 + Spr + Ter(Kf + Pl) + Bt1 + Spl + Qtz + Ilm1 + Rut1,and the peak P-T conditions of ≥ 10.4kbar at 850 ～ 919℃;2) the mid-temperature and low-pressure retrogressive metamorphism characterized by an assemblage of Grt2 + Bt2 + Pl2 + Ms + Qtz + Ilm2 + Rut2,and two stage P-T conditions of 4.9 ～ 6.5kbar at 664 ～ 754℃ and 3.5 ～ 3.9kbar at 572 ～ 576℃ respectively.The dynamic metamorphic path was that the metapelitic rock experienced high-pressure/-temperature granulite-facies metamorphism in lower continental crust(≥30km) exhumated to mid-upper crust rapidly,it might be related to the continental collision and underthrusting between the Indochina and South China blocks,and exhumation and slip shearing lately.
Wilderness Experiences What Should We Be Managing For

The U.S. Wilderness Act gives wilderness managers a challenging stewardship responsibility: to provide and/or protect opportunities for certain types of human experiences. The act states that wilderness “shall be administered for the use and enjoyment of the American people in such manner as will leave them unimpaired for future use and enjoyment as wilderness. ” The significant clause that they are to be enjoyed “as wilderness” is further defined under the definitional characteristics of wilderness. Here wilderness is defined, in part, as an area that “has outstanding opportunities for solitude or a primitive and unconfined type of recreation. ” This is all the guidance the Act provides regarding the responsibilities of wilderness managers regarding recreational experiences in wilderness. Since their primary responsibility is to preserve wilderness character, managers need clear objectives regarding human experiences in wilderness, as well as an understanding of how well those objectives are being attained. Several of the other articles in this issue provide perspective on concepts of solitude, primitive recreation, and unconfined recreation. My concern is whether stewardship objectives should relate most directly to the kinds of experiences people are having in wilderness, their evaluations of those experiences, or their opportunities for certain kinds of experiences. The answer to this question is relevant to how we should monitor and assess wilderness character, as well as the indicators we might adopt in a Limits of Acceptable Change or similar type of wilderness management plan.
Exploring the Brain Characteristics of Structure-informed Functional Connectivity through Graph Attention Network

Independent brain regions in neuroanatomy achieve a specific function through connections. As one of the significant morphological features of the cerebral cortex, previous studies have found significant differences in the structure and function of the cerebral gyri and sulci, which provides a basis for us to study the functional connectivity differences between these two anatomic parts. Previous studies using fully connected functional connectivity (FC) and structural connectivity (SC) matrices found significant differences in the perspective of region or connection in gyri and sulci. However, a clear issue is that previous studies have only analyzed the differences through either FC or SC, without effectively integrating both. Meanwhile, another nonnegligible issue is that the subcortical areas, involved in various tasks, have not been systematically explored with cortical regions. Due to the strong coupling between FC and SC, we use SC-informed FC to systematically explore the functional characteristics of gyri/sulci and subcortical regions by combining deep learning method with magnetic resonance imaging (MRI) technology. Specifically, we use graph attention network (GAT) to explore the important connections in the SC-informed FC through the Human Connectome Project (HCP) dataset. With high classification results of above 99%, we have successfully discovered important connections under different tasks. We have successfully explored the importance of different types of connections. In low threshold, gyri-gyri are the most important connections. With the threshold increasing, sub-sub become the most important. Gyri have a higher importance in functional connectivity than sulci. In the seven task states, these connections are mainly distributed among the front, subcortical, and occipital. This study provides a novel way to explore the characteristics of functional connectivity at the whole brain scale.
Ground Observation of Microphysical Properties in Shanxi Province

Using a DMT(Droplet Measurement Technologies) continuous flow streamwise thermal gradient cloud condensation nuclei(CCN) counter and the precipitation particle spectrometer,ground measurements of CCN and raindrop size distribution in Shanxi were conducted.According to the observation,affected by meteorological factors and human activities,the CCN concentration variations had a distinctive diurnal cycle with two apparent peaks.Precipitation had an scavenging effect on CCN particles.According to the expression N CCN =CS k,the CCN spectra can be derived.The fitting spectra parameters C (more than 2000) and k (less than 1) show the continental characteristic of CCN in Taiyuan.Microstructure parameters for stratiform and stratocumulus cloud precipitation were analyzed.It was found that the number concentrations of raindrop were 74-229m-3 and 305-743m-3,the average of liquid water magnitudes were 10-2g/m 3 and 10-1g/m 3 and the maximum raindrop diameters were 1.78mm and 4.7mm of three stratiform and stratocumulus cloud precipitation,respectively.Less than 1 mm and 0.2-2 mm raindrops made a bigger contribution to the number concentration and rainfall intensity of stratiform cloud precipitation.0.2-2 mm and 1-3 mm raindrops made a bigger contribution to the number concentration and rainfall intensity of stratocumulus cloud precipitation.Stable spectra appeared in stratiform cloud were more than that of stratocumulus cloud.From the instantaneous spectrum distribution,most of stratiform raindrop size distribution had single,double,and three peaks and less stratiform raindrop size distribution had four and five peaks.Stratocumulus raindrop size distribution exhibited the multi-peak distribution mainly and no exponential distribution.From the average spectrum distribution,spectral width of stratiform cloud was narrower than that of stratocumulus cloud.Stratiform raindrop size distribution showed the exponential distribution.Stratocumulus raindrop size distribution displayed downward trend.The characteristics of raindrop spectra of convective-stratiform mixed cloud precipitation in Fenyang on 17 July 2008 were analyzed.The fluctuation of microphysical parameters was strong.The rainfall intensity was largely determined by the number concentration of raindrops.Under the same rainfall intensity,if there were more big size raindrops,radar reflectivity was even more.Through the strong echo,the number concentration,number of peaks,and spectral width were increased.
Influences of Gender Role Identity on Negative Attitudes toward Robots: A Survey in Japan

As a preliminary attempt to explore the influences of sexual orientation and gender identity on feelings and behavior toward robots, we conducted an online survey on 500 randomly selected Japanese monitors (age range, 20s to 60s) based on two psychological scales measuring negative attitudes toward robots and gender role identity. The results suggested that gender role identity, particularly perceived femininity, could affect attitudes toward robots more strongly than or have an interaction effect with biological sex.
Learning Spatial Reasoning in Virtual vs. Physical Games with Robots

Spatial reasoning is one of the malleable skills well-suited to be developed using robotics that not only benefits children in their pursuit of STEM-related topics but also fosters their perspective-taking skills on dimensions beyond spatial skills. In a study involving elementary school children aged 7-10 years old, we investigated the impact of playing a game with physical robots in a physical environment versus playing the same game with virtually embodied robots in a virtual environment. The game focused on developing spatial perspective-taking skills, requiring children to make moves based on the robots’ point of view. We examined how the two environments influenced their experience of fun and learning spatial reasoning skills. We conducted a between-subject user study with 59 participants from 3rd and 4th grades, where they either played with the physical or virtual version of the game. Children in both conditions showed significant improvement in their perspective-taking and spatial orientation test scores. Furthermore, they rated the physical game as more fun compared to the virtual version.
Investigating the Role of Robot Voices and Sounds in Shaping Perceived Intentions

This study explores if, and how, the choices made regarding a robot's speaking voice and characteristic body sounds influence viewers' perceptions of its intent i.e., whether the robot's intention is positive or negative. The analysis focuses on robot representations and sounds in three films: "Robots" (2005) [1], "NextGen" (2018) [2], and "Love, Death, and Robots - Three Robots" (2019) [3]. In eight qualitative interviews, five parameters (tonality, intonation, volume, pitch, and speed) were used to understand robot sounds and the participant's perception of a robot's attitude and intentions. The study culminates in a set of recommendations and considerations for human-robot interaction designers to consider while sound coding for body, physiology, and movement.
Robot Pets for Older Adults Adopted by Over Half of Swedish Municipalities

During the past decade, there has been an increased interest in using social companionship robots for older adults in care homes. Previous studies have shown that these robots, often in the shape of a household pet, can decrease stress and loneliness while increasing communication and quality of life. In our research, studying the effects of cat and dog robots at care homes, we got the impression that these robots are quite common and that the reason for implementing them varies. Therefore, we conducted an online survey, asking all municipalities in Sweden if they have social companionship robots, how they are using them and for what kind of care organisation. The result showed that more than half of the municipalities use pet robots for older adults, and most commonly for people with dementia to lower stress and increase the feeling of safety.
Identifying the Focus of Attention in Human-Robot Conversational Groups

We propose a method for detecting the group’s focus of attention: the visual point at which a majority of participants direct their gaze in a conversation. This information enables a robot to infer important conversational cues and adjust its behavior to support more natural conversational interactions. Our approach uses a Hidden Markov Model based on mimicry, where the robot observes the head orientation of participants and infers their gaze direction to identify the group’s focus of attention. We demonstrate our method by replicating the gaze patterns of the group members, showing that the robot can accurately determine the focal point. We evaluated our algorithm using a combination of datasets and real-world scenarios with a Fetch robot, demonstrating an accuracy of 81% compared to a baseline of 54%. Our proposed method has the potential to significantly improve group-oriented human-robot interaction.
Understanding Privacy-friendly Design of Robot Eyes

Eyes have been widely found to play an important role in communicating emotions and intentions for social robots. However, when introducing robots with eyes into people’s personal living spaces, it is necessary to consider how the social aspects of a robot impact perceptions of privacy. Specifically, in this paper we explored how the design of a robot’s eyes and eye-use behavior impacts use perception of privacy and related concerns. We developed a prototype robot with display-based eyes and investigated the impacts on perceptions of privacy concerns living with the robot. Our findings indicated that robot eye design does impact perceptions of privacy concerns, with the unexpected result of robots whose eyes that stay always on garnering lower concerns than eyes that close or turn off (the display) just before a person leaves. This result offer valuable insights for robot development and present empirical evidence on the influence of robot eye design on user privacy concerns.