Miracle-dz/UniFAR-FTUs huggingface dataset:
Flexoelectric and surface effects on a cracked piezoelectric nanobeam: Analytical resonant frequency response

A nanoscale beam model containing defect under the piezoelectricity considering the surface effects and flexoelectricity is established on the framework of EulerBernoulli theory. The governing equations of motion and related boundary conditions are derived by using Hamilton’s principle. The imperfect nanobeam is modeled by dividing the beam into two separate parts that are connected by a rotational and a longitude spring at the defect location. Analytical results on the free vibration response of the imperfect piezoelectric nanobeam exhibit that the flexoelectricity and the surface effects are sensitive to the boundary conditions, defect position, and geometry of the nanobeam. Numerical results are provided to predict the mechanical behavior of a weakened piezoelectric nanobeam considering the flexoelectric and surface effects. It is also revealed that the voltage, defect severity, and piezoelectric material have a critical role on the resonance frequency. The work is envisaged to underline the influence of surface effects and flexoelectricity on the free vibration of a cracked piezoelectric nanobeam for diverse boundary conditions. It should be mentioned, despite our R. Sourkiprevious works, an important class of piezoelectric materials used nowadays and called piezoelectric ceramics is considered in the current study.
Ligand Decorated Embelin Loaded PLGA Nanoparticles for Management of Alcohol Induced Hepatotoxicity

Preparation of surface modified Embelin loaded nanoparticles (GA-PEG-PLGA) for the management of hepatotoxicity. Surface modified Embelin loaded GA-PEG-PLGA NPs were evaluated by NMR, FTIR, TEM techniques and in vitro release studies. The biodistribution of the nanoparticles was assessed by High-performance liquid chromatography (HPLC), and the cellular uptake study was evaluated using Hep G2 cells (liver cells lines). The hepatoprotecttive effect of the surface modified Embelin loaded GA-PEG-PLGA NPs was investigated in-vitro and in-vivo. The surface modified Embelin loaded GA-PEG-PLGA nanoparticles significantly increases the uptake of drug in liver by 2.5 folds more than plain drug.
The 3rd Dimension of Innovation Processes

Architects understand and visualize organizations and processes differently from their counterparts in management disciplines. With the increasing complexities of markets and blurring of organizational boundaries, linear models of innovation processes are unable to account for the range of possible interrelations and interdependencies. Design-led disciplines have become of interest in providing frames and ‘design’ structures for fostering innovation. Though it deals specifically with the conceptualization and realization of R&D and innovation centres, architecture has been largely overlooked in this regard. This paper explains how architects’ approach to reframing complexities, focussing on social interactions and shaping invisible patterns prior to building design offers new perspectives for innovation research. It critically reviews the changing context of innovation and relational models in the literature, and outlines the relevance of integrating spatial proximities and time for a constructive 3-dimensional representation. Via two case studies, the basic principles for the development of an integrative approach are sketched out and suggestions made for further research. The specific skill-set and thinking of architects offers a 3rd dimension of innovation processes.
Data Transmission Method on a Room Condition Telemonitoring Application (IoT)

Data transmission system in IoT applications such as telemonitoring, using cable or wireless, requires a robust data transmission method. In this paper, a room condition telemonitoring application has been made where all data are read from raspberry pi, and sent to a pc server every minute using LAN and Wifi media, then update to a webserver. The data are sent using the method proposed in this paper which using the UDP mechanism with several improvements. Experiments have been done using LAN and Wifi, and it is found that the data can be received perfectly, although there are interferences from communication media. The average processing time on a raspberry pi is 19 ms, while the average processing time on the pc server is 5 us. In addition, the average processing speed of the transmission data from raspberry pi to a pc server until ack is received by raspberry pi using LAN media is 0.04 second, while using Wifi media is 0.08 seconds. Based on the experiments, it was found that the proposed method was successfully implemented in the room condition telemonitoring.
Using Geographically Weighted Choice Models

7 In this paper, we investigate the use of geographically weighted choice models for 8 modelling spatially clustered preferences. We argue that this is a useful way of 9 generating highly-detailed spatial maps of willingness to pay for environmental 10 conservation, given the costs of collecting data. The data used in this study come from a 11 discrete choice experiment survey of public preferences for the implementation of a new 12 national forest management and protection programme in Poland. We combine these 13 with high-resolution spatial data related to local forest characteristics. Using locally 14 estimated discrete choice models we obtain location-specific estimates of willingness to 15 1 Wiktor Budziński and Mikołaj Czajkowski are both with the Department of Economics, University of Warsaw, Poland. Email: mc@uw.edu. pl for correspondence. Danny Campbell is in the Economics Division of Stirling Management School, University of Stirling, UK. Urška Demšar and Nick Hanley are both with the School of Geography and Sustainable Development, University of St. Andrews, UK. This study uses data collected as the part of the POLFOREX project (‘Forests as a Public Good. Evaluation of Social and Environmental Benefits of Forests in Poland to Improve Management Efficiency’; PL0257) funded by EEA Financial Mechanism, Norwegian Financial Mechanism and Polish Ministry of Science and Higher Education. Funding support is gratefully acknowledged. MC gratefully acknowledges the support of the Polish Ministry of Science and Higher Education and the National Science Centre of Poland (project 2015/19/D/HS4/01972). WB gratefully acknowledges the support of the Foundation for Polish Science (FNP). We thank two referees for their comments on previous versions of this paper. Accepted Manuscript (Journal of Agricultural Economics) pay (WTP). Variation in these estimates is explained by characteristics of the forests 1 close to where respondents live. These results are compared with those obtained from a 2 more typical, two stage procedure which uses Bayesian posterior means of the mixed 3 logit model random parameters to calculate location-specific estimates of WTP. We find 4 that there are indeed strong spatial patterns to the benefits of changes to the 5 management to national forests. People living in areas with more species-rich forests 6 and those living nearer bigger areas of mixed forests have significantly different WTP 7 values than those living in other locations. This kind of information potentially enables 8 a better distributional analysis of the gains and losses from changes to natural resource 9 management, and better targeting of investments in forest quality. 10
Assessment of honeycomb core condition in composite sandwich panels by means of guided

The work presented in this paper focuses on the integrity assessment of composite sandwich panels with honeycomb cores. Proposed technique is based on anomalies of propagating guided waves and processing of full wavefield signals registered by scanning laser vibrometer. Disbonding between a back/front panel and a core was investigated. Guided wave packets were excited at different frequencies by piezoelectric disc attached to opposite to measured side of the specimen. Sequential triggered measurements were conducted on dense mesh of points at the face sheet by laser vibrometer so that full wavefield data was received. Obtained data was further processed to create damage influence maps by means of simple RMS method or more advanced adaptive wavenumber filtering technique.
VALUES OF YOUNG EMPLOYEES: Z-GENERATION PERCEPTION

The current paper aims to analyse the importance of values of young employees now and in five years period. In order to achieve the aim, the questionnaire consisting of fifty statements was developed and disseminated between the Latvian students. The sample size was 392, which shows that the results represent the whole populations. For data processing, factor analysis was chosen as a tool. The data factorability was assessed via Bartlett’s Test of Sphericity, Kaiser-Myer-Olkin (KMO) statistic, initial estimates of communality and the anti-image correlation matrix. The factors were extracted via principal axis factoring (PAF). The number of factors was determined by the scree plot/Kaiser’s rule and was equal to five in both cases. The results showed the for the young employees the essential values today are those connected to the personality trait. However, in five years, the essential values would be those that are linked to professional development.
SSVEP-based BCI with visual stimuli from LCD screen applied for wheelchair control: offline and online investigations

Brain Computer Interfaces (BCIs) have been shown as a promising technology in the current years, especially for those wheelchair users affected by motor injuries or diseases. SteadyState Visual Evoked Potentials (SSVEP)-based BCI systems are widely used for many applications, such as keyboard and robot control, because of its short response time and ease of use. SSVEP-based BCIs use brain responses to any visual stimulus flickering at a specific frequency as input command to an external application or device. Although some SSVEPbased BCI applied to wheelchair control have shown promising results, there are specific features of the system that should be analyzed and discussed aiming to increase classification accuracy. This dissertation aims to develop and investigate the performance a SSVEP-based BCI system using LCD monitor as visual stimulator applied for wheelchair control. Two experiments were performed (offline and online). Through the offline experiment, performed by 9 participants, it was possible to identify EEG optimal channels, adequate window length for signal processing, and target location on the LCD screen. In the online experiment, 9 EEG channels (PO3, PO4, PO5, PO6, PO7, PO8, O1, O2 and Oz) were used to record the brain signal while using an interface with 5 stimuli targets (15, 12, 6.67, 8.57 e 10 Hz) placed on the top, bottom, right, left and center of the screen. Four participants were positioned in front the LCD screen where the interface was executed. The interface was developed in Python language and, after collecting the signal, it was responsible to perform filtering, windowing, feature extraction (FFT), and classification (SVM). The results showed a good performance while using a 3 seconds time-window with 250 ms of overlap. Accuracy rates from online experiments were high, which allowed the control of a powered wheelchair. This system can provide independency and increase quality of life of wheelchair users. Future works involve adaptations and improvements of the system to increase efficiency and provide more reliability to the user.
THE APPLICATION OF GENETIC ALGORITHM TO OPTIMIZE XGBOOST ALGORITHM IN MBR SIMULATION

Membrane bio-reactor (MBR) is one of the mainstream technologies of modern wasted-water treatment, but membrane fouling is a key factor which restricts the development of MBR. The formation of membrane fouling directly leads to a decrease in membrane flux. As one of the important parameters to measure membrane fouling, membrane flux is the focus and difficulties of membrane fouling research. In this paper, XGBoost algorithm is used to simulate and predict MBR membrane flux. In view of the shortcomings of XGBoost with many parameters, combined with the characteristics of genetic algorithm (GA), such as strong global search ability and fast convergence speed, the parameters of XGBoost are optimized and adjusted. By analyzing the prediction results of GA-XGBoost algorithm, and comparing with the experimental data, the results show that GA-XGBoost neural network prediction model is superior to XGBoost algorithm prediction model in the prediction of MBR membrane flux, with higher accuracy.
Side Differences in the Skull of Sheep: An Assessment by Geometric Morphometrics

Effects of perturbations during development can be due to environmental and/or genetic factors, resulting in increased developmental instability which in turn can be expressed as fluctuating asymmetry (FA), defined as the non-directional deviation (right-left differences) from bilateral symmetry. However, other asymmetry types can appear, such as and directional asymmetry (DA), characterized by a distribution skewed to one side (right or left) at the, which is originated as a response to external stimuli that affect differentially on both sides of the organism. In order to describe asymmetric patterns in the ovine skull, we studied 165 specimens from animals belonging to the sheep breed “Navarra” from North Spain, using geometric morphometric methods. On digital pictures, we analyzed two midline and 8 bilateral two-dimensional landmarks on skull dorsal aspect. Results showed that FA accounted for a reduced amount of total variation, while DA explained most of it. We suggest that the presence of side differences due to lateralized muscular function (mastication) is the most important factor in skull asymmetry. Obtained results should provide a basis for relating asymmetries to the mechanics of cranial skeletum in sheep. Original Research Article Parés-Casanova et al.; ARRB, 34(2): 1-7, 2019; Article no.ARRB. 53713 2
Maximize AUC in Default Prediction: Modeling and Blending

In this paper we present models and blending algorithms to maxmize the Area Under Receiver Operating Characteristic (ROC) curve in default prediction. We summarize all techniques and algorithms we have applied in the Give Me Some Credit competition so that future users can benefit from our experiences in this competition, including feature creation algorithms, single model constructions and blending algorithms. In particular, in this paper we highlight the following aspects: (i) different feature creation methods we explored, (ii) diverse packages utilized for single model building and the parameter tuning for each model, (iii) different blending, and (iv) additional postprocessing methods.
Development of Low-Cost, Non-Obtrusive Electrical Impedance Tomography Device for Liquid-Gas Flow Visualization

The high cost of flow visualization equipment on the market hinders more active exploration in flow science. This paper presents a development of low-cost, nonobtrusive electrical impedance tomography (EIT) device for two-phase (liquid-gas) flow visualization. The device consists of three main hardware; an Arduino microcontroller as processor and communicators between components, a customized printed circuit board to control current injection and voltage measurement, and sensors band which consists of sixteen copper electrodes. During testing, the sensors band was enclosed around a cylindrical phantom tank filled with water. The sensing field then was stimulated by injecting current to the sensors of copper electrodes. Next, the measured voltage values were imported to MATLAB and interfaced with electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS) software for reconstruction of test images. The system capitalized on the different conductivity values of water and air, with the reconstructed images showed excellent agreement with the test images. 
Morphologic cirrhosis diagnosis from Ultrasound

Cirrhosis is an endemic diseases across the world that leads to observed liver contour irregularities in the Ultrasound images, which can be used to detect and confirm the pathologic conditi on. In this work these irregularities are semi-automatically s egmented and quantified in order to help the physician in the diagnosis. Results obtained from real data have shown the abil ity of the method to detect the disease. The ultimate goal is to use these irregularity features join tly with other features extracted from the liver parenchyma to d esign a highly discriminative classifier for liver cirrhosis, ste atosis and other diffuse liver diseases.
Strength, Durability, and Micro Structural Properties of Concrete Incorporating MS and GCBA as Sand Substitute

In this experimental study, GCBA (Graded coal bottom ash) from Eklahare thermal power station, Nashik was used, as sand substitute with micro silica (MS) in concrete. Concrete specimens were casted by substituting GCBA with sand in different proportions (40 to 100%). for each substitution of GCBA, micro silica (MS) was added at 2 to 8% by weight of cement used in reference mix. The fresh and hardened properties of GCBA were studied along with the micro structural analysis (SEM) at 7, 28 and 56 days. It was observed that the workability of fresh concrete was considerably increased with increase in MS but was less than reference concrete. The all hardened properties of concrete such as compressive strength, flexural strength, split tensile strength, density, modulus of elasticity and permeability were observed more than reference concrete up to 90% substitution by GCBA with 8% MS whereas for 100% substitution with 8% MS was marginally reduced in strength compared with reference concrete.
Estudio de las propiedades, estructurales, morfológicas y ópticas de nanopartículas de Cr2O3 sintetizadas por procesos de combustión de un solo paso y diferentes combustibles Studies on structural, morphological, and optical properties of Cr2O3 nanoparticles: synthesized via one step combustion 

This research presents a novel one–step solution combustion synthesis to obtain nano-structured Cr2O3 from chrome nitrate solution and one fuel such as aspartic acid (Asp) or Lysine (Lys), or trihydroxymethylaminoPALERMO, V. ; MERINO, M.C. G. ; VÁZQUEZ P., et al. revista Matéria, v.24, n.3, 2019. methane (Tris) or ethylenediaminetetraacetic acid (Edta). Once obtained, the ashes were calcined at 500°C. The powders were characterized by x-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), infrared spectroscopy with Fourier transform (FTIR), UV-Visible Spectroscopy (UV-VIS) spectroscopy and Brunauer–Emmett–Teller (BET) techniques. These powders will be used in solar absorbing surfaces: in composites (o cermets) and painted coatings. Within the obtained ashes and calcined powders, it was identified a Cr2O3 crystalline structure corresponding to the rhombohedral system and to the R-3c spatial group. The average crystallite size was determined for ashes and calcined powders, this value was in nanometric range between 29 and 45 nm, where for ashes were in general minor than calcined powders in all cases. It is probable that with an increment of the temperature, crystallite size would grow. A specific area of 167 m/g was determined for asp-ashes. This was a highest value observed in specific literature and it could be used in catalysis reactions, while the area values of ashes was higher than calcined powders value for each fuel. The average particle size observed through TEM resulted in 50 nm to 100 nm approximately. The determined Energy band gap resulted in 3.055eV to 3.078 eV approximately. The Energy band gap slightly increased with calcination temperature. Further trials and investigation will confirm the mentioned tendencies.
An AI Integrator for Efficient Customization of Collaborative Robots

Project Details: For my project I will be pursuing next semester, I will be working with Changliu Liu, an assistant professor in the Robotics Institute. I will also be working with Abulikemu Abuduweili. The main topic of my project is human-robot interaction, particularly in a collaborative sense. As demands for human-robot collaboration increase across different domains like industry, health care, education, etc., the need for an efficient method of customizing such robots grows more apparent. If robots are meticulously designed to perform a single specific task, then a new task in a new environment will require a complete reprogramming, and may even require the underlying hardware to be changed. Obviously, this is very expensive and suboptimal, so efficient customization is the first big key to improving on these collaborative robots, or co-robots. Not only is efficiency important in the design of robots, but safe operation is also essential to consider to prevent potentially harmful interactions between the human and the robot. A proposed method for maintaining a safe collaborative environment is to incorporate human motion prediction into the robot’s decision-making. Accurate human motion prediction will allow robots to plan their trajectories according to how the human is likely to move. This, however, is a very difficult problem in many ways, as different people behave differently, especially in different tasks. Thus, human motion prediction will occupy one portion of the overall pipeline of the co-robot system. Another large part of the pipeline involves the robot’s skill learning, including everything from learning the tasks it needs to perform to adapting to the human’s movements and planning its trajectory in real time. It is very difficult to pre-program robots to perform every single task imaginable. So, work to be done in this area will involve two main steps: an initial stage of encoding, where skills shared universally across all tasks are learned by the robots, and an on-site stage of learning, where the specific task is taught to the robot. A proposed method of doing this is via human demonstration, where the robot observes two humans performing the task collaboratively, and mimics the human behavior. My project will focus specifically on high fidelity behavior prediction of intelligent agents, building on previous research on the Modified Extended Kalman Filter with Exponential Moving Average and Dynamic Multi-Epoch strategy (MEKF​EMA-DME​). In particular, I will investigate possible applications of using such a strategy to finetune models in an offline setting, where time and memory complexity are not as restricted as in an online setting. We are specifically training behavior prediction models, but we may investigate applications to online learning problems in general.
Second order directional shape derivatives of integrals on submanifolds

We compute first and second order shape sensitivities of integrals on smooth submanifolds using a variant of shape differentiation. The result is a quadratic form in terms of one perturbation vector field that yields a second order quadratic model of the perturbed functional. We discuss the structure of this derivative, derive domain expressions and Hadamard forms in a general geometric framework, and give a detailed geometric interpretation of the arising terms.