Miracle-dz/UniFAR-FTUs huggingface dataset:
MODERN MATERIALS AND STRUCTURES USED IN HOUSING CONSTRUCTION: INTERNATIONAL EXPERIENCE

Introduction: The article addresses the possibility of using universal energy-efficient engineering and technological solutions in mass housing construction, regardless of the climatic region of construction, with account for modern development in Saint Petersburg (Russian Federation) and Münster (Germany). The article not only considers improvements in building technologies used in modern housing construction but also offers an overview of the latest energy-efficient materials and structures. Purpose of the study: We aimed to introduce energy-efficient solutions in housing construction using innovative technologies and materials. In addition to theoretical materials, practical calculations will be presented, clearly showing the advantages and disadvantages of various engineering and technical solutions. Methods: In the course of the study, we used a) a comparative analysis of physical and thermal properties as well as strength characteristics of building materials used in mass housing construction; b) a problem-logical method to analyze possible typical space-planning and structural solutions for the design and construction of buildings, with account for climatic conditions and geographical features of the construction region, in compliance with the basic principles of modern sustainable construction, energy and environmental standards, economic efficiency of the solutions used, in accordance with international European LEED and BREEAM and Russian GREEN ZOOM standards. Results: We propose to introduce, along with the already well-known and time-tested ones, innovative patented solutions in materials and construction technologies both in private and mass housing construction in the countries under consideration: Russian Federation and Germany. Discussion: The discussion of field tests and implementation of the latest building materials in housing construction clearly demonstrates the importance of international cooperation in this field at various levels. As a consequence of the growing volume of housing construction and energy consumption, there emerge new stricter requirements and standards for the quality of materials produced and their technical characteristics, as well as a variety of decorative solutions enabling the construction market to be competitive and meet the over-demand requirements of the rapidly developing industrial society, while necessarily taking environmental protection measures, including those on conservation and mindful use of natural resources.
A TWO-STEP LEARNING-BY-EXAMPLES METHOD FOR PHOTOVOLTAIC POWER FORECASTING

|In this paper, an innovative machine learning ( ML ) approach for the prediction of the output power generated by photovoltaic ( PV ) plants is presented. Toward this end, a two-step learning-by-examples ( LBE ) strategy based on support vector regression ( SVR ) is proposed to learn the complex relation among the heterogeneous parameters aﬀecting the energy production of the power plant. More speci(cid:12)cally, the (cid:12)rst step is aimed at down-scaling the weather forecasts from the standard air temperature and the solar irradiance to the local module temperature and the plane-of-array ( POA ) irradiance. Then, the second step predicts the output power pro(cid:12)le given the down-scaled forecasts estimated at the previous step. The advantages and limitations of the proposed two-step approach have been experimentally analyzed exploiting a set of measurements acquired in a real PV plant. The obtained results are presented and discussed to point out the capabilities of the proposed LBE method to provide robust and reliable power predictions starting from simple weather forecasts.
Holographic renormalization of new massive gravity

We study holographic renormalization for three-dimensional new massive gravity. By studying the general falloff conditions for the metric allowed by the model at infinity, we show that at the critical point where the central charges of the dual conformal field theory (CFT) are zero, it contains a leading logarithmic behavior. In the context of AdS/CFT correspondence it can be identified as a source for an irrelevant operator in the dual CFT. The presence of the logarithmic falloff may be interpreted as the fact that the dual CFT would be a logarithmic conformal field theory.
A new look at NICMOS transmission spectroscopy of HD 189733, GJ-436 and XO-1: no conclusive evidence for molecular features

We present a re-analysis of archival HST/NICMOS transmission spectroscopy of three exoplanet systems: HD 189733, GJ-436 and XO-1. Detections of several molecules, including H 2 O, CH 4 and CO 2 , have been claimed for HD 189733 and XO-1, but similarly sized features are attributed to systematic noise for GJ-436. The data consist of time-series grism spectra covering a planetary transit. After extracting light curves in independent wavelength channels, we use a linear decorrelation technique to account for instrumental systematics (which is becoming standard in the field), and measure the planet-to-star radius ratio as a function of wavelength. We use a residual permutation algorithm to calculate the uncertainties, in an effort to evaluate the effects of systematic noise on the resulting transmission spectra. For HD 189733, the uncertainties in the transmission spectrum are significantly larger than those previously reported. We also find that the transmission spectrum is considerably altered when using different out-of-transit orbits to remove the systematics, when some parameters are left out of the decorrelation procedure, or when we perform the decorrelation with quadratic functions rather than linear functions. Given that there is no physical reason to believe that the baseline flux should be modelled as a linear function of any particular set of parameters, we interpret this as evidence that the linear decorrelation technique is not a robust method to remove systematic effects from the light curves for each wavelength channel. For XO-1, the parameters measured to decorrelate the light curves would require extrapolation to the in-transit orbit to remove the systematics, and we cannot reproduce the previously reported results. We conclude that the resulting NICMOS transmission spectra are too dependent on the method used to remove systematics to be considered robust detections of molecular species in planetary atmospheres, although the presence of these molecules is not ruled out.
Multi Objective Flexible Employee Scheduling for Pharmaceutical Industries Using Hybrid Genetic Algorithm

In this paper a hybrid genetic algorithmis used to study the employee scheduling problem in pharmaceutical industries. Scheduling is done based on the aspects of both management and employees. The management aspect is to reduce the total cost of the employee by minimizing the makes span. The employee aspects are a preferred number of shifts, shift types, days off, etc. In this scheduling an extra care is taken in not to assign a night shift on the day beforethe day off, because once a night shift assigned to the employee almost present in the next morning. A mathematical model is formed based on flexible working of the employees. In this model, 6 hour shifts isallotted to the employees, which reduces the total cost by 10.135% and the makes span by 4.145% compared to the other models.
MPC-based Motion Planning and Control Enables Smarter and Safer Autonomous Marine Vehicles: Perspectives and a Tutorial Survey

Autonomous marine vehicles (AMVs) have received considerable attention in the past few decades, mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration. Recent advances in the field of communication technologies, perception capability, computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs. In order to deploy the constrained AMVs in the complex dynamic maritime environment, it is crucial to enhance the guidance and control capabilities through effective and practical planning, and control algorithms. Model predictive control (MPC) has been exceptionally successful in different fields due to its ability to sys-tematically handle constraints while optimizing control performance. This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC. Finally, future research trends and directions in this substantial research area of AMVs are highlighted.
Infinite-variable Bessel functions in two-dimensional Wannier-Stark systems

We discuss the spectrum and the eigenfunctions of a 2D Wannier-Stark system in both the tight-binding and single-band approximations. We show that the unfamiliar infinite-variable Bessel functions play a crucial role in these considerations. Furthermore, a closed formula for the eigenfunction for an arbitrary tight-binding ansatz in terms of an expansion in Wannier states is derived. Finally we give a closed form solution for the Wannier-Stark states in the scope of the single-band approximation.
An embedded printed flexible strain resistance sensor via micro-structure design on graphene-filled conductive silicon rubber

Flexible strain sensors have been improved in sensing performance with the assistance of materials design, novel manufacturing, and microstructure fabrication. In this study, graphene was efficiently dispersed in ethanol and then re-dispersed into silicon rubber (SR) matrix, functioning as a flexible strain resistance sensor (FSRS) with functional macrostructure and modified microstructure to further improve the sensitivity. A stable dispersion of graphene was obtained in an ultrasound-aided ball milling process, where absolute ethanol was selected as the solvent and sodium dodecyl sulfonate as the surfactant. Graphene-filled conductive SR was embedded in the polydimethylsiloxane matrix as a conductive sensing layer, and the high sensing performance (GF = 25 ± 2) was achieved using a spiral printed. Micropores with an optimized interspacing of 10 mm were further introduced into the spiral CSM, and the results presented a significant improved sensitivity (GF = 51 ± 4) of the fabricated FSRS under a working strain (20%–30%) and cyclic test (>104 cycles). The FRSR was sensitive enough to monitor various movements of single and multi-joints of human body and identify the rhythm of music sound, which exhibited its potential application as a wearable flexible sensor.
Modeling of gas sample behavior in gas chromatography column

The equilibrium-dispersive model of the linear GC (gas chromatography) was derived using both assumptions and the method of its derivation different from the known in literature. It was concluded that this model is a specific case of the Fokker-Planck equation for diffusion with drift. The resolution of this derived equation for assumed initial conditions is the normal distribution with movable mean value. At the end of the GC column the standard deviation of this distribution was investigated as a factor of the sample shape. This standard deviation is independent of the retention factor.
FAM201A Promotes Cervical Cancer Progression and Metastasis through miR-1271-5p/Flotillin-1 Axis Targeting-Induced Wnt/β-Catenin Pathway

This study investigated the role of the family with sequence similarity 201-member A (FAM201A), as previously reported oncogenic, in cervical cancer (CC). FAM201A expression in CC was analyzed through bioinformatics analyses, and its distribution in CC tissues/cells was determined by in situ hybridization. CC cells were transfected/cotransfected with FAM201A/flotillin-1 (FLOT1) overexpression plasmids and miR-1271-5p mimics, followed by functional analysis on viability, migration and invasion. Pearson's correlation tests were performed to analyze the correlation between FAM201A and miR-1271-5p in CC tissues. The targeting relationship between miR-1271-5p and FLOT1 was confirmed by dual-luciferase reporter assay. The expressions of FAM201A, miR-1271-5p, FLOT1, matrix metalloproteinases (MMP)-9, MMP-2, E-cadherin, N-cadherin, and the Wnt/β-catenin pathway-related molecules (Wnt1, β-catenin and p-β-catenin) in CC cells or tissues were assessed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and/or western blot. The results showed that FAM201A was abundantly expressed and miR-1271-5p expression was downregulated in CC. FAM201A was enriched in CC cell cytoplasm and negatively correlated with miR-1271-5p in CC tissues. FAM201A overexpression enhanced the cell viability, migration, invasion, and tumorigenesis of CC in vivo and increased FLOT1 expression. These trends were all reversed by upregulating miR-1271-5p, which induced opposite effects to FAM201A overexpression. MiR-1271-5p upregulation depleted the levels of MMP-9, MMP-2, N-cadherin, and the Wnt/β-catenin pathway-related molecules and upregulated E-cadherin expression. FLOT1 was a direct target of miR-1271-5p. FLOT1 overexpression induced effects contrary to the upregulation of miR-1271-5p and abolished miR-1271-5p upregulation-induced effects in CC cells. Overall, this study showed that FAM201A promoted cervical cancer progression and metastasis by targeting the miR-1271-5p/FLOT1 axis-induced Wnt/β-catenin pathway.
High‐quality GaN film and AlGaN/GaN HEMT grown on 4‐inch Si(110) substrates by MOCVD using an ultra‐thin AlN/GaN superlattice interlayer

We report the characterization results of GaN films and AlGaN/GaN heterostructure grown on 4‐inch Si(110) substrates by MOCVD using an ultra‐thin AlN/GaN superlattice interlayer (SL IL) structure. The structure optimization of the SL IL, characterizations of the GaN film quality and the strain state are carried out. The SL IL is found to play an important role in controlling the strain states in GaN films. A crack‐free GaN film up to 2 μm thick is achieved by inserting one SL IL. High‐quality GaN is obtained with the FWHM values of (002) and (102) diffraction peaks from a 2 μm‐thick GaN film being as narrow as 427 arcsec and 665 arcsec, respectively. A flat surface morphology of GaN with monolayer steps is obtained. Based on the SL IL technique, AlGaN/GaN heterostructure is grown with 2DEG mobility and sheet carrier density being ∼1500 cm2/Vs and 1.2 × 1013 cm−2. A high‐electron‐mobility transistor (HEMT) is fabricated and good DC characteristics are demonstrated.
Energy-saving trajectory optimization of a fluidic soft robotic arm

Soft robots have attracted increasing attention due to inherent environmental adaptability and reliable human–machine interaction. However, there is relatively few research about their energy efficiency which acts as an important indicator. This paper firstly derives the time-domain model of energy consumption for a fluidic soft robotic arm. With the introduction of forward kinematics, the trajectory of the soft robotic arm is optimized for energy saving under motion constraints and solved using interior point method. A series of experiments are implemented to evaluate the performance of the proposed model and the optimized trajectory. The results show that the time-based model can capture the dynamical energy behaviors of the fluidic soft actuators under various motions. It is also found that the energy consumption of the soft robotic arm is effectively reduced when the trajectory optimization is applied. This work can provide further reference to the energy-based optimization of the soft robots.
Stacked Ensemble-IDS Using NSL-KDD Dataset

The intrusion detection system is a traffic monitoring unit that protects our network from numerous threats. It works as a monitoring unit with the ability to detect attacks in a real-time environment. Various techniques have been employed to make the IDS machine work with accuracy. To attain good accuracy, machine learning and deep learning are being utilized to train and evaluate the IDS machines. To prepare for the IDS's training and testing, before deploying them in real-time situations, a collection of real-world internet traffic records is stored with their traffic input features, this traffic records can be utilized to test the IDS machine against several attacks before they are employed into the real world. One such dataset is the University of New Brunswick's NSL-KDD dataset used to train and test the machine learning or deep learning models. In this paper, we will train and evaluate our model using the proposed stacked ensembled machine learning model, and with the NSL-KDD dataset, compare it based on various evaluation metrics against standard machine learning methods and some earlier proposed research.
EXPLORING SUSTAINABILITY FACETS OF PRO-POOR TOURISM PROGRAMS IN INDIA

This paper intends to explore local-specific sustainability facets of pro-poor tourism initiated in India's Protected Area (PA). Mixed methodology, i.e., interview and structured questionnaire adopted for data collection and followed by the factor analysis for testing hypothesis. The result indicates that the sustainability facets of pro-poor tourism have five distinct facets: monetary, environmental, societal, cultural heritage, and governance. The study assumes significance in the pro-poor approach in tourism development for addressing various Sustainable Development Goals and in understating the ground-level reality of sustainability in the context of tourism-led development in developing countries. It also throws light on setting standards for approach-based tourism programs that cater to various segments of society and the environment.
Mechanism of stimulated Hawking radiation in a laboratory Bose-Einstein condensate

We model a sonic black hole analog in a quasi one-dimensional Bose-Einstein condensate, using a Gross-Pitaevskii equation matching the configuration of a recent experiment by Steinhauer [Nat. Phys. 10, 864 (2014)]. The model agrees well with important features of the experimental observations, demonstrating their hydrodynamic nature. We find that a zero-frequency bow wave is generated at the inner (white hole) horizon, which grows in proportion to the square of the background condensate density. The relative motion of the black and white hole horizons produces a Doppler shift of the bow wave at the black hole, where it stimulates the emission of monochromatic Hawking radiation. The mechanism is confirmed using temporal and spatial windowed Fourier spectra of the condensate. Mean field behavior similar to that in the experiment can thus be fully explained without the presence of self-amplifying Hawking radiation.
Numerical evolutions of fields on the 2-sphere using a spectral method based on spin-weighted spherical harmonics

Many applications in science call for the numerical simulation of systems on manifolds with spherical topology. Through the use of integer spin-weighted spherical harmonics, we present a method which allows for the implementation of arbitrary tensorial evolution equations. Our method combines two numerical techniques that were originally developed with different applications in mind. The first is Huffenberger and Wandelt’s spectral decomposition algorithm to perform the mapping from physical to spectral space. The second is the application of Luscombe and Luban’s method, to convert numerically divergent linear recursions into stable nonlinear recursions, to the calculation of reduced Wigner d-functions. We give a detailed discussion of the theory and numerical implementation of our algorithm. The properties of our method are investigated by solving the scalar and vectorial advection equation on the sphere, as well as the 2 + 1 Maxwell equations on a deformed sphere.
AUTOMATIC IDENTIFICATION OF SOME VIETNAMESE FOLK SONGS CHEO AND QUANHO USING CONVOLUTIONAL NEURAL NETWORKS

We can say that music in general is an indispensable spiritual food in human life. For Vietnamese people, folk music plays a very important role, it has entered the minds of every Vietnamese person right from the moment of birth through lullabies for children. In Vietnam, there are many different types of folk songs that everyone loves, and each has many different melodies. In order to archive and search music works with a very large quantity, including folk songs, it is necessary to automatically classify and identify those works. This paper presents the method of determining the feature parameters and then using the convolution neural network (CNN) to classify and identify some Vietnamese folk tunes as Quanho and Cheo. Our experimental results show that the average highest classification and identification accuracy are 99.92% and 97.67%, respectivel.
Flame Reconstruction Using Synthetic Aperture Imaging

Flames can be formed by burning methane (CH4). When oxygen is scarce, carbon particles nucleate into solid particles called soot. These particles emit photons, making the flame yellow. Later, methane is pre-mixed with air forming a blue flame; burning more efficiently, providing less soot and light. Imaging flames and knowing their temperature are vital to maximizing efficiency and validating numerical models. Most temperature probes disrupt the flame and create differences leading to an inaccurate measurement of the flame temperature. We seek to image the flame in three dimensions using synthetic aperture imaging. This technique has already successfully measured velocity fields of a vortex ring [1]. Synthetic aperture imaging is a technique that views one scene from multiple cameras set at different angles, allowing some cameras to view objects that are obscured by others. As the resulting images are overlapped different depths of the scene come into and out of focus, known as focal planes, similar to tomography. These focal planes can be used to extract three-dimensional information about the scene. This procedure was used to extract the outer edge of a oxygen-starved methane flame (yellow) from which the three-dimensional flame was reconstructed. When the reconstructed image was compared to the raw image from the central camera the two shapes corresponded well. This experiment in the fluid dynamics video (entry #: V041) demonstrated that a three-dimensional flame can be reconstructed by combining images from multiple cameras using synthetic aperture imaging.
Skin microcirculation reactivity to local thermal hyperaemia in patients with Covid-19 - A pilot observational study.

BACKGROUND Endothelial dysfunction and microvascular disturbances are suggested to play a key role in higher morbidity and worse prognosis in patients with COVID-19 and cardiometabolic diseases. OBJECTIVE Study was aimed to establish relationships between the skin microcirculation parameters and various clinical and laboratory indicators. METHODS The study included 18 patients with moderate disease according to WHO criteria. Skin microcirculation measurements were performed by laser Doppler flowmetry using a heating test on the hairy skin of the right forearm. RESULTS Baseline perfusion only correlated with C-reactive protein (Rs = 0.5, p = 0.034). Microcirculation indices characterising the development of hyperaemia during the first minute of heating (LTH1 and AUC60) showed significant correlations (Rs from 0.48 to 0.67, p < 0.05) with indices of general blood analysis and blood coagulation (fibrinogen, D-dimer, haemoglobin, erythrocyte count and haematocrit). Indexes characterising the dynamics of hyperaemia development over longer time intervals showed correlation with the glomerular filtration rate (Rs = 0.6, p = 0.009). CONCLUSION Known COVID-19 risk factors (haemorheological parameters, age) are correlated with the microvascular reactivity to heating in patients with COVID 19. We suggest that, prospectively, the method of laser Doppler flowmetry could be used for non-invasive instrumental assessment of microcirculatory disorders in patients with COVID-19.