Miracle-dz/UniFAR-FTUs huggingface dataset:
PROPOSED METHOD FOR IMAGE SEGMENTATION USING GRAPH THEORY

This paper presents an image segmentation technique using graph tools for object detection. Graph theoretical systems have many good features among different segmentation schemes. It organizes the image elements into mathematically and structural form, and makes the problem formulation more flexible, and the computation more efficient. In this paper, the work, consists of two stages, in the first stage we apply the pixel-based labeling algorithm to the binary image, the algorithm works similarly to the eight connectivity labeling, but it is broader than it in terms of the search area, where two (horizontal and vertical) thresholds are first defined so that the search is in a block whose height is the vertical threshold and its width (2 * horizontal threshold), in the second stage the output of the first stage is mapping into an undirected weighted graph, in which each vertex represent region rather than pixel. We evaluate the results by comparing it with other method using (RI) parameter. We use 50 image from online source and image taken from Berkeley database.
From asymmetric dependency to discursive disengagement: How social movements and the media/public talked past each other

Social movement-media/public interaction has been largely examined from the lens of “asymmetric dependency” in which both movements’ representation and self-understanding are mainly shaped by their media and public opinion environment. The introduction of digital technologies, however, has diversified this discursive environment and seemed to reverse the uneven dynamics. Using a case study of a protest campaign organized by Chinese American immigrants, this study demonstrates a new pattern of movement-media/public dynamics that goes beyond the “asymmetric dependency” model or its obverse. In the aftermath of a Chinese American police officer who shot a black man to death, Chinese immigrants stood with him and deliberated on WeChat, a China-based digital platform engineered like a “walled garden. ” The technolinguistic enclosure of the platform facilitated the development of a separate interpretative universe in the WeChatsphere vis-à-vis the one in the mediasphere. Later, even when immigrant protesters confronted the public in the Twittersphere, they continued talking past each other. By unpacking the decoupling processes between movements and the media/public, this study shifts the research focus from understanding their interaction to examining their disengagement, as well as the “filter bubble” effects that contribute to contemporary fragmentation and polarization in political and civic engagements.
Effects of Graphene Layer Size on the Adsorption of Fluids on Graphitized Thermal Carbon Black. A Computer Simulation Study

The adsorption of Lennard-Jones fluids (argon and nitrogen) onto a graphitized thermal carbon black surface was studied with a Grand Canonical Monte Carlo Simulation (GCMC). The surface was assumed to be finite in length and composed of three graphene layers. When the GCMC simulation was used to describe adsorption on a graphite surface, an over-prediction of the isotherm was consistently observed in the pressure regions where the first and second layers are formed. To remove this over-prediction, surface mediation was accounted for to reduce the fluid–fluid interaction. Do and co-workers have introduced the so-called surface-mediation damping factor to correct the over-prediction for the case of a graphite surface of infinite extent, and this approach has yielded a good description of the adsorption isotherm. In this paper, the effects of the finite size of the graphene layer on the adsorption isotherm and how these would affect the extent of the surface mediation were studied. It was found that this finite-surface model provides a better description of the experimental data for graphitized thermal carbon black of high surface area (i.e. small crystallite size) while the infinite-surface model describes data for carbon black of very low surface area (i.e. large crystallite size).
Comparison of machine learning approaches used to identify the drivers of Bakken oil well productivity

Geologists and petroleum engineers have struggled to identify the mechanisms that drive productivity in horizontal hydraulically fractured oil wells. The machine learning algorithms of Random Forest (RF), gradient boosting trees (GBT) and extreme gradient boosting (XGBoost) were applied to a dataset containing 7311 horizontal hydraulically fractured wells drilled into the middle member of the Bakken Formation from 2010 through 2017. The initial goal is to use these data‐driven machine learning algorithms to identify the most important explanatory predictors of well productivity within nine subareas and the composite area. Predictor variables representing initial gas production, the initial 180‐day water cut, and vertical depth vary spatially and are identified with geologically favorable areas. Well‐completion predictors include the well lateral length, number of fracture stages, volume of proppant per stage, and the volume of injected fluids per stage. The performance of methods is compared based on a common test sample. The analysis then examines the comparative predictive performance of the three algorithms for 1330 wells that had initiated production after the initial 7311 well sample had been producing. The computations of predictor importance identified the initial 180‐day water cut and the 30‐day initial gas production predictors as having a dominant influence in most subareas and for the composite area. The relative importance of well completion predictor variables, that is, the number of fracture stages per well, volume of injected proppant per stage, volume of injected fluids per stage, and lateral length, varied considerably across the subareas. For the common test or holdout sample, the models calibrated with the XGBoost algorithm had superior predictive power. The predictive power of all the algorithms trained on the data from the original sample suffered some loss when tested with a sample of wells that had started production after the end of that period. Implications of the empirical findings and strategies to mitigate loss of predictive power are discussed in the concluding section.
The electromagnetic wave amplification in thin superconducting film in non-linear mixed state

In this paper the interaction of electromagnetic waves with the moving fluxons in the thin superconducting film on the dielectric substrate is considered. It is shown that in the case of flux-flow described by the Larkin-Ovchinnikov model, the amplification of electromagnetic wave can be observed. In this case, amplification can be achieved when the fluxons velocity is less than the phase velocity of the electromagnetic wave. It is revealed that the thin superconducting film in mixed state demonstrated nonreciprocal properties for backward and forward waves. The results obtained in this work allow to create amplifiers based on cuprate superconductors.
Approaching Instagram data: reflections on accessing, archiving and anonymising visual social media

ABSTRACT Instagram is one of the most popular social media platforms worldwide, making it a key site for social examination. Despite this, scholarly conversations about analysing Instagram data remain scarce, with existing research focusing on text-driven platforms such as Twitter. This year, Instagram permanently disabled access to its Legacy API. For users, this has been hailed as positive, increasing privacy and control. However, these actions have unintentional impacts on research, creating significant access barriers. How researchers continue to engage with Instagram data as ‘personal data’ is a central question, particularly in light of global privacy events like Cambridge Analytica. This article contributes to emerging discussions about approaching visual social media, responding to ethical and policy challenges of Instagram data. It details the process of accessing, archiving and anonymising Instagram data from a three-year platform study. Social research now encounters multiple commercial gatekeepers, where third-party applications are pivotal, and paywalls widen access inequalities.
Cryptosporidium Infection in Goats in Serbia

Cryptosporidiosis is an anthropozoonosis caused by coccidia of the family Cryptoporididae, whish may cause a serious health problem for kids in the first weeks of life. In our paper we presented results of examination of goat cryptosporidiosis in Serbia. In period 2016-2019 we examined 197 goat herds. Total of 1576 faecal smears were examined by Sheather’s sugar floatation technique and modified Ziehl–Neelsen staining technique. Cryptosporidiosis were found at 119 herds. Kids between five and twenty-one days old are the most susceptible. The morbidity varies from 75–100% and the mortality from 45-50%. Some animals do not develop into chronic cases and become carriers. After infection, animals either resist the organism, develop a mild infection that is self limiting, or soon sicken and die. Based on the performed research, we have established a significant role of cryptosporidiosis in the development of neonatal enteropathies of kids.
The scientific results from the X-ray observatory Hitomi

Hitomi is the 6th Japanese X-ray astronomy satellite launched on 2016 Feb 17. Although it was unfortunately lost about 1 month from the launch, Hitomi produced many new scientific results, owing to extremely high spectral resolution of the non-dispersive SXS detector (X-ray microcalorimeter). From the observations of the Perseus cluster, a stringent upper limit of the turbulent pressure, only <7% of that of the thermal pressure, is obtained, and the metal abundance in ICM is found consistent to that of the solar vicinity. Power of the high resolution spectroscopy even with small photon counts is demonstrated in N132D and IGR J16318-4848. Emission/absorption line search was performed in Crab and G21.5−0.9. A result is obtained to support that the Crab nebula was born from an electron-capture supernova. New absorption line structures are detected from G21.5−0.9, although they need further confirmation because of low statistical significance of 34σ . To fulfill the calorimeter science, the XRISM project has been on-going. Following XRISM, we have started preparing the next generation hard X-ray mission FORCE that is a successor of the hard X-ray imager onboard Hitomi, but with much better spatial resolution of 15 arcsec in HPD. They are planned to be launched by the end of March 2022 and late 2020’s, respectively.
Reciprocal modulation of Linc-223 and its ligand miR-125a on the basis of platelet function level

Cardiovacular diseases (CVD) are the leading cause of death worldwide. Platelet play a key role in the pathophysiology of multiple CVD. LincRNAs are long non-coding RNAs transcribed from intergenic DNA segments. Some members of this class were recently associated with human disease. Linc-223 is co-transcribed together with mir-223 and was recently shown to bind to miR-125. Both miR-223 and miR-125 are highly expressed in platelets. In light of the capability of Linc-223 to bind to miR-125, we aimed to investigate whether their reciprocal expression levels might reflect the degree of platelet activity. RNA was extracted using miRVANA. MiRNAs and lncRNAs were measured by means of quantitative Real Time RT-PCR. We found a significant reduction of Linc-223 levels (p<0.05) along with a significant increase in miR-125 levels (p<0.05) after initiation of any antiplatelet treatment (n=30) compared to naïve patients (n=10). Moreover, the upgrade to a higher-intensity antiplatelet treatment with ASA+ticagrelor from ASA+clopidogrel (n=30) was associated to a further down-regulation of Linc-223 (p<0.05) along with a further increase of miR-125. (p<0.05). Finally, these results were validated in a larger cohort of 300 patients from the ATLANTIS study, demonstrating significant modulation of both miR-223 and miR-125 in patients with high on-treatment platelet aggregation levels compared to antiplatelet-responsive patients. We identify a reciprocal modulation of Linc-223 and miR-125, its ligand upon different levels of platelet aggregations. These results are compatible with previous evidence from patients with Acute Myeloid Leukemia, that Linc-223 might bind to and sponge miR-125, inhibiting its effect. These results suggest that plasma levels of Linc-223, miR-125 and miR-223 might be used a biomarkers of platelet finction in a clinical context, for risk stratification of patients or to assess the responsiveness to antiplatelet treatments. Type of funding source: None
QCM sensors for aqueous phenols based on active layers constituted by tetrapyrrolic macrocycle Langmuir films

Three different metalated tetrapyrrolic macrocycles have been transferred by Langmuir-Blodgett technique directly onto piezoelectric quartz crystal covered with gold electrodes of a commercial quartz crystal microbalance instrument in order to perform a flow injection analysis. All floating films at the air-water interface have been analyzed by registration of Langmuir curves and by UV-vis reflection spectroscopy and brewster angle microscopy. The sensing performances of the modified gold electrodes were investigated by monitoring the frequency variation induced by the presence of several toxic phenols. The explored concentrations ranged around 10-3 M and the corresponding frequency variations ranged between 10 and 200 Hz. All responses observed were fast, reproducible and reversible; moreover, the active layers are stable over long periods of utilization. The observation that interferences from fulvic acid are absolutely negligible is also noteworthy. The responses are not selective for each singular phenol derivative; notwithstanding this, to the best of our knowledge, this contribution represents one of the first examples of sensing layers for the monitoring of the total content of phenols.
Validity and Reliability of Resilience Scale for Islamic Boarding School Students

This research aimed to examine the content validity and resilience scale reliability that was developed based on the theory of Reivich and Shatte. The measuring instrument consisted of 32 items, which resulted from a modification of the instruments made by Reivich and Shatte with seven aspects of resilience, namely emotion regulation, impulse control, optimism, causal analysis, empathy, self-efficacy, and reaching out. This research sample amounted to 150 respondents consisting of Islamic boarding school students in Purworejo, Central Java, boys and girls aged 11-18 years. The items in the measuring instruments were analyzed using the Gregory formula with the help of Ms. Excel program; then, the Cronbach Alpha formula was analyzed using the SPSS program. Based on the results of the analysis of content validity with two experts’ judgments and the validity index of 1, it means that the instrument’s validity is very high. As for the reliability test results, the value of Cronbach’s Alpha item resilience scale is 0,753. This shows that the resilience scale item has good reliability. Based on these data, resilience instruments can be said to be valid and reliable to measure the resilience of Islamic boarding school students.
Optical and Morphological Studies of Doped Core Shell ZnS:Cu/ZnS Nanoparticles

The paper presents some results of study based on applications of ZnS core shell quantum dots (QDs) doped with Cu. Keeping the luminous properties in focus we synthesized the core shell QDs by chemical precipitation route, resulting in formation of core@shell QDs with ZnS core doped with copper and ZnS shell on it, i.e. [ZnS:Cu@Zn. We focus the application of these particles in field of OLEDs (AMOLED) to address the performance deficiencies like varying brightness of the different wavelength emitting LEDs, called Green Window problem. Efforts have been done to address the problems by synthesizing highly luminescent green emitting copper doped ZnS, core@shell QDs. Further a monolayer of core shell quantum dots was deposited on ITO by spin coating for analyzing the photometric properties of the QDs.
Algorithm for obtaining palindromes of the binary number system

The aim of this paper is to describe a new method for searching all binary palindromes that have a given number of the binary digits. The main result is presented in the form of an algorithm. The obtained algorithm is based on the use of the regularity revealed in the course of the study, based on the application of basic arithmetic operations with palindromes that have a various number of the binary digits. The paper also provides examples of using this algorithm to obtain binary palindromes with different number of the binary digits. The algorithm formulated here can be applied to analyse computer data written in the form of a binary code.
Horizontal axis wind turbine modelling and data analysis by multilinear regression

Abstract. The modelling of each horizontal axis wind turbine (HAWT) differs due to variation in operating conditions, dynamic parameters, and components. Thus, the choice of profiles also varies for specific applications. So for the better choice of profiles, the wind turbine performance is analysed for different parameters and working conditions. The efficiency of HAWTs mainly depends on the blade, which in turn is related to the profile of the blade, blade orientation, and tip size. Hence, the main aim of the present work is to evaluate the performance of HAWTs for three different blade tip sizes and six different blade twist angles for three major NACA (National Advisory Committee for Aeronautics) airfoils. A statistical analysis is also carried out to find the influence of different performance parameters such as drag, lift, vorticity, and normal force. The static design parameters are considered based on the available literature. A three-bladed offshore HAWT is adopted as the research object in the study. Data visualization using star glyphs and sunray plots is performed, along with multilinear regression analysis. From the multilinear regression analysis and reliable empirical correlations, it is known that drag coefficient and lift coefficient parameters have less significance in contrast to the other parameters which have more significance in the regression model. The different results obtained in terms of parametric coefficients provide an effective way to generate appropriate airfoil profiles for given HAWTs. Thus, the study helps to achieve better turbine performance, and it serves as a benchmark for future studies on HAWTs.
Anionic waterborne polyurethane dispersions based on hydroxyl‐terminated polybutadiene and poly(propylene glycol): Synthesis and characterization

Nonpolluting systems based on anionic polyurethane aqueous dispersions were obtained. The prepolymer based on hydroxyl-terminated polybutadiene (HTPB), isophorone diisocyanate (IPDI), poly(propylene glycol) (PPG), and dimethylolpropionic acid (DMPA) were synthesized in bulk. After neutralization with triethylamine (TEA), the anionomer prepolymer was dispersed in water, followed by a chain-extension reaction with ethylenediamine (EDA). The prepolymers were characterized by Fourier transform infrared spectrometry (FTIR) and the average particle size of the aqueous dispersions was determined by laser light scattering (LLS). The mechanical behavior of polyurethane-cast films and the adhesive properties of the aqueous dispersions as coatings for wood were evaluated. It was observed that an increase in the HTPB content provoked an increase in the viscosity and in the particle size of the dispersions. The tensile strength and the modulus values of the films and the adhesiveness of the coatings in wood were also increased by increasing the HTPB content. On the other hand, the elongation of the polyurethane-cast films and the tackness of the surface coatings decreased as the HTPB was increased. © 2001 John Wiley & Sons, Inc. J Appl Polym Sci 80: 566–572, 2001
A geometric deep learning approach for checking element-to-entity mappings in infrastructure building information models

Data interoperability between domain-specific applications is a key prerequisite for building information modeling (BIM) to solidify its position as a central medium for collaboration and information sharing in the construction industry. The Industry Foundation Classes (IFC) provides an open and neutral data format to standardize data exchanges in BIM, but is often exposed to data loss and misclassifications. Concretely, errors in mappings between BIM elements and IFC entities may occur due to manual omissions or the lack of awareness of the IFC schema itself, which is broadly defined and highly complex. This study explored the use of geometric deep learning models to classify infrastructure BIM elements, with the ultimate goal of automating the prechecking of BIM-to-IFC mappings. Two models with proven classification performance, Multi-View Convolutional Neural Network (MVCNN) and PointNet, were trained and tested to classify 10 types of commonly used BIM elements in road infrastructure, using a dataset of 1496 3D models. Results revealed MVCNN as the superior model with ACC and F1 score values of 0.98 and 0.98, compared with PointNet's corresponding values of 0.83 and 0.87, respectively. MVCNN, which employs multiple images to learn the features of a 3D artifact, was able to discern subtle differences in their shapes and geometry. PointNet seems to lose the granularity of the shapes, as it uses points partially selected from point clouds.
Construction Project Change Management in the Democratic Republic of the Congo: Status, Causes, and Impacts

Changes in construction projects are very frequent and are expected to occur at any stage of the project. These changes modify the original scope of work and affect the project in various aspects. To minimize these effects, there is a need to implement a systematic change management system during the construction process. This study aimed to investigate the current situation of change management implementation, identify the main causes of change management, and assess their impacts in the Congolese construction industry. A comprehensive literature review was conducted for a thorough understanding of change management, and a structured survey was conducted. The collected survey data were analyzed using the relative importance index (RII), and Statistical Package for the Social Sciences (SPSS) methods. The results conclude that the change management implementation situation in the Congolese construction industry is significantly high, and the project cost and the project type play a major role in the implementation of change management in the construction projects. The study further revealed that the main causes of changes were the project, contractor, materials, equipment, and other causes. These changes impact the project significantly in terms of organization, owner and contractor, project, materials, and equipment.
Visible photoluminescence in Si+‐implanted thermal oxide films on crystalline Si

We have investigated visible photoluminescence excited by Ar ion laser (488 nm, 2.54 eV) at room temperature from Si+‐implanted thermal oxide films grown on crystalline Si wafer, as‐implanted and after subsequent annealing in vacuum. We found two types of visible luminescence bands similar to those of silica glasses; one band is observed in as‐implanted specimens and disappears after heating to about 600 °C, and the other band is observed only after heating the specimens to about 1100 °C. Though the shapes of these luminescence spectra are different from those having been observed in Si+‐implanted silica glass, the origins of these bands are the same as in silica glass. We discuss the similarities and the differences of luminescence bands in Si+‐implanted silica glasses and thermal oxide films grown on crystalline Si.