Miracle-dz/UniFAR-FTUs huggingface dataset:
Smart Nests: IoT for Ornithology

In this work an autonomous bird nest is presented to monitor and record the breeding of the Great Tit species (Parus major) which is a passerine bird in the tit family Paridae. It introduces a novel design for a reliable measurement of the time that birds spend inside the nests. This design is based on a double-switched RFID reader and antenna configuration that recognizes when the bird enters and exits the nest. The system includes a micro-controller, two Radio Frequency IDentification (RFID) readers, two coil antennas, a power management module, and aGPRS communications subsystem to transmit the birds' activity to the Internet. It also contains a Real Time Clock (RTC) to obtain time and date when a bird goes in or out of the nest, and a memory to save the data when cellular coverage is occasionally lost.Birds are ringed with glass capsuled passive Low Frequency (LF) FDX-B RFID tags, which are mounted on a 3D printed tag holder and attached to the bird's leg. The IoT smart nest can providespecific information about the breeding of birds' to ornithologists all over the world: Correlation of birds and nests, timing of birds entering and exiting a nest, duration of each stay, feeding frequency, etc. During manual and field tests, the IoT bird nests have demonstrated consistent detection, with a success rate of 100% and 95% respectively. This IoT device could be used for any other bird species with the only modification of the coil antenna diameterupon the bird's size.
Prophet Inequalities for Independent Random Variables from an Unknown Distribution

A central object in optimal stopping theory is the single-choice prophet inequality for independent, identically distributed random variables: Given a sequence of random variables $X_1,\dots,X_n$ drawn independently from a distribution $F$, the goal is to choose a stopping time $\tau$ so as to maximize $\alpha$ such that for all distributions $F$ we have $\mathbb{E}[X_\tau] \geq \alpha \cdot \mathbb{E}[\max_tX_t]$. What makes this problem challenging is that the decision whether $\tau=t$ may only depend on the values of the random variables $X_1,\dots,X_t$ and on the distribution $F$. For quite some time the best known bound for the problem was $\alpha\geq1-1/e\approx0.632$ [Hill and Kertz, 1982]. Only recently this bound was improved by Abolhassani et al. [2017], and a tight bound of $\alpha\approx0.745$ was obtained by Correa et al. [2017]. The case where $F$ is unknown, such that the decision whether $\tau=t$ may depend only on the values of the first $t$ random variables but not on $F$, is equally well motivated (e.g., [Azar et al., 2014]) but has received much less attention. A straightforward guarantee for this case of $\alpha\geq1/e\approx0.368$ can be derived from the solution to the secretary problem. Our main result is that this bound is tight. Motivated by this impossibility result we investigate the case where the stopping time may additionally depend on a limited number of samples from~$F$. An extension of our main result shows that even with $o(n)$ samples $\alpha\leq 1/e$, so that the interesting case is the one with $\Omega(n)$ samples. Here we show that $n$ samples allow for a significant improvement over the secretary problem, while $O(n^2)$ samples are equivalent to knowledge of the distribution: specifically, with $n$ samples $\alpha\geq1-1/e\approx0.632$ and $\alpha\leq\ln(2)\approx0.693$, and with $O(n^2)$ samples $\alpha\geq0.745-\epsilon$ for any $\epsilon>0$.
PZT and PNIPAM Film-Based Flexible and Stretchable Electronics for Knee Health Monitoring and Enhanced Drug Delivery

This paper presents a flexible and stretchable electronic device with multi-functionality. This device contains a functional node array coated in smart materials and can be packaged with biocompatible polydimethylsiloxane (PDMS) films as a smart patch. Two kinds of smart materials are utilized: piezoelectric lead zirconate titanate (PZT) film for sensing acoustic emission (AE) waves and thermally activated poly (N-isopropylacrylamide) film for drug delivery. The functional node array is implemented on a thin flexible titanium sheet with an electrically connected serpentine network. This design has two advantages: 1) the serpentine network allows the node array to stretch in an arbitrary planar direction and 2) while the patch is stretched, the normal force exerted by the node can enhance the AE detection head’s coupling to the sensing object as well as increase the contact force and area of the PNIPAM film. The fabrication and experimental results of the designed serpentine-network AE-sensing structure, along with the temperature-controlled drug-release element, is described. The fabricated stretchable and flexible electronic device, assembled with a knee-band strap to examine the AE signals from the knee while executing hopping and jumping as well as walking motions, is also discussed.
Effects of Modeling and a Directional Cue on Vehicle Safety Belt Use

A driver's safety belt use in the presence or absence of a specific directional cue (dashboard sign to fasten seat belts) was manipulated and belt use of passengers observed. In a 2 x 2 factorial design, 20 men and 37 women were randomly assigned to modeled belt use versus nonuse and sign-present versus sign-absent conditions. The experiment involved a short car ride with opportunity for belt use or nonuse modeling by the female driver and observation of front-seat passenger belt use. Significant main effects for the modeling and sign variables were qualified by a significant interaction: The relationship between passenger belt use and modeling was strongest when the sign was present. In particular, the model's disobedience to the instruction of the sign significantly reduced passenger belt use from the relatively high levels of use in the other three conditions. A significant interaction of modeling and subject gender showed that lowest belt use occurred for male subjects whose (female) drivers modeled n.
Time-space–displaced responses in the orangutan vocal system

Wild orangutan mothers weigh the danger posed by predators and wait until it is safe to inform their dependent infants. One of the defining features of language is displaced reference—the capacity to transmit information about something that is not present or about a past or future event. It is very rare in nature and has not been shown in any nonhuman primate, confounding, as such, any understanding of its precursors and evolution in the human lineage. Here, we describe a vocal phenomenon in a wild great ape with unparalleled affinities with displaced reference. When exposed to predator models, Sumatran orangutan mothers temporarily suppressed alarm calls up to 20 min until the model was out of sight. Subjects delayed their vocal responses in function of perceived danger for themselves, but four major predictions for stress-based mechanisms were not met. Conversely, vocal delay was also a function of perceived danger for another—an infant—suggesting high-order cognition. Our findings suggest that displaced reference in language is likely to have originally piggybacked on akin behaviors in an ancestral hominid.
Study on Land Classification of PolSAR Data by Using Support Vector Machine

Polarimetric Synthetic Aperture Radar (PolSAR) has been attracting attention in ground target detection and classification. Various methods, such as model-based scattering power decomposition, eigenvalue analysis and so forth, have been proposed for the analysis of PolSAR data. Recently, classification techniques by using machine learning have been intensively studied to reduce misclassification. In this paper, we present some experimental results of land classification of ALOS-2/PALSAR-2 data by using support vector machine. We confirm in this report that support vector machine analysis is more accurate than the conventional unsupervised classifier such as model-based decomposition.
Humanization of the Prostate Microenvironment Reduces Homing of PC3 Prostate Cancer Cells to Human Tissue-Engineered Bone

The primary tumor microenvironment is inherently important in prostate cancer (PCa) initiation, growth and metastasis. However, most current PCa animal models are based on the injection of cancer cells into the blood circulation and bypass the first steps of the metastatic cascade, hence failing to investigate the influence of the primary tumor microenvironment on PCa metastasis. Here, we investigated the spontaneous metastasis of PC3 human PCa cells from humanized prostate tissue, containing cancer-associated fibroblasts (CAFs) and prostate lymphatic and blood vessel endothelial cells (BVECs), to humanized tissue-engineered bone constructs (hTEBCs) in NOD-SCID IL2Rγnull (NSG) mice. The hTEBC formed a physiologically mature organ bone which allowed homing of metastatic PCa cells. Humanization of prostate tissue had no significant effect on the tumor burden at the primary site over the 4 weeks following intraprostatic injection, yet reduced the incidence and burden of metastases in the hTEBC. Spontaneous PCa metastases were detected in the lungs and spleen with no significant differences between the humanized and non-humanized prostate groups. A significantly greater metastatic tumor burden was observed in the liver when metastasis occurred from the humanized prostate. Together, our data suggests that the presence of human-derived CAFs and BVECs in the primary PCa microenvironment influences selectively the metastatic and homing behavior of PC3 cells in this model. Our orthotopic and humanized PCa model developed via convergence of cancer research and tissue engineering concepts provides a platform to dissect mechanisms of species-specific PCa bone metastasis and to develop precision medicine strategies.
The kinetics of gut microbial community composition in patients with irritable bowel syndrome following fecal microbiota transplantation

Background Gut microbiota alterations are important in irritable bowel syndrome (IBS). The aim was to investigate the effect of fecal microbiota transplantation (FMT) on gut microbiota and the symptoms in patients with IBS. Material and methods The study included 13 IBS patients according to Rome III criteria and 13 healthy donors. Freshly donated feces were administered to the descending part of the duodenum via a gastroscope. Feces were collected from donors and patients before FMT, and from the patients at 1, 3 and 12 weeks and donors and patients at 20/28 weeks after FMT. Microbiota analysis was performed using GA-map Dysbiosis test (Genetic Analysis AS, Oslo, Norway). The patients completed the following questionnaires before and at the aforementioned weeks after FMT: IBS Symptom Questionnaire (IBS-SQ), IBS-Symptom Severity Scoring system (IBS-SSS), Short Form of Nepean Dyspepsia Index (SF-NDI), Bristol stool form scale, the Eysenck Personality Questionnaire-Neuroticism and Hospital Anxiety and Depression. Results Donors and IBS patients had significantly different bacterial strain signals before FMT (Ruminococcus gnavus, Actinobacteria and Bifidobacteria) that became non-significant after 3 weeks following FMT. The changes in gut microbiota were similar between donors and patients at 20/28 weeks after FMT. Thus, patients’ microbiota profiles became more-or-less similar to donors. The scores of all the questionnaires were significantly improved at all time points following FMT. No reported adverse effects. Conclusions FMT was associated with a change in gut microbiota and improvement in IBS symptoms and quality of life lasting for up to 28 weeks. Trial registration ClinicalTrials.gov ID: NCT03333291
A Common Integrated Framework for Heterogeneous Modeling Services

Modeling languages are often used for designing complex systems. To simplify the modeling process, system designers can use dedicated modeling frameworks, which provide all necessary tools and services in order to facilitate system development and decrease costs by eliminating errors early at design time. Nowadays, the emergence of heterogeneous engineering domains has led to design flows that span multiple Domain Specific Modeling Languages (DSMLs). As a result, analyzing system behavior requires the semantic integration of modeling domains through languages that are supported by formal semantics, are easily adaptable, and provide scalable and efficient correctness-checking services. To this end, we present a framework that provides heterogeneous modeling services that are based on the combination of two formalisms, 1) logics and 2) graphs. On one hand, we use the FORMULA tool to formalize the semantics of DSMLs and provide a common integrated semantic background. On the other hand, we use graph queries specified in Gremlin to employ efficient query and model analysis services. Our framework offers a complete model-based engineering solution that includes graphical modeling and version control services, which are integrated into a web-based collaborative environment.
Multilevel modeling: what's in a level? A position paper

Multi-Level Modeling (MLM) conceptualizes software models as layered architectures of sub-models whose elements are inter-related by the instance-of relation, which is radically different from the traditional two level representations that consist of a class model and an instance model, where the former represents the schema and the latter the population. Key to the MLM representation is the notion of a level, which is the subject of this position paper. We argue that a theory of MLM must have a distinguished notion of level, which should have both a syntactic and a semantic status. Moreover, the notion of a level must represent a class model, and the overall MLM theory must be compositional, being composed from the theory of class models.
Filler Migration and Granuloma Formation After Gluteal Augmentation with Free-silicone Injections

Gluteal augmentation may be performed using a variety of techniques, including implant-based, autologous fat grafting, local flaps, impermanent filler injection, or, as in this case, by way of permanent filler injection with free-silicone. Of these, free-silicone injections carry one of the highest complication rates, specifically regarding migration of the filler material from the native injection site and induction of painful reactive soft tissue changes at the new filler location. A radiologist providing this diagnosis may assist the clinician, who often cannot obtain a history of illicit silicone injection for gluteal augmentation unless the suspicion is raised. Presented here is a case of painful filler migration to the knee with granuloma formation after free-silicone gluteal injection.
Analysis of Ricefield Land Damage in Denpasar City, Bali, Indonesia

Soil as a natural resource, living area, environmental media, and factors of production including biomass production that supports human life and other living beings must be preserved, on the other hand, uncontrolled biomass production activities can cause soil damage, ultimately can threaten the survival of humans and other living things. Therefore, in order to control soil damage, first must inventories the soil condition data and its damage which then visualised in soil damage potential and soil damage status. The activities of the study are the preparation of a map of the initial soil conditions and the delineation of potentially land degradation distribution. Mapping results are used as work maps for verification on the field to take soil samples and create soil damage status. In general, Denpasar City have soil damage potential at very low, low until medium rate. Soil damage status in Denpasar City generally is low damage of bulk volume, total porosity, soil permeability and electrolyte conductivity which beyond limitation thresholds.
Investigation of metasurface eigenmode impact on receive sensitivity enhancement of MRI machine

Magnetic resonance image quality directly depends on the signal-to-noise ratio provided by the receive coil. It was recently shown that wire metasurface can enhance the signal-to-noise ratio of the commercial scanner due to the spatial redistribution of the radiofrequency electromagnetic field through the resonant excitation of a wire metasurface eigenmode. In this work, we experimentally investigate the impact of this eigenmode on receive sensitivity enhancement of the 1.5 T birdcage coil. We proof that due to the certain spatial profile of the metasurface eigenmode, signal-to-noise ratio enhancement directly depends on the position and dimensions of the studied object on the metasurface.
Power (Set) ALC

We explore the relationships between Description Logics and Set Theory. The study is carried on using, on the set-theoretic side, a very rudimentary axiomatic set theory Ω, consisting of only four axioms characterizing binary union, set difference, inclusion, and the power-set. The approach is then completed defining ALC , an extension of ALC in which concepts are naturally interpreted as sets living in Ω-models. In ALC not only membership between concepts is allowed—even admitting circularity—but also the power-set construct is exploited to add metamodeling capabilities. We conclude providing a polynomial translation ofALC inALCOI and proving its basic traits, among which the validity of the finite model property.
Condition monitoring technology of transformer with multiple sensing methods united

partial discharge detection is an effective way for transformer condition monitoring, and thus different detection methods for partial discharge are developed. However, the fact is that there hasn't been a detection method that can solve all the problems so far. Every detection method has its advantages and limitations. To improve this problem, the paper introduces a united detection method based on ultra-high frequency (UHF) method, high-frequency method and ultrasonic method. It is validated by an experiment that a better performance in the partial discharge detection of transformer can be obtained by the united method compared to conventional detection methods. The common problems in partial discharge detection such as anti-interfere, pattern recognition, defects location and apparent charge measurement can be solved with the united detection technology effectively.
Stability implies constancy for fully autonomous reaction-diffusion-equations on finite metric graphs

We show that there are no stable stationary nonconstant solutions of the evolution problem (1) for fully autonomous reaction-diffusion-equations on the edges of a finite metric graph \begin{document}$ G$\end{document} under continuity and Kirchhoff flow transition conditions at the vertices. \begin{document}$(1) \ \ \ \ \ \ \ \ \ \ \begin{cases} u∈ \mathcal{C}(G×[0,∞))\cap \mathcal{C}^{2,1}_{K}(G×(0,∞)),\\\partial_t u_j=\partial_j^2u_{j}+f(u_j) & \text{on the edges }k_j,\\ \displaystyle(K)\ \ \ \ \sum\limits_{j=1}^N d_{ij} c_{ij}\partial_ju_{j}(v_i,t)=0 &\text{at the vertices } v_i. \end{cases} $ \end{document}
Direct 4D Patlak 18F-FDG PET/MR for the Multi-Parametric Assessment of active cardiac sarcoidosis

Cardiac involvement in sarcoidosis is currently under-diagnosed despite being the leading cause of death amongst sarcoidosis patients. Therefore, accurate and early diagnosis of subclinical but active cardiac sarcoidosis (ACS) is an important clinical goal. The recent advent of hybrid PET/MRI has enabled the multi-parametric and non-invasive evaluation of ACS in the myocardium at a significantly reduced radiation exposure. Although cardiac MRI with late gadolinium enhancement (LGE) may visualize the anatomical pattern of myocardial injury due to ACS, it cannot differentiate between active disease and old chronic scarring. On the other hand, 18FFDG PET standard uptake values (SUVs), which are used to identify regions of increased myocardial inflammation in patients with ACS, may not discriminate ACS-related inflammatory FDG signal, from high non-specific physiological FDG uptake, often leading to false positive ACS interpretation. In this study, we introduce a clinically feasible dynamic 18F-FDG PET/MR cardiac imaging protocol enabling the 4D analysis of the 18FFDG myocardial uptake pattern, coregistered with the LGE MR images. In addition, we employ advanced direct 4D Patlak parametric PET image reconstructions to deliver, beside standard semi-quantitative SUVs, highly quantitative images of the physiological parameters of FDG uptake rate (Ki), obtained directly from the complete 4D PET acquisition data, for enhanced robustness to statistical noise and Ki quantification. We believe that our proposed framework of multi-parametric 4D 18F-FDG PET/MR cardiac imaging may substantially improve ACS diagnosis by i) allowing a more accurate identification of positive ACS patterns in matched myocardium regions across LGE, SUV as well as Ki images and ii) enabling the quantitative Ki-driven differentiation between true- and false-positive ACS indications for enhanced specificity.
A New Learning Automata-Based Pruning Method to Train Deep Neural Networks

Deep neural network are one of the most powerful model for machine learning, which can learn the underlying patterns automatically from a large amount of data. So it can be extensively used in more and more Internet-of-Things (IoT) applications. However, the training of deep models is difficult, suffering from overfitting and gradient vanishing problem. Besides, the large amount of parameters and multiplication operations make it impractical for most deep learning models to directly execute on target hardware. In this paper, we propose a method of gradually pruning the weakly connected weights to improve the traditional stochastic gradient descent. And we adopt a reinforcement learning method called learning automata to find the weakly connected weights on account of its strong policy-making ability in stochastic and nonstationary environment. Our proposed method can learn a more effective and sparsely connected architecture during training from the initially fully connected neural networks. The experiments on MNIST show that our method have stronger power to defeat overfitting and can get better generalization performance on test set. Meanwhile, the thin and sparsely connected model we get can be more suitable for IoT applications.
A systematic review of quality measures used in primary care dentistry.

INTRODUCTION 'Quality' in primary care dentistry is poorly defined. There are significant international efforts focussed on developing quality measures within dentistry. The aim of this research was to identify measures used to assess quality in primary care dentistry and categorise them according to which dimensions of quality they attempt to measure. METHODS Quality measures were identified from the peer-reviewed and grey literature. Peer-reviewed papers describing the development and validation of measures were identified using a structured literature search. Measures from the grey literature were identified using structured searches and direct contact with dental providers and institutions. Quality measures were categorised according to domains of structure, process and outcome and by disaggregated dimensions of quality. RESULTS From 22 studies, 11 validated measure sets (comprising nine patient satisfaction surveys and two practice assessment instruments) were identified from the peer-reviewed literature. From the grey literature, 24 measure sets, comprising 357 individual measures, were identified. Of these, 96 addressed structure, 174 addressed process and 87 addressed outcome. Only three of these 24 measure sets demonstrated evidence of validity testing. The identified measures failed to address dimensions of quality, such as efficiency and equity. CONCLUSIONS There has been a proliferation in the development of dental quality measures in recent years. However, this development has not been guided by a clear understanding of the meaning of quality. Few existing measures have undergone rigorous validity or reliability testing. A consensus is needed to establish a definition of quality in dentistry. Identification of the important dimension of quality in dentistry will allow for the production of a core quality measurement set.