Video Question Answering: Datasets, Algorithms and Challenges

Video Question Answering (VideoQA) aims to answer natural language questions according to the given videos. It has earned increasing attention with recent research trends in joint vision and language understanding. Yet, compared with ImageQA, VideoQA is largely underexplored and progresses slowly. Although different algorithms have continually been proposed and shown success on different VideoQA datasets, we find that there lacks a meaningful survey to categorize them, which seriously impedes its advancements. This paper thus provides a clear taxonomy and comprehensive analyses to VideoQA, focusing on the datasets, algorithms, and unique challenges. We then point out the research trend of studying beyond factoid QA to inference QA towards the cognition of video contents, Finally, we conclude some promising directions for future exploration.Comment: Accepted by EMNLP 202

Anisotropic GPMP2: a fast continuous-time Gaussian processes based motion planner for unmanned surface vehicles in environments with ocean currents

In the past decade, there is an increasing interest in the deployment of unmanned surface vehicles (USVs) for undertaking ocean missions in dynamic, complex maritime environments. The success of these missions largely relies on motion planning algorithms that can generate optimal navigational trajectories to guide a USV. Apart from minimising the distance of a path, when deployed a USVs' motion planning algorithms also need to consider other constraints such as energy consumption, the affected of ocean currents as well as the fast collision avoidance capability. In this paper, we propose a new algorithm named anisotropic GPMP2 to revolutionise motion planning for USVs based upon the fundamentals of GP (Gaussian process) motion planning (GPMP, or its updated version GPMP2). Firstly, we integrated the anisotropy into GPMP2 to make the generated trajectories follow ocean currents where necessary to reduce energy consumption on resisting ocean currents. Secondly, to further improve the computational speed and trajectory quality, a dynamic fast GP interpolation is integrated in the algorithm. Finally, the new algorithm has been validated on a WAM-V 20 USV in a ROS environment to show the practicability of anisotropic GPMP2

Detection of Outliers in a Time Series of Available Parking Spaces

With the provision of any source of real-time information, the timeliness and accuracy of the data provided are paramount to the effectiveness and success of the system and its acceptance by the users. In order to improve the accuracy and reliability of parking guidance systems (PGSs), the technique of outlier mining has been introduced for detecting and analysing outliers in available parking space (APS) datasets. To distinguish outlier features from the APS’s overall periodic tendency, and to simultaneously identify the two types of outliers which naturally exist in APS datasets with intrinsically distinct statistical features, a two-phase detection method is proposed whereby an improved density-based detection algorithm named “local entropy based weighted outlier detection” (EWOD) is also incorporated. Real-world data from parking facilities in the City of Newcastle upon Tyne was used to test the hypothesis. Thereafter, experimental tests were carried out for a comparative study in which the outlier detection performances of the two-phase detection method, statistic-based method, and traditional density-based method were compared and contrasted. The results showed that the proposed method can identify two different kinds of outliers simultaneously and can give a high identifying accuracy of 100% and 92.7% for the first and second types of outliers, respectively

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator–prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy-deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate-only model shows that only 11.64% (17,190 km2) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km2 (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate-only model. It is predicted that future climate may alter the predator–prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards – a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future

Square-lattice s=1/2 XY model and the Jordan-Wigner fermions: The ground-state and thermodynamic properties

Using the 2D Jordan-Wigner transformation we reformulate the square-lattice s=1/2 XY (XZ) model in terms of noninteracting spinless fermions and examine the ground-state and thermodynamic properties of this spin system. We consider the model with two types of anisotropy: the spatial anisotropy interpolating between 2D and 1D lattices and the anisotropy of the exchange interaction interpolating between isotropic XY and Ising interactions. We compare the obtained (approximate) results with exact ones (1D limit, square-lattice Ising model) and other approximate ones (linear spin-wave theory and exact diagonalization data for finite lattices of up to N=36 sites supplemented by finite-size scaling). We discuss the ground-state and thermodynamic properties in dependence on the spatial and exchange interaction anisotropies. We pay special attention to the quantum phase transition driven by the exchange interaction anisotropy as well as to the appearance/disappearance of the zero-temperature magnetization in the quasi-1D limit.Comment: 28 pages, 7 figures include

RBPJ Mutations Identified in Two Families Affected by Adams-Oliver Syndrome

Through exome resequencing, we identified two unique mutations in recombination signal binding protein for immunoglobulin kappa J (RBPJ) in two independent families affected by Adams-Oliver syndrome (AOS), a rare multiple-malformation disorder consisting primarily of aplasia cutis congenita of the vertex scalp and transverse terminal limb defects. These identified mutations link RBPJ, the primary transcriptional regulator for the Notch pathway, with AOS, a human genetic disorder. Functional assays confirmed impaired DNA binding of mutated RBPJ, placing it among other notch-pathway proteins altered in human genetic syndromes

Decreasing brown bear (Ursus arctos) habitat due to climate change in Central Asia and the Asian Highlands

Around the world, climate change has impacted many species. In this study, we used bioclimatic variables and biophysical layers of Central Asia and the Asian Highlands combined with presence data of brown bear (Ursus arctos) to understand their current distribution and predict their future distribution under the current rate of climate change. Our bioclimatic model showed that the current suitable habitat of brown bear encompasses 3,430,493 km2 in the study area, the majority of which (>65%) located in China. Our analyses demonstrated that suitable habitat will be reduced by 11% (378,861.30 km2) across Central Asia and the Asian Highlands by 2,050 due to climate change, predominantly (>90%) due to the changes in temperature and precipitation. The spatially averaged mean annual temperature of brown bear habitat is currently −1.2°C and predicted to increase to 1.6°C by 2,050. Mean annual precipitation in brown bear habitats is predicted to increase by 13% (from 406 to 459 mm) by 2,050. Such changes in two critical climatic variables may significantly affect the brown bear distribution, ethological repertoires, and physiological processes, which may increase their risk of extirpation in some areas. Approximately 32% (1,124,330 km2) of the total suitable habitat falls within protected areas, which was predicted to reduce to 1,103,912 km2 (1.8% loss) by 2,050. Future loss of suitable habitats inside the protected areas may force brown bears to move outside the protected areas thereby increasing their risk of mortality. Therefore, more protected areas should be established in the suitable brown bear habitats in future to sustain populations in this region. Furthermore, development of corridors is needed to connect habitats between protected areas of different countries in Central Asia. Such practices will facilitate climate migration and connectivity among populations and movement between and within countries

Exposición al SARS-CoV-2 y la percepción del riesgo de los trabajadores en entornos no sanitarios de Hong Kong, Nanjing y Wuhan: Un estudio cualitativo multisitio

Introducción: Understanding risk perception that hinges on health-protective behaviors is central to strategies for prevention. Aim: To classify the pattern of potential risk of worker exposure to SARS-CoV-2, and to assess association with risk perception among non-healthcare workers Methods: In a multi-site, qualitative study, we conducted individual in-depth interviews and mini focus group discussions with employees, managerial staff and self-employees from Hong Kong (n=87), Nanjing (n=60), and Wuhan (n=60) between June 2020 and March 2021. Audios were transcribed and categorized by themes following Grounded Theory approach. Results: We identified seven major types of potential risk exposure pattern by category of parameters. The risk perceptions decreased among Type A workers, working at fixed location in office, and no/little contacts with clients/customers, and increased among workers having the concern of asymptomatic characteristics of SAR-CoV-2, daily contact with large size of the unfamiliar crowds, unhygienic behaviors of clients/customers, and use of public transportation to commute to work. The notion that the sense of safety deriving from the implementation and adherence with safety measures despite stringency, and trust with the government was most frequently reported in Nanjing and Wuhan. Conclusion: Study examines COVID-19 risks and risk perceptions among non-healthcare workers in three cities. Variations in risk perceptions were found, influenced by factors such as work patterns and safety measures. Trust in government and concerns about international contacts were common themes. The findings emphasize the need for targeted interventions, mental health support, and inclusive policies to address occupational health disparities and promote workplace safety.Introducción: Comprender la percepción del riesgo que condiciona conductas de protección de la salud es fundamental para la prevención. Objetivo: Clasificar el patrón del riesgo de exposición de los trabajadores al SRAS-CoV-2 y su asociación con la percepción del riesgo entre los trabajadores no sanitarios. Métodos: Estudio cualitativo multisitio. Realizamos entrevistas en profundidad y minigrupos de discusión con empleados, personal directivo y autoempleados de Hong Kong (n=87), Nanjing (n=60) y Wuhan (n=60) -junio 2020-marzo 2021-. Los audios se transcribieron y clasificaron por temas con enfoque de la teoría fundamentada. Resultados: Se identificaron siete tipos de patrón de exposición (Tipo A-G) al riesgo potencial. Las percepciones de riesgo disminuyeron entre trabajadores de tipo A que trabajaban en oficina y sin contacto con clientes y aumentaron entre trabajadores preocupados por características asintomáticas del SAR-CoV-2, contacto diario con multitudes, comportamientos antihigiénicos de clientes y uso de transporte público para ir al trabajo. La sensación de seguridad por aplicación y cumplimiento de medidas de seguridad y la confianza en el gobierno fue más frecuente en Nanjing y Wuhan. Conclusiones: Se hallaron variaciones en las percepciones del riesgo, influidas por factores como pautas de trabajo y medidas de seguridad. Fueron comunes la confianza en el gobierno y la preocupación por los contactos internacionales. Se requieren intervenciones específicas, apoyo a la salud mental y políticas integradoras para abordar las disparidades en salud laboral y promover la seguridad en el lugar de trabajo

Should older people be considered a homogeneous group when interacting with level 3 automated vehicles?

Exploring the future mobility of older people is imperative for maintaining wellbeing and quality of life in an ageing society. The forthcoming level 3 automated vehicle may potentially benefit older people. In a level 3 automated vehicle, the driver can be completely disengaged from driving while, under some circumstances, being expected to take over the control occasionally. Existing research into older people and level 3 automated vehicles considers older people to be a homogeneous group, but it is not clear if different sub-groups of old people have different performance and perceptions when interacting with automated vehicles. To fill this research gap, a driving simulator investigation was conducted. We adopted a between-subjects experimental design with subgroup of old age as the independent variable. The differences in performance, behaviour, and perception towards level 3 automated vehicles between the younger old group (60–69 years old) and older old group (70 years old and over) was investigated. 15 subjects from the younger old group (mean age = 64.87 years, SD = 3.46 years) and 24 from the older old group (mean age = 75.13 years, SD = 3.35 years) participated in the study. The findings indicate that older people should not be regarded as a homogeneous group when interacting with automated vehicle. Compared to the younger old people, the older old people took over the control of the vehicle more slowly, and their takeover was less stable and more critical. However, both groups exhibited positive perceptions towards level 3 automation, and the of older old people’s perceptions were significantly more positive. This study demonstrated the importance of recognising older people as a heterogeneous group in terms of their performance, capabilities, needs and requirements when interacting with automated vehicles. This may have implications in the design of such systems and also understanding the market for autonomous mobility