Miracle-dz/UniFAR-FTUs huggingface dataset:
Acceptability of an mHealth App Intervention for Persons With Type 2 Diabetes and its Associations With Initial Self-Management: Randomized Controlled Trial

Background Mobile health interventions are increasingly used in health care. The level of acceptability may indicate whether and how such digital solutions will be used. Objective This study aimed to explore associations between the level of acceptability of a mobile diabetes app and initial ability of self-management for patients with type 2 diabetes. Methods Participants with type 2 diabetes were recruited from primary health care settings to a 3-armed randomized controlled trial in the Norwegian study in the RENEWING HEALTH project. At the 1-year follow-up, 75 out of 101 participants from the intervention groups completed an acceptability questionnaire (The Service User Technology Acceptability Questionnaire). In the randomized controlled trial, the 2 intervention groups (n=101 in total) received a mobile phone with a diabetes diary app, and one of the groups received additional health counseling given by telephone calls from a diabetes specialist nurse (n=50). At baseline, we collected clinical variables from medical records, whereas demographic data and self-management (The Health Education Impact Questionnaire) measures were self-reported. Log data from the use of the app by self-monitoring were registered continuously. Associations between initial ability to self-manage at baseline and acceptability of the diabetes diary app after 1 year were analyzed using linear regression. Results We found statistically significant associations between 5 of the 8 self-management domains and perceived benefit, one of the acceptability factors. However, when adjusting for age, gender, and frequency of use, only 1 domain, skill and technique acquisition, remained independently associated with perceived benefit. Frequency of use of the app was the factor that revealed the strongest association with the acceptability domain perceived benefit. Conclusions Our findings indicate that persons with diabetes may accept the app, despite its perceived benefit being associated with only one of the 8 domains of their initial level of self-management. Trial Registration ClinicalTrials.gov NCT01315756; https://clinicaltrials.gov/show/NCT01315756 (Archived by WebCite at http://www.webcitation.org/6z46qPhWl)
Schematic Invariants by Reduction to Ground Invariants

Computation of invariants, which are approximate reachability information for state-space search problems such as AI planning, has been considered to be more scalable when using a schematic representation of actions/events rather than an instantiated/ground representation. A disadvantage of schematic algorithms, however, is their complexity, which also leads to high runtimes when the number of schematic events/actions is high. We propose algorithms that reduce the problem of finding schematic invariants to solving a smaller ground problem.
Associative Memory with Class I and II Izhikevich Model

Spiking neural network is a system that qualitatively reproduce the nervous system. It was shown in previous researches that the performance of associative memory task in all-to-all connected networks is higher when they are composed of Class II neurons than Class I neurons. The Izhikevich model in its Class II mode, however, does not have this performance boost. In this study, we focus on phase resetting curve as an index that reflects neuronal properties related to neuron classes in detail.
Transcranial sonography of the substantia nigra in Japanese patients with Parkinson's disease or atypical parkinsonism: clinical potential and limitations.

OBJECTIVE There is growing interest in the use of transcranial sonography (TCS) of the substantia nigra (SN) in patients with Parkinson's disease (PD), as it has been reported that SN hyperechogenicity may be present in about 90% of PD patients. However, TCS of the SN has not been applied in Japanese patients, and its clinical potential has not been determined. PATIENTS AND METHODS TCS of the SN was performed in patients with PD, progressive supranuclear palsy (PSP), multiple system atrophy (MSA), and essential tremor (ET), and age-matched controls. Ultrasound images of the SN were assessed using semi-qualitative estimation criteria by two investigators unaware of clinical diagnosis. RESULTS SN hyperechogenicity was observed in approximately 83% of accessible SNs in Japanese PD patients. In comparison, SN hyperechogenicity was less frequently observed in healthy subjects or in patients with PSP, MSA, and ET. However, the rate of successful recording of the SN by TCS decreased prominently with advancing age, particularly in females. CONCLUSION The present study confirmed that TCS of the SN is potentially useful in the investigation of Japanese patients, and it provides a better differential diagnosis between PD and atypical parkinsonism. The recording failure of TCS in aged, particularly female subjects, may limit the clinical potential of TCS of the SN in Japanese patients.
Design Method for the Coil-System and the Soft Switching Technology for High-Frequency and High-Efficiency Wireless Power Transfer Systems

Increasing the resonant frequency of a wireless power transfer (WPT) system effectively improves the power transfer efficiency between the transmit and the receive coils but significantly limits the power transfer capacity with the same coils. Therefore, this paper proposes a coil design method for a series-series (SS) compensated WPT system which can power up the same load with the same DC input voltage & current but with increased resonant frequency. For WPT systems with higher resonant frequencies, a new method of realizing soft-switching by tuning driving frequency is proposed which does not need to change any hardware in the WPT system and can effectively reduce switching losses generated in the inverter. Eighty-five kHz, 200 kHz and 500 kHz WPT systems are built up to validate the proposed methods. Experimental results show that all these three WPT systems can deliver around 3.3 kW power to the same load (15 Ω) with 200 V input voltage and 20 A input current as expected and achieve more than 85% coil-system efficiency and 79% system overall efficiency. With the soft-switching technique, inverter efficiency can be improved from 81.91% to 98.60% in the 500 kHz WPT system.
Production and Characterization of Nanoparticle Based Hyaluronate Gel Containing Retinyl Palmitate for Wound Healing.

BACKGROUND Wound healing is a biological process that can get in a state of pathologic inflammation, requiring the use of specific medications able to promote proper tissue repair. OBJECTIVE The study describes the production and characterization of nanoparticle based gel for wound healing treatment designed to deliver hyaluronic acid and retinyl palmitate onto the skin. METHODS Tristearin solid lipid nanoparticles and nanostructured lipid carriers based on a tristearin and caprylic/capric triglyceride mixture were produced and characterized. Gel spreadability and viscosity were investigated. Drug diffusion and "in vitro" wound healing were assessed by Franz cell and scratch wound assay in keratinocytes. RESULTS Cryogenic transmission electron microscopy evidenced flat discoid nanoparticles. Photon correlation spectroscopy analysis indicated homogeneous dimensional distribution and mean diameter 132±46 nm. X-ray evidenced a lamellar inner structure of lipid nanoparticles. Nanostructured lipid carriers, being based on a heterogeneous solid/ liquid lipid mixture, could better solubilize retinyl palmitate and control its stability. The hyaluronic acid directly added into nanoparticles' dispersion enabled to obtain a shear-thinning gel suitable for cutaneous administration. Retynil palmitate diffusion was slower from the nanoparticulate gel with respect to the plain nanoparticle dispersion. The "wound healing" effect of nanoparticulate gel containing retinyl palmitate and hyaluronic acid, analyzed in HaCaT cells, showed significant differences in wounded areas between treated and control cells during the first 24 h postwounding suggesting a synergic effect of retinyl palmitate and hyaluronic acid in "in vitro" wound healing. CONCLUSIONS This study suggests that a nanoparticle based hyaluronate gel containing retinyl palmitate can be efficiently used for wound healing.
Neural network modeling for near wall turbulent flow

A neural network methodology is developed in order to reconstruct the near wall field in a turbulent flow by exploiting flow fields provided by direct numerical simulations. The results obtained from the neural network methodology are compared with the results obtained from prediction and reconstruction using proper orthogonal decomposition (POD). Using the property that the POD is equivalent to a specific linear neural network, a nonlinear neural network extension is presented. It is shown that for a relatively small additional computational cost nonlinear neural networks provide us with improved reconstruction and prediction capabilities for the near wall velocity fields. Based on these results advantages and drawbacks of both approaches are discussed with an outlook toward the development of near wall models for turbulence modeling and control.
On the Convergence of Stochastic Gradient Descent with Adaptive Stepsizes

Stochastic gradient descent is the method of choice for large scale optimization of machine learning objective functions. Yet, its performance is greatly variable and heavily depends on the choice of the stepsizes. This has motivated a large body of research on adaptive stepsizes. However, there is currently a gap in our theoretical understanding of these methods, especially in the non-convex setting. In this paper, we start closing this gap: we theoretically analyze in the convex and non-convex settings a generalized version of the AdaGrad stepsizes. We show sufficient conditions for these stepsizes to achieve almost sure asymptotic convergence of the gradients to zero, proving the first guarantee for generalized AdaGrad stepsizes in the non-convex setting. Moreover, we show that these stepsizes allow to automatically adapt to the level of noise of the stochastic gradients in both the convex and non-convex settings, interpolating between $O(1/T)$ and $O(1/\sqrt{T})$, up to logarithmic terms.
Recognition of Activities from Eye Gaze and Egocentric Video

This paper presents a framework for recognition of human activity from egocentric video and eye tracking data obtained from a head-mounted eye tracker. Three channels of information such as eye movement, ego-motion, and visual features are combined for the classification of activities. Image features were extracted using a pre-trained convolutional neural network. Eye and ego-motion are quantized, and the windowed histograms are used as the features. The combination of features obtains better accuracy for activity classification as compared to individual features.
Spatially Explicit Metrics of Species Diversity, Functional Diversity, and Phylogenetic Diversity: Insights into Plant Community Assembly Processes

Spatial processes underlie major species coexistence mechanisms. A range of spatial analysis techniques are increasingly applied to data of fully mapped communities to quantify spatial structures in species and phylogenetic and functional diversity at some given spatial scale with the goal of gaining insights into processes of community assembly and dynamics. We review these techniques, including spatial point pattern analysis, quadrat-based analyses, and individual-based neighborhood models, and provide a practical roadmap for ecologists in the analysis of local spatial structures in species and phylogenetic and functional diversity. We show how scale-dependent metrics of spatial diversity can be used in concert with ecological null models, statistical models, and dynamic community simulation models to detect spatial patterns, reveal the influence of the biotic neighborhood on plant performance, and quantify the relative contribution of species interactions, habitat heterogeneity, and stochastic processe.
VESTIGIOS DE YESO. LOS REVESTIMIENTOS CONTINUOS HISTÓRICOS EN LAS FACHADAS DE LA VALENCIA INTRAMUROS: ESTUDIO HISTÓRICO, CARACTERIZACIÓN Y PROPUESTAS DE CONSERVACIÓN

En el presente estudio se indican los principales resultados referentes a la investigacion realizada sobre los revestimientos continuos historicos en las fachadas de la Valencia intramuros (Espana), concretamente en los barrios de El Carme, Sant Francesc- Universitat, El Mercat, La Seu-Xerea, y Velluters. En esta zona casi la totalidad de los edificios residenciales de finales del siglo XVIII hasta principios del siglo XX estan revestidos por capas que protegen y a la vez decoran sus fabricas. Por tanto, se convierten en un rasgo distintivo de la imagen de la ciudad historica y de la tecnica constructiva local, y mas cuando se ha podido descubrir su verdadera materialidad caracterizada por el uso de yeso. Esta tesis doctoral pretende contribuir a la puesta en valor de los revestimientos de la ciudad partiendo del conocimiento de su historia, de la definicion de su caracterizacion material y tecnica, y de la necesaria conservacion de los vestigios que de ellos quedan. Se consideran vestigios porque no son simples restos de algo material sino son tambien indicios de una memoria constructiva olvidada. Por lo tanto, el objetivo central de la investigacion ha sido profundizar en el conocimiento de sus caracteristicas, peculiaridades, singularidades y particularidades para evidenciar los multiples valores: historico, arquitectonico, cultural, material, tecnologico, constructivo, etc. que atesoran. En este sentido, el estudio se divide en tres dimensiones temporales que han hecho posible conocer el pasado, el presente y el futuro de este elemento constructivo, aplicando un enfoque multidisciplinar que auna los fundamentos, conocimientos y contenidos clave proporcionados por la Historia de la Arquitectura y de la Construccion, la Restauracion Arquitectonica, la Geografia y sobre todo la Geologia. De este modo, en la primera parte se intenta descubrir y conocer los revestimientos continuos historicos desde una perspectiva historica y constructiva a traves del analisis de fuentes bibliograficas y archivisticas, prestando especial atencion al yeso como material de la tradicion valenciana. En la segunda parte se pretende analizar e interpretar los revestimientos continuos que revisten las fachadas de los edificios historicos de la ciudad partiendo del analisis quimico y mineralogico de muestras pertenecientes a excavaciones arqueologicas y a edificios historicos, para asi poder caracterizarlos y conocer su materialidad. Asimismo, ello ha hecho posible realizar una re-lectura analitica de toda la informacion obtenida gracias a su sistematizacion en fichas, asi como establecer una posible evolucion cronologica de los revestimientos de la ciudad. Por ultimo, en la tercera parte se aborda como intervenir y proteger este elemento constructivo proponiendose pautas a seguir y materiales mas compatibles con su realidad constructiva asi como mecanismos para intentar evitar su constante perdida.
Building Task-Oriented Dialogue Systems for Online Shopping

We present a general solution towards building task-oriented dialogue systems for online shopping, aiming to assist online customers in completing various purchase-related tasks, such as searching products and answering questions, in a natural language conversation manner. As a pioneering work, we show what & how existing NLP techniques, data resources, and crowdsourcing can be leveraged to build such task-oriented dialogue systems for E-commerce usage. To demonstrate its effectiveness, we integrate our system into a mobile online shopping app. To the best of our knowledge, this is the first time that an AI bot in Chinese is practically used in online shopping scenario with millions of real consumers. Interesting and insightful observations are shown in the experimental part, based on the analysis of human-bot conversation log. Several current challenges are also pointed out as our future directions.
0 Cashtag piggybacking : uncovering spam and bot activity in stock microblogs on Twi

Microblogs are increasingly exploited for predicting prices and traded volumes of stocks in nancial markets. However, it has been demonstrated that much of the content shared in microblogging platforms is created and publicized by bots and spammers. Yet, the presence (or lack thereof) and the impact of fake stock microblogs has never systematically been investigated before. Here, we study 9M tweets related to stocks of the 5 main nancial markets in the US. By comparing tweets with nancial data from Google Finance, we highlight important characteristics of Twier stock microblogs. More importantly, we uncover a malicious practice perpetrated by coordinated groups of bots and likely aimed at promoting low-value stocks by exploiting the popularity of high-value ones. Our results call for the adoption of spam and bot detection techniques in all studies and applications that exploit user-generated content for predicting the stock market.
Enabling Edge Analytics of IoT Data: the Case of LoRaWAN

LoRaWAN is a promising network solution for various application domains, especially in developing countries. While its network architecture is highly distributed, the network architecture aims at aggregating data into a centralized location, mainly the cloud-based data center. With such an architecture, we can bring data from distributed sensing sources to centralized cloud-based data andanalytics services, however, it does not foster edge analytics atop LoRaWAN, which is highly suitable for scenarios in developing countries due to connectivity and cost constraints. We outline a conceptual architecture and design augmenting LoRaWAN software architecture for edge analytics. In this paper we develop techniques for edge analytics working with LoRaWAN core network functions. We present key principles of shared data for edge analytics with LoRaWAN. Based on that, we describe main services, their interactions and data models for connecting edge analytics to LoRaWAN infrastructures. We present our prototype to illustrate our implementation.
A Wavelet-based Data Analysis to Credit Scoring

Nowadays, the dramatic growth in consumer credit has made ineffective the methods based on the human intervention, aimed to assess the potential solvency of loan applicants. For this reason, the development of approaches able to automate this operation represents today an active and important research area named Credit Scoring. In such scenario it should be noted how the design of effective approaches represents an hard challenge, due to a series of well-known problems, such as, for instance, the data imbalance, the data heterogeneity, and the cold start. The Centroid wavelet-based approach proposed in this paper faces these issues by moving the data analysis from its canonical domain to a new time-frequency one, where this operation is performed through three different metrics of similarity. Its main objective is to achieve a better characterization of the loan applicants on the basis of the information previously gathered by the Credit Scoring system. The performed experiments demonstrate how such approach outperforms the state-of-the-art solutions.
Leaf-associated bacterial microbiota of coffee and its correlation with manganese and calcium levels on leaves

Abstract Coffee is one of the most valuable agricultural commodities and the plants’ leaves are the primary site of infection for most coffee diseases, such as the devastating coffee leaf rust. Therefore, the use of bacterial microbiota that inhabits coffee leaves to fight infections could be an alternative agricultural method to protect against coffee diseases. Here, we report the leaf-associated bacteria in three coffee genotypes over the course of a year, with the aim to determine the diversity of bacterial microbiota. The results indicate a prevalence of Enterobacteriales in Coffea canephora, Pseudomonadales in C. arabica ‘Obatã’, and an intriguing lack of bacterial dominance in C. arabica ‘Catuaí’. Using PERMANOVA analyses, we assessed the association between bacterial abundance in the coffee genotypes and environmental parameters such as temperature, precipitation, and mineral nutrients in the leaves. We detected a close relationship between the amount of Mn and the abundance of Pseudomonadales in ‘Obatã’ and the amount of Ca and the abundance of Enterobacteriales in C. canephora. We suggest that mineral nutrients can be key drivers that shape leaf microbial communities.
The biomass distribution on Earth

Significance The composition of the biosphere is a fundamental question in biology, yet a global quantitative account of the biomass of each taxon is still lacking. We assemble a census of the biomass of all kingdoms of life. This analysis provides a holistic view of the composition of the biosphere and allows us to observe broad patterns over taxonomic categories, geographic locations, and trophic modes. A census of the biomass on Earth is key for understanding the structure and dynamics of the biosphere. However, a global, quantitative view of how the biomass of different taxa compare with one another is still lacking. Here, we assemble the overall biomass composition of the biosphere, establishing a census of the ≈550 gigatons of carbon (Gt C) of biomass distributed among all of the kingdoms of life. We find that the kingdoms of life concentrate at different locations on the planet; plants (≈450 Gt C, the dominant kingdom) are primarily terrestrial, whereas animals (≈2 Gt C) are mainly marine, and bacteria (≈70 Gt C) and archaea (≈7 Gt C) are predominantly located in deep subsurface environments. We show that terrestrial biomass is about two orders of magnitude higher than marine biomass and estimate a total of ≈6 Gt C of marine biota, doubling the previous estimated quantity. Our analysis reveals that the global marine biomass pyramid contains more consumers than producers, thus increasing the scope of previous observations on inverse food pyramids. Finally, we highlight that the mass of humans is an order of magnitude higher than that of all wild mammals combined and report the historical impact of humanity on the global biomass of prominent taxa, including mammals, fish, and plants.