Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Proximity with Bluetooth Low Energy Beacons for Cultural Heritage

The RE.S. I.STO project targets visitors of Pisa medieval city, with the goal of providing high-quality digital contents accessible with smart devices. We describe the design, implementation and the test phases of the RE.S. I.STO application, whose goal is to automatically detect the proximity between visitors and artworks. Proximity is detected with a set of algorithms based on the analysis of Bluetooth Low Energy beacons. We detail our experimental campaigns which reproduce several museum layouts of increasing complexity at two pilot sites, and we compute the performance of the implemented algorithms to detect the nearby artworks. In particular, we test our solution in a wide open space located in our research institute and by performing a real deployment at the Camposanto Monumentale located in Pisa (Italy). The obtained performance varies in the range of 40% to perfect accuracy, according to the complexity of the considered museum layouts. We also describe a set of stress and stability tests aimed at verifying the robustness of the application during the data collection process. Our results show that the mobile application is able to reduce the beacon loss rate, with an average value of 77% of collected beacons.
Media Literacy in Preventing the Spread of Radicalism in the Millennial Generation

This study aims to deepen the understanding of the millennial generation in Malang on the importance of media literacy skills in preventing the spread of radicalism through social media. The units of analysis in this study were students from Brawijaya University and Muhammadiyah Malang University who were active in campus organizational activities. Researchers use a qualitative approach with an interpretive paradigm in order that researchers can obtain a more detailed perspective or point of view of the informant. The results showed that the millennial generation already understands the concept of media literacy and practices it in using social media so that radicalism spread through social media cannot influence them.
The Eagle

Our goal is to provide quality and safe health care to our Veterans. Urgent Care Centers are used to treat minor illnesses or injuries and are not open 24/7. Coatesville VAMC does not provide 24/7 emergency services but will provide full urgent care services during its weekday hours of operations to include pharmacy, radiology and laboratory. Community emergency rooms are available at all hours for life-threatening conditions. See page two for more information about VA payment for emergency care.
Moving target trajectory prediction based on Dropout-LSTM and Bayesian inference for long-time multi-satellite observation

ABSTRACT Multi-satellite cooperation facilitates long-time and wide-area observation of moving targets and has received considerable attention. An accurate and real-time trajectory prediction of an observed target is the primary premise of multi-satellite cooperative observation that attempts to address the field-of-view switching problem for different satellites. However, the existing methods do not consider the non-linear and time-variant satellite observation process, and the interpretability requires improvement. Therefore, a trajectory prediction model is constructed with decoupled linear Gaussian and non-linear Gaussian parts, based on the analysis of the satellite observation process and the verification of the normal distribution of the observation error. Thereafter, a trajectory prediction method, comprising long short-term memory networks and Bayesian inference, is proposed. The proposed method not only enables the long short-term memory with dropout variational inference to automatically extract features and learn more complex spatiotemporal patterns, but also employs Bayesian inference to introduce the satellite orbit and attitude information as known variables and improve the spatiotemporal smoothness. Finally, a simulation system of moving target trajectory prediction is established, and the results indicate that our approach is superior in terms of the prediction accuracy and generalization properties, compared with the existing methods, particularly when the observed target is manoeuvring rapidly. Consequently, the proposed approach provides a technical basis for achieving long-time multi-satellite observation of the moving target.
Efficiency of Resistant Starch and Dextrins as Prebiotics: A Review of the Existing Evidence and Clinical Trials

In well-developed countries, people have started to pay additional attention to preserving healthy dietary habits, as it has become common knowledge that neglecting them may easily lead to severe health impairments, namely obesity, malnutrition, several cardiovascular diseases, type-2 diabetes, cancers, hypertensions, and inflammations. Various types of functional foods were developed that are enriched with vitamins, probiotics, prebiotics, and dietary fibers in order to develop a healthy balanced diet and to improve the general health of consumers. Numerous kinds of fiber are easily found in nature, but they often have a noticeable undesired impact on the sensory features of foods or on the digestive system. This led to development of modified dietary fibers, which have little to no impact on taste of foods they are added to. At the same time, they possess all the benefits similar to those of prebiotics, such as regulating gastrointestinal microbiota composition, increasing satiety, and improving the metabolic parameters of a human. In the following review, the evidence supporting prebiotic properties of modified starches, particularly resistant starches and their derivatives, resistant dextrins, was assessed and deliberated, which allowed drawing an interesting conclusion on the subject.
A New Hybrid Kinematic/Dynamic Whole-Body Control for Humanoid Robots with Real-Time Experiments

In this paper, a new hybrid kinematic/dynamic control scheme for humanoid robots is proposed. Its basic idea lies in the tracking of several values in both operational and joint spaces. These values include (i) the relative pose of the robot’s feet, (ii) the position of the center of mass, (iii) the body’s orientation and (iv) the admissible range of variation of the joints. A zero moment point (ZMP) based dynamic feedback is included in the proposed scheme to improve the stability of dynamic motions. The proposed stabilizer is based on a spherical projection of a nonlinear PID regulation control law. Through the proposed study, it is shown that these objectives allow to produce smooth dynamically stable whole-body motions. The eﬀectiveness and robustness of the proposed control scheme is demonstrated through four real-time experimental scenarios, conducted on HOAP-3 humanoid robot.
Efficacy of a Preparation Based on Calcium Butyrate, Bifidobacterium bifidum, Bifidobacterium lactis, and Fructooligosaccharides in the Prevention of Relapse in Ulcerative Colitis: A Prospective Observational Study

Several compounds based on short chain fatty acids and/or probiotics/prebiotics have shown promising results in the therapy of ulcerative colitis (UC), possibly due to its key role in restoring gut homeostasis as well as intestinal barrier integrity. Here, we investigated the efficacy of a patented preparation based on calcium butyrate, Bifidobacterium bifidum, Bifidobacterium lactis, and fructooligosaccharides (FEEDColon®, Princeps, Cuneo, Italy) in maintaining remission and improving subjective symptoms and inflammatory indices in patients with UC receiving 5-ASA therapy. A total of 42 patients were prospectively recruited and randomized in 21 patients receiving combination therapy with mesalamine (5-ASA) plus FEEDColon® and 21 patients treated with standard 5-ASA therapy. Patients were assessed at baseline, at 6-month, and 12-month follow-up (FU). Therapeutic success (defined as Mayo partial score ≤ 2 and faecal calprotectin (FC) < 250 µg/g at 12-month FU) was reached by 32 (76%) patients: 20 (95%) among those treated with 5-ASA + FeedColon®, and 12 (57%) among those treated with 5-ASA only (p = 0.009). Consistently, patients treated with combination therapy improved subjective symptoms (quality of life, abdominal pain, and stool consistency) and reduced FC values, while those treated with 5-ASA alone, improved neither subjective symptoms nor FC during the FU. In conclusion, FEEDColon® supplementation appears to be a valid add-on therapy for the maintenance of remission in patients with UC. Further multicentre, placebo-controlled, double-blind clinical trials are needed to validate our results on larger cohorts of patients with UC.
Effects of Reproductive Health Education Using Video Animation Towards Reproductive Health Knowledge and Attitudes in 5th and 6th Elementary Grade Students in Serang City, Banten

Introduction: Adolescent reproductive health education aims to increase knowledge and attitudes about reproductive health. Therefore, an easy, inexpensive, and standardized method of education is needed in the delivery of reproductive health material to young adolescents, one of them is audiovisual media animationMethod: The research was conducted using a pre-experimental research design pretest-posttest one group design within 31 days. This study used a total sample of 180 subjects, furthermore, the data were analyzed using Structural Equation Modeling (SEM). Result: Education with reproductive health animated videos increased knowledge about reproductive health immediately after education was given (P = 0.002), but after 31 days, it did not affect (P = 0.171). Education with animated videos did not affect the subjects’ attitude immediately after education was carried out (P = 0.802) but had an effect after 31 days from the start of education (P = 0.031). After analyzing the correlation including other confounding variables (R square), it was found that the effect of education with animated videos towards the increasing knowledge of reproductive health was 14.9%, and 8.4% towards changes in subject attitudes.Discussion: Health education with video animation increases knowledge, but the phenomenon of attitudes such as dating still occurs even the subjects’ knowledge have increased.Conclusion: Reproductive health education using animated videos increases knowledge but does not change attitudes in reproductive health
JLM-Fast RNN Language Model with Large Vocabulary

The language model is a key to many tasks like machine translation, speech recognition, and input method. While neural network language model shows better accuracy and scalability to a wider context, the cost to get the probability of next word is non-trivial. Moreover, eastern Asian languages like Japanese and Chinese can easily have a large vocabulary over 100K words to cover the most frequently appeared tokens. In this paper, a fast RNN model named JLM1 with a hybrid optimization is proposed. The experiment on BCCWJ Japanese corpus shows a 50x speed up during inference with decoder and up to 90% model size reduced without significant perplexity change.
Large-scale snow data assimilation using a spatialized particle filter: recovering the spatial structure of the particles

Abstract. The use of particle filters for data assimilation is increasingly popular because of its minimal assumptions. Nevertheless, implementing a particle filter over domains of large spatial dimensions remains challenging, as the number of required particles rises exponentially as domain size increases. A common solution to overcome this issue is to localize the particle filter and consider a collection of local applications rather than a single regional one. Although this solution can solve the dimensionality limit, it can also create some spatial discontinuity inside the particles. This issue can become even more problematic when additional data is assimilated. The purpose of this study is to test the possibility of remedying the spatial discontinuities of the particles by locally reordering the particles. We implement a spatialized particle filter to estimate the snow water equivalent (SWE) over a large territory in eastern Canada by assimilating local manual snow survey observations. We apply two reordering strategies based on 1) a simple ascending order sorting and 2) the Schaake Shuffle and evaluate their ability to maintain the spatial structure of the particles. To increase the amount of assimilated data, we investigate the inclusion of a second data set, in which SWE is indirectly estimated from snow depth. The two reordering solutions maintain the spatial structure of the individual particles throughout the winter season, which significantly reduces the random noise in the distribution of the particles and decreases the uncertainty associated with the estimation. The Schaake Shuffle proves to be a better tool for maintaining a realistic spatial structure for all particles, although we also found that sorting provides a simpler and satisfactory solution. The assimilation of the secondary data set improved SWE estimates in ungauged sites when compared with the open-loop model, but we noted no significant improvement when both snow courses and the SR50 data were assimilated.
Duty Cycle Control Strategy for Dual-Side LCC Resonant Converter in Wireless Power Transfer Systems

The dual-side inductor–capacitor–capacitor (LCC) topology circuit has been widely adopted in wireless power transfer (WPT) systems due to its constant output current characteristic. However, most conventional control methods need specific synchronization techniques between the primary and secondary sides to avoid the oscillation in the system, which increases the cost and control complexity. To solve this issue, this article proposes a new duty cycle control (DCC) strategy for a dual-side LCC resonant converter with a semibridgeless active rectifier (SAR). With such a control strategy, gate signals of the primary- and secondary-side circuits do not need to be synchronized, which could reduce the complexity and the cost of the WPT system. Besides, the switching frequency of the secondary side can be decreased significantly. This article first presents the modal analysis of phase shift control (PSC) and DCC. Then, generalized state-space averaging (GSSA) modeling with PSC and the hybrid average modeling with DCC are performed. In addition, controllers’ design for both strategies is conducted to achieve the constant output voltage. Finally, the eigenvalues’ analysis is used to determine the stability region of the WPT system. The theoretical analysis has been validated by both simulation and experimental results.
Rho/ROCK Pathway and Noncoding RNAs: Implications in Ischemic Stroke and Spinal Cord Injury

Ischemic strokes (IS) and spinal cord injuries (SCI) are major causes of disability. RhoA is a small GTPase protein that activates a downstream effector, ROCK. The up-regulation of the RhoA/ROCK pathway contributes to neuronal apoptosis, neuroinflammation, blood-brain barrier dysfunction, astrogliosis, and axon growth inhibition in IS and SCI. Noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), were previously considered to be non-functional. However, they have attracted much attention because they play an essential role in regulating gene expression in physiological and pathological conditions. There is growing evidence that ROCK inhibitors, such as fasudil and VX-210, can reduce injury in IS and SCI in animal models and clinical trials. Recently, it has been reported that miRNAs are decreased in IS and SCI, while lncRNAs are increased. Inhibiting the Rho/ROCK pathway with miRNAs alleviates apoptosis, neuroinflammation, oxidative stress, and axon growth inhibition in IS and SCI. Further studies are required to explore the significance of ncRNAs in IS and SCI and to establish new strategies for preventing and treating these devastating diseases.
Production of Carbon Black in Turbulent Spray Flames of Coal Tar Distillates

Conventional carbon black production occurs by pyrolysis after heavy aromatic feedstock is injected into the post-combustor region of furnace black reactors. The current work examines the conversion of the coal tar distillate in turbulent spray flames to demonstrate a more compact reactor configuration. Coal tar distillates diluted in toluene is atomized and burned in a standardized flame spray synthesis configuration, known as SpraySyn. Flame conditions are characterized by thermocouple, soot pyrometry and image analysis and product particle properties are examined by TEM and Raman spectroscopy. The measured flame temperature corresponds to the range of temperatures used in the furnace black process, but the current synthesis includes oxidizing conditions and faster residence times. The resulting carbon black particles are aggregates with primary particle sizes on the small end of the carbon black size spectrum, according to analysis of TEM images. Carbon black, formed under a range of flame temperatures, show Raman spectra with features resembling typical carbon black materials. Conversion of coal tar distillate to carbon black by direct flame synthesis may be a scalable method to produce high-surface area grades without a conventional pyrolysis reactor stage.
Multi-Objective Approach for User Association to Improve Load Balancing and Blockage in Millimeter Wave Cellular Networks

One of the leading enabling technologies of 5G wireless networks is to use the millimeter wave spectrum band. Despite its large and wide frequency bandwidth, the obtained data rate can be diminished due to link blockage in this frequency band. In this paper, we formulate a bi-objective optimization problem to optimize user association in cellular networks with millimeter wave enabled base stations. The two objectives to minimize are maximum base station utility and blockage score (to indicate the chance of a link getting blocked). We simulate three different scalarization methods to turn a bi-objective vector into a scalar. Since the combinatorial bi-objective problem is NP-Hard, we conduct Lagrangian dual analysis on all of the scalarization methods. Solving the dual problem decreases the time complexity of the solver algorithm, but the solution has a distance from the optimal point created by solving the primal. We also solve the primal optimization problem with a single objective optimization tool. Compared to the time complexity of the primal problem of scalarization methods, the time complexities of solutions to the dual problems are lower. The results show that our solution to the bi-objective optimization problem has a better outcome in terms of the number of link blockage and the maximum base station utility compared to optimizing each objective alone.
An Integrated Approach for Bearing Health Indicator and Stage Division Using Improved Gaussian Mixture Model and Confidence Value

Bearing prognosis is of paramount and practical importance for rotating machinery. In this article, we propose an integrated approach for bearing performance degradation assessment. First, we propose an improved clustering algorithm, called the Hellinger distance-based regularized Gaussian mixture model (HRGMM). In this model, the Hellinger distance is incorporated to measure the similarity between probability distributions (PDs) of raw data. The manifold regularized GMM is then enhanced to differentiate bearing performance changes. Second, we construct a new health indicator (HI) that combines the Jensen–Rényi divergence and improved confidence value to normalize the difference in PDs between the test condition and healthy condition. It aims to solve the problems of the insensitivity of HI to the incipient defect and its highly fluctuating behavior as the bearing deteriorates over time. Clustering results of the experimental and real bearings show that the HRGMM successfully distinguishes different health states, damage severities, and working conditions. The results of two run-to-failure bearing tests demonstrate that, for each bearing, the HI based on HRGMM drops in a smooth and monotonic manner and accurately identify the incipient defect as the beginning of the slight degradation. Moreover, it can automatically mark the sharp state declines as the beginning of severe degradation and failure stages so that appropriate warnings can be set for follow-up maintenance.
Synchronized Data Collection for Human Group Recognition

It is commonplace for people to perform various kinds of activities in groups. The recognition of human groups is of importance in many applications including crowd evacuation, teamwork coordination, and advertising. Existing group recognition approaches require snapshots of human trajectories, which is often impossible in the reality due to different data collection start time and frequency, and the inherent time deviations of devices. This study proposes an approach to synchronize the data of people for group recognition. All people’s trajectory data are aligned by using data interpolating. The optimal interpolating points are computed based on our proposed error function. Moreover, the time deviations among devices are estimated and eliminated by message passing. A real-life data set is used to validate the effectiveness of the proposed approach. The results show that 97.7% accuracy of group recognition can be achieved. The approach proposed to deal with time deviations was also proven to lead to better performance compared to that of the existing approaches.
Spatial distribution of lichen communities and air pollution mapping in a tropical city: Medellín, Colombia

Introduction: Enough scientific evidence is available on the harmful effects of air pollution on the health of human beings, fauna, flora, and ecosystems in general. The mechanical and electronical monitoring networks are the first option for the air quality diagnosis, but they do not allow a direct and precise assessment of the impacts in living organisms that may result from the exposure to air pollutants. Objective: To evaluate the changes in the composition of corticulous lichen communities as a response to various stress factors in areas with different levels of air quality to diagnose the state of pollution or intervention in an area with a more complete option. Methods: Air quality contrasts and changes in richness and coverage of corticulous lichens in response to different stress factors, such as land use and distance to roads, in three different biomonitoring areas, were evaluate using GIS, and the data are presented in an easy-to-understand grey scale coded isoline map. Results: Indicators such as lichen coverage (R= -0.4) and richness (R= -0.7) are inverse correlated with PM2.5 concentrations in each area. A total of 110 lichen species were identified, being Phaeophyscia chloantha (Ach.) Moberg and Physcia poncinsii Hue the most frequent species (present in 38 and 33 % of the 86 sampled phorophytes, respectively). The intra-area relationships of lichen richness exhibit significant relationships with regards to the land use and distance to roads (with correlations coefficients greater than 0.5) and the Simpson index was higher than 0.9, in places with better conditions in terms of air quality and microenvironments, likewise the resistance factors calculated suggest that the most sensitive species can be found in environments with a lesser degree of disturbance. Conclusion: These evaluations represent more criteria elements for the diagnosis of the environmental health in the biomonitoring areas.