Miracle-dz/UniFAR-FTUs huggingface dataset:
FullBreathe

Human respiration detection based on Wi-Fi signals does not require users to carry any device, hence it has drawn a lot of attention due to better user acceptance and great potential for real-world deployment. However, recent studies show that respiration sensing performance varies in different locations due to the nature of Wi-Fi radio wave propagation in indoor environments, i.e., respiration detection may experience poor performance at certain locations which we call "blind spots". In this paper, we aim to address the blind spot problem to ensure full coverage of respiration detection. Basically, the amplitude and phase of Wi-Fi channel state information (CSI) are orthogonal and complementary to each other, so they can be combined to eliminate the blind spots. However, accurate CSI phase cannot be obtained from commodity Wi-Fi due to the clock-unsynchronized transceivers. Thus, we apply conjugate multiplication (CM) of CSI between two antennas to remove the phase offset and construct two orthogonal signals--new "amplitude and phase" which are still complementary to each other. In this way, we can ensure full human respiration detection. Based on these ideas, We design and implement a real-time respiration detection system with commodity Wi-Fi devices. We conduct extensive experiments to validate our model and design. The results show that, with only one transceiver pair and without leveraging multiple sub-carriers, our system enables full location coverage with no blind spot, showing great potential for real deployment.
The Recalculation of the Weights of Criteria in MCDM Methods Using the Bayes Approach

The application of multiple criteria decision-making methods (MCDM) is aimed at choosing the best alternative out of the number of available versions in the absence of the apparently dominant alternative. One of the two major components of multiple criteria decision-making methods is represented by the weights of the criteria describing the considered process. The weights of the criteria quantitatively express their significance and influence on the evaluation result. The criterion weights can be subjective, i.e., based on the estimates assigned by the experts, and the so-called objective, i.e., those which assess the structure of the data array at the time of evaluation. Several groups of experts, representing the opinions of various interested parties may take part in the evaluation of criteria. The evaluation data on the criterion weights also depend on the mathematical methods used for calculations and the estimation scales. In determining the objective weights, several methods, assessing various properties or characteristics of the data array’s structure, are usually employed. Therefore, the use of the procedures, improving the accuracy of the evaluation of the weights’ values and the integration of the obtained data into a single value, is often required. The present paper offers a new approach to more accurate evaluation of the criteria weights obtained by using various methods based on the idea of the Bayes hypothesis. The performed investigation shows that the suggested method is symmetrical and does not depend on the fact whether a priori or posterior values of the weights are recalculated. This result is the theoretical basis for practical use of the method of combining the weights obtained by various approaches as the geometric mean of various estimates. The ideas suggested by the authors have been repeatedly used in the investigation for combining the objective weights, for recalculating the criteria weights after obtaining the estimates of other groups of experts and for combining the subjective and the objective weights. The recalculated values of the weights of the criteria are used in the work for evaluating the quality of the distant courses taught to the students.
Temporary Techno-social Gatherings? A (hacked) discussion about open practices

This paper is rooted in an experimental inquiry of issue-oriented temporary techno-social gatherings or TTGs, which are typically referred to as hackathons, workshops or pop-ups and employ rapid design and development practices to tackle technical challenges while engaging with social issues. Based on a collaboration between three digital practitioners (a producer, a researcher and a designer), qualitative and creative data was gathered across five different kinds of TTG events in London and in Tartu which were held in partnership with large institutions, including Art:Work at Tate Exchange within Tate Modern, the Mozilla Festival at Ravensbourne College and the 2017 Association of Internet Researchers conference hosted in Tartu. By analysing data using an open and discursive approach manifested in both text and visual formats, we reflect on the dynamic and generative characteristics of TTG gatherings while also arriving at our own conclusions as situated researchers and practitioners who are ourselves engaged in increasingly messy webs where new worlds of theory and practice are built.
Influence of crop residues, matric potential and temperature on growth of Exserohilum turcicum an emerging maize pathogen in Argentina

Northern corn leaf blight (NCLB) caused by Exserohilum turcicum is an endemic foliar disease in the Argentinean maize production area. Before applying a control method, it is essential to focus on factors that lead to the survival and conservation of E. turcicum inoculum. However, there is little information about the life cycle of this emerging pathogen in our country. The objective of the present work was to analyse the growth ability of three E. turcicum isolates under different type and conditions of maize, wheat and soybean residues, matric potential, temperature and their interactions. Statistical analysis demonstrated a significant effect of three factors on growth rate: residues‐based media, matric potential and temperature. Among them the major effect was produced by matric potential followed by temperature. Although there were no significant differences in the growth rate among different residues types, the range of conditions in which growth occurred was different. According to these results, soybean residues would allow a better survival of E. turcicum inoculum under no‐tillage system and providing an inoculum source for maize infections in subsequent year.
Privacy With Estimation Guarantees

We study the central problem in data privacy: how to share data with an analyst while providing both privacy and utility guarantees to the user that owns the data. In this setting, we present an estimation-theoretic analysis of the privacy-utility trade-off (PUT). Here, an analyst is allowed to reconstruct (in a mean-squared error sense) certain functions of the data (utility), while other private functions should not be reconstructed with distortion below a certain threshold (privacy). We demonstrate how chi-square information captures the fundamental PUT in this case and provide bounds for the best PUT. We propose a convex program to compute privacy-assuring mappings when the functions to be disclosed and hidden are known a priori and the data distribution is known. We derive lower bounds on the minimum mean-squared error of estimating a target function from the disclosed data and evaluate the robustness of our approach when an empirical distribution is used to compute the privacy-assuring mappings instead of the true data distribution. We illustrate the proposed approach through two numerical experiments.
UBE3A Suppresses Overnutrition‐Induced Expression of the Steatosis Target Genes of MLL4 by Degrading MLL4

Regulation of the protein stability of epigenetic regulators remains ill‐defined despite its potential applicability in epigenetic therapies. The histone H3‐lysine 4‐methyltransferase MLL4 is an epigenetic transcriptional coactivator that directs overnutrition‐induced obesity and fatty liver formation, and Mll4+/‐ mice are resistant to both. Here we show that the E3 ubiquitin ligase UBE3A targets MLL4 for degradation, thereby suppressing high‐fat diet (HFD)‐induced expression of the hepatic steatosis target genes of MLL4. In contrast to Mll4+/‐ mice, Ube3a+/‐ mice are hypersensitive to HFD‐induced obesity and fatty liver development. Ube3a+/‐;Mll4+/‐ mice lose this hypersensitivity, supporting roles of increased MLL4 levels in both phenotypes of Ube3a+/‐ mice. Correspondingly, our comparative studies with wild‐type, Ube3a+/‐ and Ube3a‐/‐ and UBE3A‐overexpressing transgenic mouse livers demonstrate an inverse correlation of UBE3A protein levels with MLL4 protein levels, expression of the steatosis target genes of MLL4, and their decoration by H3‐lysine 4‐monomethylation, a surrogate marker for the epigenetic action of MLL4. Conclusion: UBE3A indirectly exerts an epigenetic regulation of obesity and steatosis by degrading MLL4. This UBE3A‐MLL4 regulatory axis provides a potential therapeutic venue for treating various MLL4‐directed pathogeneses, including obesity and hepatic steatosis.
Isolation and Characterization of Multipotent CD24+ Cells From the Renal Papilla of Swine

Over 100,000 patients in the United States are currently waiting for a kidney transplant. With just over 10,000 cadaveric kidneys transplanted annually, it is of the utmost importance to optimize kidney viability upon transplantation. One exciting avenue may be xenotransplantation, which has rejuvenated interest after advanced gene editing techniques have been successfully used in swine. Simultaneously, acute kidney injury (AKI) is associated with high morbidity and mortality and currently lacks effective treatment. Animal models have been used extensively to address both of these issues, with recent emphasis on renal progenitor cells (RPCs). Due to anatomical similarities to humans we aimed to examine progenitor cells from the renal papillae of swine kidneys. To do this, RPCs were dissected from the renal papillae of healthy swine. Cell surface marker expression, proliferation, and differentiation of the RPCs were tested in vitro. Additionally, a mixed lymphocyte reaction was performed to examine immunomodulatory properties. RPCs displayed spindle shaped morphology with limited self-renewing capacity. Isolated RPCs were positive for CD24 and CD133 at early passages, but lost expression with subsequent passaging. Similarly, RPCs displayed myogenic, osteogenic, and adipogenic differentiation capacities at passage 2, but largely lost this by passage 6. Lastly, direct contact of RPCs with human lymphocytes increased release of IL6 and IL8. Taken together, RPCs from the papilla of porcine kidneys display transient stem cell properties that are lost with passaging, and either represent multiple types of progenitor cells, or a multipotent progenitor population. In instances of ischemic insult, augmentation of/with RPCs may potentiate regenerative properties of the kidney. While the use of swine for transplantation and ischemia studies confers obvious advantages, the populations of different progenitor cell populations within pig kidneys warrants further investigation. Ultimately, while gene editing techniques enhance the potential for xenotransplantation of organs or cells, the ultimate success of this strategy may be determined by the (dis)similarities of RPCs from different species.
FluidMeter: Gauging the Human Daily Fluid Intake Using Smartwatches

Water is the most vital nutrient in the human body accounting for about 60% of the body weight. To maintain optimal health, it is important for humans to consume a sufficient amount of fluids daily. Therefore, tracking the amount of human daily fluid intake has a myriad of health applications like dehydration prevention. In this paper, we present FluidMeter: a ubiquitous and unobtrusive system to track the amount of fluid intake leveraging the inertial sensors embedded in smartwatches. To achieve this, FluidMeter first separates the drinking activities from other human activities (playing, running, eating, etc.). Thereafter, it analyzes the sampled sensors data during the extracted drinking episodes to recognize the sequence of micro-activities (lift the bottle, sip, release the bottle) that constitute the drinking activity. Finally, it applies some machine learning algorithms on some features extracted from sampled sensor data during the sipping period to gauge the amount of fluid intake in the designated drinking episode. FluidMeter is evaluated by collecting more than 260 hours of different human activities by 70 different participants using different smartwatch models. The results show that FluidMeter can recognize the drinking activity and its micro-activities accurately which is comparable to that achieved by the state-of-the-art techniques. Finally, FluidMeter can estimate the overall amount of fluid intake in grams accurately with a estimation error limited to 15%, highlighting its promise as a ubiquitous health service.
Hybrid Internal Anomaly Detection System for IoT: Reactive Nodes with Cross-Layer Operation

We present a hybrid internal anomaly detection system that shares detection tasks between router and nodes. It allows nodes to react instinctively against the anomaly node by enforcing temporary communication ban on it. Each node monitors its own neighbors and if abnormal behavior is detected, the node blocks the packets of the anomaly node at link layer and reports the incident to its parent node. A novel RPL control message, Distress Propagation Object (DPO), is formulated and used for reporting the anomaly and network activities to the parent node and subsequently to the router. The system has configurable profile settings and is able to learn and differentiate between the nodes normal and suspicious activities without a need for prior knowledge. It has different subsystems and operation phases that are distributed in both the nodes and router, which act on data link and network layers. The system uses network fingerprinting to be aware of changes in network topology and approximate threat locations without any assistance from a positioning subsystem. The developed system was evaluated using test-bed consisting of Zolertia nodes and in-house developed PandaBoard based gateway as well as emulation environment of Cooja. The evaluation revealed that the system has low energy consumption overhead and fast response. The system occupies 3.3 KB of ROM and 0.86 KB of RAM for its operations. Security analysis confirms nodes reaction against abnormal nodes and successful detection of packet flooding, selective forwarding, and clone attacks. The system’s false positive rate evaluation demonstrates that the proposed system exhibited 5% to 10% lower false positive rate compared to simple detection system.
Creating a social media-based personal emotional lexicon

One of the major problems when using lexicon in sentiment analysis is that they do not cover all possible words in a text and frequently they miss the more expressive to describe the emotions of the text's author efficiently. This problem occurs because people in non-official, on formal channels, communicate using slangs, neologisms, new patterns based on abbreviations (as "aka", "brb" and "asap") and the different meanings, making challenging to analyse texts using a finite subset of a language. This is a problem because some unknown words can completely change the meaning of a sentence, producing misunderstandings. In this paper we present an approach to expand an emotional lexicon for a specific author, producing a customised lexicon which represents how the author "feels" the words. In our experiments, we got an increase of 35.34% and 107.02% in the dictionary size when compared to the original lexicon using two different authors, and identifying different emotions from the same text according to each author's lexicon, i.e. interpreting the text according to the author's "point of view".
Generalized Content-Preserving Warps for Image Stitching

Local misalignment caused by global homography is a common issue in image stitching task. Content-Preserving Warping (CPW) is a typical method to deal with this issue, in which geometric and photometric constraints are imposed to guide the warping process. One of its essential condition however, is colour consistency, and an elusive goal in real world applications. In this paper, we propose a Generalized Content-Preserving Warping (GCPW) method to alleviate this problem. GCPW extends the original CPW by applying a colour model that expresses the colour transformation between images locally, thus meeting the photometric constraint requirements for effective image stitching. We combine the photometric and geometric constraints and jointly estimate the colour transformation and the warped mesh vertexes, simultaneously. We align images locally with an optimal grid mesh generated by our GCPW method. Experiments on both synthetic and real images demonstrate that our new method is robust to colour variations, outperforming other state-of-the-art CPW-based image stitching methods.
Text Sentiment Polarity Classification Method Based on Word Embedding

Most of the machine learning algorithms for text sentiment analysis use the word embedding obtained by word2vec training as their inputs. However, the word embedding of word2vec training contains only semantic information. An algorithm for text sentiment analysis is proposed solve the problem of text containing semantics, syntax, sentiment and other information. It begins with the learning of original text-multi word embedding in the semantic, syntactic, and sentiment information, followed by proceeding the word embedding fusion. The improved convolution neural network is applied for sentiment analysis. Thus, it solves the problem that the word embedding contains monotonous text information. K-means text clustering is applied by dividing similar text into the same cluster, thus improving the classification accuracy. The application of the Principal Component Analysis (PCA) dimensionality not only extracts the principal component information, but also solves the problem of redundancy embedding and improves the computational performance of classification model. The experiment results show that the presented method has a significant improvement in the accuracy, recall rate and F value of the sentiment polarity analysis of the critical text in comparison with other fusion algorithms.
Semantic Enrichment of a Multilingual Archive with Linked Open Data

This paper introduces MERCKX, a Multilingual Entity/Resource Combiner & Knowledge eXtractor. A case study involving the semantic enrichment of a multilingual archive is presented with the aim of assessing the relevance of natural language processing techniques such as named-entity recognition and entity linking for cultural heritage material. In order to improve the indexing of historical collections, we map entities to the Linked Open Data cloud using a language-independent method. Our evaluation shows that MERCKX outperforms similar tools on the task of place disambiguation and linking, achieving over 80% precision despite lower recall scores. These results are encouraging for small and medium-size cultural institutions since they demonstrate that semantic enrichment can be achieved with limited resources.
Sinomenine Protects Against Morphine Dependence through the NMDAR1/CAMKII/CREB Pathway: A Possible Role of Astrocyte-Derived Exosomes

Sinomenine is a nonaddictive alkaloid used to prevent morphine dependence, even thoughits mechanism isnot fully understood. Astrocytes aggravate the pathological process in their neighboring cellsthrough exosomes in central nervous system diseases. However, the effect of sinomenine on astrocyte-derived exosomes for the amelioration of morphine dependence has not been reported yet. In this study, we found that sinomenine prevented the morphine-induced conditionedplace preference in mice. Sinomenine reduced the levels of cAMP and intracellular Ca2+ in morphine-treated SH-SY5Y cells. Moreover, sinomenine inhibited the expressions of p-NMDAR1/NMDAR1, p-CAMKII/CAMKII, and p-CREB/CREB in the hippocampusof morphine-dependent mice and SH-SY5Y cells. Furthermore, we found that sinomenine inhibitedthe morphine-induced activation of astrocytesin vivo and in vitro. Afterwards, exosomes were isolated from cultured primary astrocytes treated with phosphate buffer saline (PBS, ctl-exo), morphine (mor-exo), or morphine and sinomenine (Sino-exo). Subsequently, morphine-treated SH-SY5Y cells were treated with ctl-exo, mor-exo, and Sino-exo. Results showed that Sino-exo reduced the level of cAMP, intracellular Ca2+, and the expression of p-CAMKII/CAMKII and p-CREB/CREB in morphine-treated SH-SY5Y cells. In conclusion, we demonstrated that sinomenine exhibited protective effects against morphine dependencein vivo and in vitro through theNMDAR1/CAMKII/CREB pathway. Sinomenine-induced alterationof the function of astrocyte-derived exosomes may contribute to the antidependence effects of sinomenine in morphine dependence.
Time zones of pancreatic islet metabolism

Most living beings possess an intrinsic system of circadian oscillators, allowing anticipation of the Earth's rotation around its own axis. The mammalian circadian timing system orchestrates nearly all aspects of physiology and behaviour. Together with systemic signals originating from the central clock that resides in the hypothalamic suprachiasmatic nucleus, peripheral oscillators orchestrate tissue‐specific fluctuations in gene transcription and translation, and posttranslational modifications, driving overt rhythms in physiology and behaviour. There is accumulating evidence of a reciprocal connection between the circadian oscillator and most aspects of physiology and metabolism, in particular as the circadian system plays a critical role in orchestrating body glucose homeostasis. Recent reports imply that circadian clocks operative in the endocrine pancreas regulate insulin secretion, and that islet clock perturbation in rodents leads to the development of overt type 2 diabetes. While whole islet clocks have been extensively studied during the last years, the heterogeneity of islet cell oscillators and the interplay between α‐ and β‐cellular clocks for orchestrating glucagon and insulin secretion have only recently gained attention. Here, we review recent findings on the molecular makeup of the circadian clocks operative in pancreatic islet cells in rodents and in humans, and focus on the physiologically relevant synchronizers that are resetting these time‐keepers. Moreover, the implication of islet clock functional outputs in the temporal coordination of metabolism in health and disease will be highlighted.
Performance model for mesh optimization on distributed-memory computers

Many mesh optimization applications are based on vertex repositioning algorithms (VrPA). The execution times of these numerical algorithms vary widely, usually with a trade-off between different parameters. In this work, we analyze the impacts of six parameters of sequential VrPA on runtime. Our analysis is used to propose a new workload measure called number of mesh element evaluations. Since the execution time required for VrPA programs may be too large and there is concurrency in processing mesh elements, parallelism has been used to improve performance efficiently. The performance model is extended to parallel VrPA algorithms that are implemented in MPI. This model has been validated using two Open MPI versions on two distributed-memory computers and is the basis for the quantitative analysis of performance scalability, load balancing and synchronization and communication overheads. Finally, a new approach to mesh partitioning that improves load balancing is proposed.