Moments of rotary motion : temporary use in vacant industrial heritage architecture

The vacant industrial historic building at 145 Globe Street within the Jewelry District in Providence, Rhode Island is designated one of the ten most endangered historic properties in the city. After surviving many stalled plans for renovation there are no efforts underway to save it, and deterioration from natural elements and vandalism continues. Many Industrial heritage buildings wait in a similar limbo. When there are no definite plans for renewal, often these buildings are left vacant for years without routine maintenance, causing severe damage and posing a threat to public safety. These buildings should be used as a resource in urban planning, rather than a problem, as they adjust well to swiftly changing occupancy. Contemporary society is in constant flux. Architecture should break the traditional fixed pattern toward a perpetual malleability to adapt to the transition of functions quickly. Compared with other architectural typologies, industrial historical buildings generally have more open and organized spatial conditions. It is necessary to develop a system of flexible architecture within historic industry structures to support temporary use, which provides an active transitional construction by adaptive reuse of industry landmark buildings in the urban regeneration. By applying reversible materials, temporary-use spaces will be quickly built and moveable to suit different programs and functions. The flexibility in the reuse of industrial heritage buildings will make more public the architectural heritage in the city, to accommodate different purposes of use and promote the city’s positive development. At the host building at 145 Globe Street, temporary use will promote a creative art therapy community center, by applying a flexible spatial transformation system based on multifunction, with the intention of changing the original severe manufacturing spatial pattern into one of accessibility, healing & community. Its flexible presentation will bring new vitality and development opportunities to the historic district and city as a whole

Accurate and lightweight dehazing via multi-receptive-field non-local network and novel contrastive regularization

Recently, deep learning-based methods have dominated image dehazing domain. Although very competitive dehazing performance has been achieved with sophisticated models, effective solutions for extracting useful features are still under-explored. In addition, non-local network, which has made a breakthrough in many vision tasks, has not been appropriately applied to image dehazing. Thus, a multi-receptive-field non-local network (MRFNLN) consisting of the multi-stream feature attention block (MSFAB) and cross non-local block (CNLB) is presented in this paper. We start with extracting richer features for dehazing. Specifically, we design a multi-stream feature extraction (MSFE) sub-block, which contains three parallel convolutions with different receptive fields (i.e., $1\times 1$, $3\times 3$, $5\times 5$) for extracting multi-scale features. Following MSFE, we employ an attention sub-block to make the model adaptively focus on important channels/regions. The MSFE and attention sub-blocks constitute our MSFAB. Then, we design a cross non-local block (CNLB), which can capture long-range dependencies beyond the query. Instead of the same input source of query branch, the key and value branches are enhanced by fusing more preceding features. CNLB is computation-friendly by leveraging a spatial pyramid down-sampling (SPDS) strategy to reduce the computation and memory consumption without sacrificing the performance. Last but not least, a novel detail-focused contrastive regularization (DFCR) is presented by emphasizing the low-level details and ignoring the high-level semantic information in the representation space. Comprehensive experimental results demonstrate that the proposed MRFNLN model outperforms recent state-of-the-art dehazing methods with less than 1.5 Million parameters.Comment: submitted to IEEE TCYB for possible publicatio

Prompt-based test-time real image dehazing: a novel pipeline

Existing methods attempt to improve models' generalization ability on real-world hazy images by exploring well-designed training schemes (e.g., CycleGAN, prior loss). However, most of them need very complicated training procedures to achieve satisfactory results. In this work, we present a totally novel testing pipeline called Prompt-based Test-Time Dehazing (PTTD) to help generate visually pleasing results of real-captured hazy images during the inference phase. We experimentally find that given a dehazing model trained on synthetic data, by fine-tuning the statistics (i.e., mean and standard deviation) of encoding features, PTTD is able to narrow the domain gap, boosting the performance of real image dehazing. Accordingly, we first apply a prompt generation module (PGM) to generate a visual prompt, which is the source of appropriate statistical perturbations for mean and standard deviation. And then, we employ the feature adaptation module (FAM) into the existing dehazing models for adjusting the original statistics with the guidance of the generated prompt. Note that, PTTD is model-agnostic and can be equipped with various state-of-the-art dehazing models trained on synthetic hazy-clean pairs. Extensive experimental results demonstrate that our PTTD is flexible meanwhile achieves superior performance against state-of-the-art dehazing methods in real-world scenarios. The source code of our PTTD will be made available at https://github.com/cecret3350/PTTD-Dehazing.Comment: update github link (https://github.com/cecret3350/PTTD-Dehazing

Flexible Superwettable Tapes for On-Site Detection of Heavy Metals

Bioinspired superwettable micropatterns that combine superhydrophobicity and superhydrophilicity have been proved to exhibit outstanding capacity in controlling and patterning microdroplets and possessed new functionalities and possibilities in emerging sensing applications. Here, we introduce a flexible tape-based superhydrophilic–superhydrophobic tape toward on-site heavy metals monitoring. On such a superwettable tape, capillarity-assisted superhydrophilic microwells allow directly anchoring indicators in fixed locations and sampling into a test zone via simple dip-pull from an origin specimen solution. In contrast, the superhydrophobic substrate could confine the microdroplets in the superhydrophilic microwells for reducing the amount of analytical solution. The tape-based microchip also displays excellent flexibility against stretching, bending, and torquing for expanding wearable and portable sensing devices. Qualitative and quantitative colorimetric assessments of multiplex heavy metal analyses (chromium, copper, and nickel) by the naked eye are also achieved. The superwettable tape-based platforms with a facile operation mode and accessible signal read-out represent unrevealed potential for on-site environmental monitoring

eMotions: A Large-Scale Dataset for Emotion Recognition in Short Videos

Nowadays, short videos (SVs) are essential to information acquisition and sharing in our life. The prevailing use of SVs to spread emotions leads to the necessity of emotion recognition in SVs. Considering the lack of SVs emotion data, we introduce a large-scale dataset named eMotions, comprising 27,996 videos. Meanwhile, we alleviate the impact of subjectivities on labeling quality by emphasizing better personnel allocations and multi-stage annotations. In addition, we provide the category-balanced and test-oriented variants through targeted data sampling. Some commonly used videos (e.g., facial expressions and postures) have been well studied. However, it is still challenging to understand the emotions in SVs. Since the enhanced content diversity brings more distinct semantic gaps and difficulties in learning emotion-related features, and there exists information gaps caused by the emotion incompleteness under the prevalently audio-visual co-expressions. To tackle these problems, we present an end-to-end baseline method AV-CPNet that employs the video transformer to better learn semantically relevant representations. We further design the two-stage cross-modal fusion module to complementarily model the correlations of audio-visual features. The EP-CE Loss, incorporating three emotion polarities, is then applied to guide model optimization. Extensive experimental results on nine datasets verify the effectiveness of AV-CPNet. Datasets and code will be open on https://github.com/XuecWu/eMotions

Flexible Superwettable Tapes for On-Site Detection of Heavy Metals

Bioinspired superwettable micropatterns that combine superhydrophobicity and superhydrophilicity have been proved to exhibit outstanding capacity in controlling and patterning microdroplets and possessed new functionalities and possibilities in emerging sensing applications. Here, we introduce a flexible tape-based superhydrophilic–superhydrophobic tape toward on-site heavy metals monitoring. On such a superwettable tape, capillarity-assisted superhydrophilic microwells allow directly anchoring indicators in fixed locations and sampling into a test zone via simple dip-pull from an origin specimen solution. In contrast, the superhydrophobic substrate could confine the microdroplets in the superhydrophilic microwells for reducing the amount of analytical solution. The tape-based microchip also displays excellent flexibility against stretching, bending, and torquing for expanding wearable and portable sensing devices. Qualitative and quantitative colorimetric assessments of multiplex heavy metal analyses (chromium, copper, and nickel) by the naked eye are also achieved. The superwettable tape-based platforms with a facile operation mode and accessible signal read-out represent unrevealed potential for on-site environmental monitoring

Flexible and superwettable bands as a platform toward sweat sampling and sensing

Wearable biosensors as a user-friendly measurement platform have become a rapidly growing field of interests due to their possibility in integrating traditional medical diagnostics and healthcare management into miniature lab-on-body analytic devices. This paper demonstrates a flexible and skin-mounted band that combines superhydrophobic-superhydrophilic microarrays with nanodendritic colorimetric biosensors toward in situ sweat sampling and analysis. Particularly, on the superwettable bands, the superhydrophobic background could confine microdroplets into superhydrophilic microwells. On-body investigations further reveal that the secreted sweat is repelled by the superhydrophobic silica coating and precisely collected and sampled onto the superhydrophilic micropatterns with negligible lateral spreading, which provides an independent “vessel” toward cellphone-based sweat biodetection (pH, chloride, glucose and calcium). Such wearable, superwettable band-based biosensors with improved interface controllability could significantly enhance epidemical sweat sampling in well-defined sites, holding a great promise for facile and noninvasive biofluids analysis

Flexible and superwettable bands as a platform toward sweat sampling and sensing

Wearable biosensors as a user-friendly measurement platform have become a rapidly growing field of interests due to their possibility in integrating traditional medical diagnostics and healthcare management into miniature lab-on-body analytic devices. This paper demonstrates a flexible and skin-mounted band that combines superhydrophobic-superhydrophilic microarrays with nanodendritic colorimetric biosensors toward in situ sweat sampling and analysis. Particularly, on the superwettable bands, the superhydrophobic background could confine microdroplets into superhydrophilic microwells. On-body investigations further reveal that the secreted sweat is repelled by the superhydrophobic silica coating and precisely collected and sampled onto the superhydrophilic micropatterns with negligible lateral spreading, which provides an independent “vessel” toward cellphone-based sweat biodetection (pH, chloride, glucose and calcium). Such wearable, superwettable band-based biosensors with improved interface controllability could significantly enhance epidemical sweat sampling in well-defined sites, holding a great promise for facile and noninvasive biofluids analysis

Human Influenza A (H5N1) Cases, Urban Areas of People’s Republic of China, 2005–2006

We investigated potential sources of infection for 6 confirmed influenza A (H5N1) patients who resided in urban areas of People’s Republic of China. None had known exposure to sick poultry or poultry that died from illness, but all had visited wet poultry markets before illness