Typographic attacks are often attributed to the ability of multimodal pre-trained models to fuse textual semantics into visual representations, yet the mechanisms and locus of such interference remain unclear. We examine whether such models genuinely encode textual semantics or primarily rely on texture-based visual features. To disentangle orthographic form from meaning, we introduce the ToT dataset, which includes controlled word pairs that either share semantics with distinct appearances (synonyms) or share appearance with differing semantics (paronyms). A layer-wise analysis of Intrinsic Dimension (ID) reveals that early layers exhibit competing dynamics between orthographic and semantic representations. In later layers, semantic accuracy increases as ID decreases, but this improvement largely stems from orthographic disambiguation. Notably, clear semantic differentiation emerges only in the final block, challenging the common assumption that semantic understanding is progressively constructed across depth. These findings reveal how current vision-language models construct text representations through texture-dependent processes, prompting a reconsideration of the gap between visual perception and semantic understanding. The code is available at: https://github.com/Ovsia/Textural-or-Textual

This paper introduces the ZenStem, an interactive prototype that facilitates meditation by visually guiding a user’s breathing pattern. The ZenStem links users’ breathing and heart rate to the irrigation of an indoor plant, as it will water the plant so long as the user can maintain a meditative state. Upon feedback from a pulse-sensing armband that the user’s heart rate has risen, it will initialize its light-based breathing guide to help the user re-enter their meditative state. We describe the ideation and prototyping process of the ZenStem, followed by the initial impressions gained from pilot evaluations with potential users. Based on impressions pertaining to the appearance and functionality of the ZenStem, we end by proposing future research directions and design suggestions.

Voice messages, by nature, prevent users from gauging the emotional tone without fully diving into the audio content. This hinders the shared emotional experience at the pre-retrieval stage. Research scarcely explored “Emotional Teasers”—pre-retrieval cues offering a glimpse into an awaiting message’s emotional tone without disclosing its content. We introduce EmoWear, a smartwatch voice messaging system enabling users to apply 30 animation teasers on message bubbles to reflect emotions. EmoWear eases senders’ choice by prioritizing emotions based on semantic and acoustic processing. EmoWear was evaluated in comparison with a mirroring system using color-coded message bubbles as emotional cues (N=24). Results showed EmoWear significantly enhanced emotional communication experience in both receiving and sending messages. The animated teasers were considered intuitive and valued for diverse expressions. Desirable interaction qualities and practical implications are distilled for future design. We thereby contribute both a novel system and empirical knowledge concerning emotional teasers for voice messaging.

The intrinsic dimension (ID) represents the minimum dimension needed to describe data on a lower-dimensional manifold within high-dimensional spaces. Network pruning aims to reduce the complexity of high-dimensional networks while minimizing performance trade-offs. This symmetry motivates the exploration of ID as a metric for effective pruning. For vision-language models, we investigate whether different modalities exist on separate manifolds, indicating varying complexity and prunability. We empirically study ID variations in large-scale vision-language pre-trained models and examine the contributions of different modalities to model prunability. We propose a layer importance metric based on ID, which can conveniently integrate with current metrics and enhance performance in vision-language model pruning. The experimental results show a high correlation between ID and modality prunability. Visual representations are more sensitive and crucial to model performance, while language representations are more robust and offer greater prunability. Our findings suggest an asymmetric pruning strategy for vision and language modalities, guided by the ID metric. The code is available at https://github.com/Nofear18/ID_VL_Pruning

There are three characteristics for ecosystem services, zonal characteristics, complexity and conventional civilization, which affect ecological valuation directly. Considering regional environment and anthropogenic influence, grassland's ecosystem services in Gansu Province are concluded 11 types, including gas regulation, climate regulation, disturbance regulation, wind erosion control and sand fixture, water resource provision, soil erosion control, waste treatment, gene resistance, food production, raw materials, recreation and culture. Landsat TM data are collected for manual photointerpretation. The grassland type distribution map is obtained. In this paper, we use stockbreeding income as benchmark, the other ecosystem services values which do not enter market to exchange are decided by experts questionary in this field. The relative weights can help to calculate the non-market ecological service value. The results' spatial distribution are displayed and analyzed by using Geographic Information Systems software. The results indicate: the total Gansu province grassland ecosystem value reaches 283.67times108yuan (RMB) in 1980s. The grassland in the low zone along Hexi corridor and Longnan have the highest ecosystem service value, the grassland in Gannan take second place, and the western of Qingyang and counties around Lanzhou take third place, the other places value in the province are low. The Gansu Province is a severe erosion region in arid and semiarid area, therefore wind erosion control and sand fixture, soil erosion control are the most valuable services.

Precision agriculture needs a mass of data, therefore data availability is a vital obstacle factor for precision agriculture technology widely use. The methods of acquisition data for precision agriculture change from field survey to sensor acquisition gradually. Remote Sensing plays an important role in the large-scale, real-time, multi-spectral data acquisition. But there are still some problems when Remote Sensing data are applied in the actual farm production and management, which result in that precision agriculture's advantages are limited, so finding the solution of data acquisition for precision agriculture based on remote sensing becomes very necessary. In this paper, the NPP, NDVI, LAI etc are retrieved from remote sensing data, the field investigation data are also obtained. We set up a decision-making system based on CNCS (central neural control system), which is composed of several module such as data updating, data editing, decision-making supporting. The system is made for the farmers to decide cultivation strategies on when, where and how much irrigation, fertilizer and pesticide should be applied on each plot.

Precision agriculture needs a mass of data whose availability is an important factor of spreading PA technology. The methods of acquisition data of precision agriculture are developmental from truth-surveying to sensor. Remote Sensing can provide an important and convenient method for acquisition data of precision agriculture. There are some obstacles in the aspect of data of precision agriculture based on Remote Sensing, which result that precision agriculture can not apply widely in the agriculture, so the researches of the acquisition data of precision agriculture based on Remote Sensing became more necessary. This paper obtains data of precision agriculture through distilling NPP, NDVI, LAI etc indices, and refers to land truth, construct models of management decision-making support system, which can provide how, when, where to use precision agriculture technologies, and help end user to make schemes of irrigation, fertilizer, spray pesticide. We make a program, which provide function of data update, data edits, data issue, management decision-making support etc. It is a way to providing data of precision agriculture quickly to end user.

Having not considered such aspects as spatial distribution features of transportation networks and resident areas, the spatial influence of outside transportation modes on the features within the research regions as well as the different transit capacity of different transportation ways, the conventional measuring methods based on path analysis and network analysis are deficient to the description of regional transportation situation. With the employment and optimization of the connectivity and accessibility of the network nodes to evaluate transportation network, this study successfully breaks through the limitation of the border of investigative area and, different transportation modes can also be taken into account. Based on the gradually increased correlation coefficient between the connectivity change, which is a gradually increased process from direct connections to indirect multi-steps connections, and the development of regional economy, this paper proposes economy-network diameter index (ENDI), which is employed to evaluate the development of network and the contribution to regional economy of Gansu Province, China with the data of 2002 transportation network and the economic statistics in the Statistical Yearbook. By above methods, this empirical study comes to the following conclusions: 1) interregional transportation contributes more to the development of regional economic than that of the adjoining transportation; and 2) these indices can be used to designate spatial interactional scopes of regional economy, and accordingly to provide powerful and scientific supports for the planning of regional transportation and economy; and 3) the accessibility figure of network nodes shows that transportation of Gansu Province takes on a phenomenon of high cluster and spatial autocorrelation; and 4) ENDI can also be used to create spatial weight matrix of spatial progress. As calculation of these indices is laborious, several efficient computational methods are developed.