Miracle-dz/UniFAR-FTUs huggingface dataset:
SweepLoc

Indoor localization based on visual landmarks has received much attention in commercial sites with rich features (e.g., shopping malls, museums) recently because landmarks are relatively stable over a long time. Prior arts often require a user to take multiple independent images around his/her location, and manually confirm shortlisted landmarks. The process is sophisticated, inconvenient, slow, unnatural and error-prone. To overcome these limitations, we propose SweepLoc, a novel, efficient and automatic video-based indoor localization system. SweepLoc mimics our natural scanning around to identify nearby landmarks in an unfamiliar site to localize. In SweepLoc, a user simply takes a short video clip (about 6 to 8 seconds) of his/her surroundings by sweeping the camera. Using correlation and scene continuity between successive video frames, it automatically and efficiently selects key frames (where potential landmarks are centered) and subsequently reduces the decision error on landmarks. With identified landmarks, SweepLoc formulates an optimization problem to locate the user, taking compass noise and floor map constraint into account. We have implemented SweepLoc in Android platform. Our extensive experimental results in a food plaza and a premium mall demonstrate that SweepLoc is fast (less than 1 second to localize), and achieves substantially better accuracy as compared with the state-of-the-art approaches (reducing the localization error by 30%).
Palm vein recognition using a high dynamic range approach

In this study, the authors propose a novel approach for palm vein recognition relying on high dynamic range (HDR) imaging. Specifically, the authors speculate that the exploitation of multiple-exposure vein images guarantees better recognition performance than a baseline system relying on single-exposure acquisitions. To verify the authors' assumptions, a multiple-exposure dataset is collected from 86 subjects, with 12 sets of palm vein images captured for each user. Each set is composed of five images, acquired at different exposures, which can be fused to generate a HDR representation of the actual vein pattern. Local binary pattern and local derivative pattern are employed to extract features from single-exposure images, raw HDR images, and tone-mapped HDR images. The obtained experimental results show that significant performance improvement can be achieved when discriminative features are extracted from HDR contents, with respect to the use of single-exposure images.
Modulatory multiplicity in the functional repertoire of the feeding mechanism in cichlid fishes. I. Piscivores

Among piscivorous cichlids consistent differences have been recorded between ambush and pursuit hunters with respect to electromyographic, kinematic, pressure and behavioral profiles during prey capture by high speed inertial suction. Piscivorous cichlids possess a repertoire of at least two patterns of prey capture, each of which is characterized by an extreme regularity of the kinematic, pressure, electromyographic and behavioral profiles. The nature and locomotory behavior of the prey, visually analyzed by the predator during the prestrike stalk, determine which of the two preprogrammed patterns is recruited. Agile and elusive prey invariably will elicit a preprogrammed motor output (stereotyped motor pattern) that produces the greatest suction velocities in both ambush and pursuit hunters. The greater the kinematic and suction velocities, the greater the overlap of the firing sequences of antagonistic muscle complexes. The opercular and branchiostegal apparati function as an exceedingly effective anti‐backwash device, damping potential fluid oscillations within the oropharynx. Mastication occurs by triphasic movements and actions of muscles of the upper and lower pharyngeal jaws in both ambush and pursuit hunters. The lower pharyngeal jaw is acted upon by a force couple of which the fourth levator externus on one hand and the pharyngocleithralis externus and pharyngohyoideus on the other hand are the antagonistic components. Furthermore, the lower pharyngeal jaw is suspended by a muscular sling, the tension of which can be modified continuously. It is postulated that the switch from insectivorous to piscivorous feeding regimes (and perhaps vice versa) is accomplished by very minor structural and functional modifications, because the modulatory multiplicity and total range of repertories of the feeding machinery of the two trophic groups overlap significantly. Piscivorous cichlids may not have arisen by orthoselection in gradually‐changing lineages, but represent the differential success of subsets from a random pool of speciation events. Adaptive features identified as characteristic for piscivory could have evolved in multiple and independent lineages at a punctuational mode and tempo.
Neutral or Negative?: Sentiment Evaluation in Reviews of Hosting Services

Sharing economy represents activities between people to obtain, provide, or share access to goods and services, coordinated by online services. Airbnb and Couchsurfing are examples of sharing economy, where users offer hosting service in their own houses to the public. In both services, guests can review accommodations. In hosting services of the sharing economy, there is personal contact between those who offer and contract the accommodation, which can affect users' decision to make negative reviews. This is because negative reviews can damage the offered services. To evaluate this issue, we collected reviews from two sharing economy platforms, Airbnb and Couchsurfing, and from one platform of the formal economy that works mostly with hotels, Booking.com, for some cities in the United States and Brazil. We performed a sentiment analysis in the shared texts and found that reviews in the sharing economy tend to be more favorable than those in the formal economy. This can represent a problem in those systems, as an experiment with volunteers performed in this study suggests. In addition, we present some of the main features of these comments, as well as a proposal on how to exploit the results obtained.
Persona: A Method for Facial Analysis in Video and Application in Entertainment

This article proposes the Persona method. The goal of the prosposed method is to learn and classify the facial actions of actors in video sequences. Persona is based on standard action units. We use a database with main expressions mapped and pre-classified that allows the automatic learning and faces selection. The learning stage uses Support Vector Machine (SVM) classifiers to identify expressions from a set of feature points tracked in the input video. After that, labeled control 3D masks are built for each selected action unit or expression, which composes the Persona structure. The proposed method is almost automatic (little intervention is needed) and does not require markers on the actor’s face or motion capture devices. Many applications are possible based on the Persona structure such as expression recognition, customized avatar deformation, and mood analysis, as discussed in this article.
A new multimodal deep-learning model to video scene segmentation

The recent development of deep learning techniques, like convolutional networks, shed a new light over the video (story) scene segmentation problem, bringing the potential to outperform state-of-the-art non-deep learning multimodal approaches. However, one important aspect of the multimodality still needs investigation in the context of deep learning: the multimodal fusion. Often, features are directly fed to a network, which may be an inadequate approach to perform the underlying multimodal fusion. This paper presents an evaluation of early and late approaches to deep learning multimodal fusion. In addition, it proposes a new deep learning model to perform video scene segmentation, based on convolutional network feature extraction capabilities and a recurrent neural network architecture. The results show the early versus late fusion discussion is reopened regarding deep learning. Moreover, the results prove the proposed model is competitive against state-of-the-art techniques when evaluated over a public documentary video dataset obtaining up to 64 of average FCO, while also maintaining a lower computational cost when compared with a related convolutional approach.
Incorporating Semantic Item Representations to Soften the Cold Start Problem

Recommender systems have been extensively used to provide meaningful and personalized content to users. A recurring issue, especially in collaborative filtering methods, is the cold-start problem, which can be related to new items or new users. This problem can be smoothed by aggregating item information into the recommender calculation, thus the semantics behind these items representations are important. In this paper, we propose four rich item representations, based on three kinds of semantics: sentiment analysis, sense embeddings and similarities. The items' features are disambiguated concepts extracted from textual users' reviews, which are known for possessing a great information load with both item descriptions and user preferences. We apply these four representations in two classic collaborative filtering algorithms, which were adapted to be attribute aware. We compare our approach against the original recommenders, and evaluate our results in two very different datasets to show the generality of our approach. Results show a very positive influence of the item representations to reduce prediction error.
Conductively coupled flexible silicon electronic systems for chronic neural electrophysiology

Significance A critical challenge for flexible biomedical implants is in the development of materials and structures that enable intimate coupling to biotissues with long-term stability. The results presented here address this problem through a materials and integration strategy that combines highly doped silicon nanomembranes chemically bonded to thin films of thermal silicon dioxide in a construct that simultaneously serves as a biofluid barrier and a conductively coupled biointerface. Use of this approach with various flexible electronic systems, including passive and active electrodes for electrophysiological sensing and electrical stimulation, illustrate capabilities in high-fidelity operation. Systematic accelerated lifetime studies in artificial biofluids highlight the stability of these systems for chronic operation, without electrical leakage or other forms of degradation. Materials and structures that enable long-term, intimate coupling of flexible electronic devices to biological systems are critically important to the development of advanced biomedical implants for biological research and for clinical medicine. By comparison with simple interfaces based on arrays of passive electrodes, the active electronics in such systems provide powerful and sometimes essential levels of functionality; they also demand long-lived, perfect biofluid barriers to prevent corrosive degradation of the active materials and electrical damage to the adjacent tissues. Recent reports describe strategies that enable relevant capabilities in flexible electronic systems, but only for capacitively coupled interfaces. Here, we introduce schemes that exploit patterns of highly doped silicon nanomembranes chemically bonded to thin, thermally grown layers of SiO2 as leakage-free, chronically stable, conductively coupled interfaces. The results can naturally support high-performance, flexible silicon electronic systems capable of amplified sensing and active matrix multiplexing in biopotential recording and in stimulation via Faradaic charge injection. Systematic in vitro studies highlight key considerations in the materials science and the electrical designs for high-fidelity, chronic operation. The results provide a versatile route to biointegrated forms of flexible electronics that can incorporate the most advanced silicon device technologies with broad applications in electrical interfaces to the brain and to other organ systems.
The association of diabetes-related self-care activities with perceived stress, anxiety, and fatigue: a cross-sectional study

Purpose Many people with type 2 diabetes (T2DM) do not sustain sufficient diabetes-related self-care activities (DRSCA) in their daily lives. To provide additional information about the positive influence of DRSCA, this study was conducted to examine whether DRSCA were associated with reduced perceived stress, anxiety, and fatigue among people with T2DM and to explore the level of DRSCA, perceived stress, anxiety, and fatigue and their association with background information. Patients and methods This study was a cross-sectional survey including 251 participants aged 18 years and older recruited from two hospitals in the eastern part of China. The study utilized self-report questionnaires that consisted of background information, DRSCA, perceived stress, anxiety, and fatigue. Hierarchical multiple regression analysis was conducted to explore the association of DRSCA with perceived stress, anxiety, and fatigue while adjusting for background information. Results The results indicated that the level of self-care activities, stress, and fatigue was around middle level. The prevalence of anxiety was 19%. A high level of DRSCA was likely to reduce perceived stress but was not linked to anxiety and fatigue. Women were more susceptible to stress and anxiety, and people who had diabetes for >5 years were more likely to have anxiety. The background information included diabetes duration, standardized diabetes education, and high social support, all of which are factors that may influence DRSCA. Conclusion The findings suggest that improving the level of DRSCA might effectively reduce perceived stress. The potential benefits of DRSCA can provide both motivational and evaluative data for self-care programs. In addition, the findings show that DRSCA were not linked to anxiety and fatigue, which implies that their positive influence on anxiety and fatigue may be offset by the load of frequent DRSCA. It is suggested that helping patients to make tailored plans to integrate DRSCA into their daily lives is needed. Meanwhile, in the background information, it is suggested that standardized diabetes education and high social support can benefit DRSCA; in improving psychological health, more attention should be paid to women and patients with diabetes duration <5 years.
Rhine: FRP with type-level clocks

Processing data at different rates is generally a hard problem in reactive programming. Buffering problems, lags, and concurrency issues often occur. Many of these problems are clock errors, where data at different rates is combined incorrectly. Techniques to avoid clock errors, such as type-level clocks and deterministic scheduling, exist in the field of synchronous programming, but are not implemented in general-purpose languages like Haskell. Rhine is a clock-safe library for synchronous and asynchronous Functional Reactive Programming (FRP). It separates the aspects of clocking, scheduling and resampling from each other, and ensures clock-safety at the type level. Concurrent communication is encapsulated safely. Diverse reactive subsystems can be combined in a coherent, declarative data-flow framework, while correct interoperability of data at different rates is guaranteed by type-level clocks. This provides a general-purpose framework that simplifies multi-rate FRP systems and can be used for game development, media applications, GUIs and embedded systems, through a flexible API with many reusable components.
A MPK3/6-WRKY33-ALD1-Pipecolic Acid Regulatory Loop Contributes to Systemic Acquired Resistance[OPEN]

A positive feedback loop consisting of MPK3/6, WRKY33, ALD1, and pipecolic acid regulates local immune amplification contributing to systemic acquired resistance in Arabidopsis thaliana. Plants induce systemic acquired resistance (SAR) upon localized exposure to pathogens. Pipecolic acid (Pip) production via AGD2-LIKE DEFENSE RESPONSE PROTEIN1 (ALD1) is key for SAR establishment. Here, we report a positive feedback loop important for SAR induction in Arabidopsis thaliana. We showed that local activation of the MAP kinases MPK3 and MPK6 is sufficient to trigger Pip production and mount SAR. Consistent with this, mutations in MPK3 or MPK6 led to compromised Pip accumulation upon inoculation with the bacterial pathogen Pseudomonas syringae pv tomato DC3000 (Pto) AvrRpt2, which triggers strong sustained MAPK activation. By contrast, P. syringae pv maculicola and Pto, which induce transient MAPK activation, trigger Pip biosynthesis and SAR independently of MPK3/6. ALD1 expression, Pip accumulation, and SAR were compromised in mutants defective in the MPK3/6-regulated transcription factor WRKY33. Chromatin immunoprecipitation showed that WRKY33 binds to the ALD1 promoter. We found that Pip triggers activation of MPK3 and MPK6 and that MAPK activation after Pto AvrRpt2 inoculation is compromised in wrky33 and ald1 mutants. Collectively, our results reveal a positive regulatory loop consisting of MPK3/MPK6, WRKY33, ALD1, and Pip in SAR induction and suggest the existence of distinct SAR activation pathways that converge at the level of Pip biosynthesis.
Epicardial ventricular tachycardia in ischemic cardiomyopathy: Prevalence, electrophysiological characteristics, and long‐term ablation outcomes

The characteristics of the epicardial (EPI) substrate responsible for ventricular tachycardia (VT) in ischemic cardiomyopathy (ICM) are undefined, and data on the long‐term outcomes of EPI catheter ablation limited. We evaluated the prevalence, electrophysiologic features, and outcomes of catheter ablation of EPI VT in ICM.
Spillage of bacterial products during colon surgery increases the risk of liver metastases development in a rat colon carcinoma model.

ABSTRACT Surgical resection of the primary tumor provides the best chance of cure for patients with colorectal carcinoma (CRC). However, bacterial translocation during intestinal surgery has been correlated with poor long-term oncological outcome. Therefore, we investigated the influence of bacterial contamination during colon surgery on CRC liver metastases development. Blood and liver samples of patients undergoing resection of primary CRC or liver metastases were collected. Cell numbers, activation markers and inflammatory mediators were determined. Tumor cell adhesion and outgrowth after sham- or colectomy operations were determined in a rat model, in which tumor cells had been injected into the portal vein. White blood cells and granulocytes were increased in per- and post-operative patient blood samples. IL-6 was also increased post-operatively compared to the preoperative level. Expression of NOX-2, NOX-4 and polymorphonuclear cells (PMNs) numbers were elevated in post-operative human liver samples. In vitro stimulation of macrophages with plasma of rats after colectomy resulted in production of reactive oxygen species (ROS). Colectomy in rats increased D-lactate levels in plasma, supporting bacterial translocation. Decreased expression of tight junction molecules and increased tumor cell adhesion and outgrowth was observed. Treatment with a selective decontamination of the digestive tract (SDD) cocktail decreased tumor cell adherence after colectomy. In conclusion, postoperative bacterial translocation may activate liver macrophages and PMNs, resulting in ROS production. As we previously showed that ROS release led to liver vasculature damage, circulating tumor cells may adhere to exposed extracellular matrix and grow out into liver metastases. This knowledge is pivotal for development of therapeutic strategies to prevent surgery-induced liver metastases development.
Shifting Diatom—Dinoflagellate Dominance During Spring Bloom in the Baltic Sea and its Potential Effects on Biogeochemical Cycling

The Baltic Sea is affected by a range of human induced environmental pressures such as eutrophication. Here we synthesize the ongoing shift from diatom dominance towards more dinoflagellates in parts of the Baltic Sea during the spring bloom and its potential effects on biogeochemical cycling of key elements (e.g. C, N and P). The spring bloom is the period with the highest annual primary production and sinking of organic matter to the sediment. The fate of this organic matter is a key driver for material fluxes, affecting ecosystem functioning and eutrophication feedback loops. The dominant diatoms and dinoflagellates appear to be functionally surrogates as both groups are able to effectively exhaust the wintertime accumulation of inorganic nutrients and produce bloom level biomass that contribute to vertical export of organic matter. However, the groups have very different sedimentation patterns, and the sea floor has variable potential to mineralize the settled biomass in the different sub-basins. While diatoms sink quickly out of the euphotic zone, dinoflagellates sink as inert resting cysts, or lyse in the water column contributing to slowly settling phyto-detritus. The dominance by either phytoplankton group thus directly affects both the summertime nutrient pools of the water column and the input of organic matter to the sediment but to contrasting directions. The proliferation of dinoflagellates with high encystment efficiency could increase sediment retention and burial of organic matter, alleviating the eutrophication problem and improve the environmental status of the Baltic Sea.
Attribute Representation for Human Activity Recognition of Manual Order Picking Activities

Semantic descriptions or attribute representations have been used successfully for object and scene recognition, and for word-spotting. However, these representations have not been explored deeply on human activity recognition (HAR). Particularly, in the manual order picking process, attribute representations are beneficial for dealing with the versatility of activities in the process. This paper compares the performance of deep architectures trained using different attribute representations for HAR. Besides, it evaluates their quality from the perspective of practical application.
Network-Based Procedural Story Generation

Procedural story generation has become an important research area due to its attractiveness to computer entertainment applications. Several approaches have been proposed to create procedural stories for games based mainly on logic programming and decision trees. These approaches use a set of possible events that are executed based on how the player interacts with the story. However, these approaches commonly use a fixed set of characters with predefined relationships. In contrast, in this article, we propose an approach that creates dynamic stories based on two networks: a handcrafted event network and a dynamic artificial social network created for each new story. This allows each story to have its own set of characters with a unique relationship network, resulting in an even wider range of possible stories. We demonstrate this with some examples and discuss how this approach can be implemented for interactive computer entertainment systems, such as video games.