Miracle-dz/UniFAR-FTUs huggingface dataset:
GREEN INDEXING OF HISAR MUNICIPAL CORPORATION USING GEOSPATIAL TECHNIQUES

Abstract. Urban Green Space (UGS) enhances the structure of the landscape of a city. It provides economic, social and health benefits to the inhabitants. Rapid urbanization and increase in population has put extreme pressure on urban green spaces. Therefore, mapping of urban green spaces is important to facilitate the urban planning sustainably. This study has been taken up to map the UGS in the Hisar Municipal Corporation (HMC) area of Haryana State constituting an area of 4197.32 ha using high resolution LISS-IV data of November, 2017. Three different methods namely (a) Onscreen Digitization (b) Support Vector Machine-based classification (SVM) and (c) Multi Resolution Segmentation (MRS) have been tested to extract the green spaces. The onscreen digitization method has been considered as best method as compared to SVM and MRS because of the intervention of human mind and full control on manual editing. The SVM under estimated the green space for HMC with average relative deviation of 15%. However, it extracted the green area precisely without mixing of open spaces. MRS have given good results in terms of total area (relative deviation was 5%), however, spatial distribution of green spaces have been mixed with open spaces. The study identified the green index of HMC and suggested the suitability and sustainability of the city based on World Health Organization (WHO) defined standards. Green space for Hisar Municipal Corporation was 1690.96 ha with average urban green space index of 0.40. Per capita green cover for HMC was 9.69 m2/inhabitant, which is as per the standard reported by WHO i.e. 9 m2/inhabitant. Further study may suggest some other algorithm for better results and automatic green space extraction.
Optimization and Parameter Characterization for Rotating Scatter Mask Designs

The Rotating Scatter Mask system, which consists of a NaI detector, plexiglass mask, and a small motor, is a low cost directional radiation detection system with a nearly 4π field-of-view over a broad range of photon energies. However, the current mask design is limited by similarities in the directional modes of the detector response, causing potential misidentification errors when locating a source. A new class of RSM designs were simulated using MCNP and compared to the current mask design using the modal assurance criterion to characterize differentiability between directional modes. These masks were shown to successfully decouple the angular components of the source’s direction, improving the average criterion value by up to 83% and limiting the directional uncertainty to the order of the physical system’s angular resolution. Correlation between the geometry of the mask and the detector response for this new class of designs also presents an improved method for determining source direction, potentially enabling imaging capabilities. Finally, the new designs drastically improved the system’s efficiency, reducing the time to identify the source by up to two orders of magnitude.
Polymeric ferrite‐loaded antennas for on‐body communications

Wearable antennas are integral part of body area networks (BANs). Antenna design for BAN applications is a challenging task since the antennas have to be small, efficient, and must not be affected by the wearer's body. This makes isolation of antenna a matter of importance. Ferrites form an opaque media for microwave at the 2.4‐GHz ISM band and hence it could be used for the isolation of antenna from surroundings. Thin polymeric ferrite sheets are used to reduce body influence in BAN perspective. © 2009 Wiley Periodicals, Inc. Microwave Opt Technol Lett 51: 2530–2533, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.24669
Synthèse de textures multifractales directement sur des surfaces 3D

We propose a method for the synthesis of multifractal textures on a curved 3D surface, without any geometrical transformation of the surface or any mapping. This procedural method permits the description of potentially infinitely extended texture with few parameters only which ensures a limited memory footprint. Scale invariant textures, like the welknown fractional Brownian motion, are essential to computer graphics. Up to our knowledge this is the first procedural method for the synthesis of multifractal textures (scale invariant and non Gaussian) on 3D surfaces. In practice, by avoiding the use of any classical mapping step, we avoid some undesired artefacts and alleviate the global procedure. We currently develop a software that implements this approach.
A Comparative Study of LFM Reverberation Suppression Schemes

The research work in this paper is based on, improving the target detection performance under reverberation scenario which is the most important issue when active sonar’s are used for target detection. Reverberation is echo due to scatterers and boundaries in the water when the transmitted signal off. Reverberation is severely colored, correlated strongly with the emitted signal and non stationary in time and frequency domains. It is also frequency dependent in nature and the pulse length is more because it is doubly spread. Due to these difficulties matched filtering is ineffective. The motivation behind this paper is to suppress LFM reverberation, which is present while transmitting a Linear Frequency Modulated (LFM) signal. In this paper, the performance analysis of dechirping transformation based and Fraction Fourier Transform (FrFT) based parametric power spectrum estimation methods such as Autoregressive (AR), Moving Average (MA) and Autoregressive Moving Average (ARMA) prewhitening models were studied with respect to LFM reverberation data and results are presented. The simulation results with LFM reverberation data verify that the proposed dechirping transformation based and FrFT based MA and ARMA prewhitening models improves the target detection performance of active sonar systems.
Reduced-intensity conditioning allogeneic stem cell transplantation in pediatric patients and subsequent supportive care.

PURPOSE/OBJECTIVES To determine if children undergoing reduced-intensity conditioning allogeneic hematopoietic stem cell transplantation (RIC-AlloHSCT) have lower incidence of acute toxicities and, subsequently, require less supportive care than is required with myeloablative conditioning (MAC)-AlloHSCT. An additional purpose is to examine later outcomes by comparing 100-day transplantation-related mortality (TRM). DESIGN Retrospective chart and electronic medical records review. SETTING A pediatric care center in the northeastern United States. SAMPLE 86 patients who underwent AlloHSCT from January 2004 through March 2008. METHODS Charts were retrospectively reviewed. The comparison between groups was done by t test (continuous variables) and chi-square test (categorical variables). The logistic regressions, Kaplan-Meier product-limit estimator, log rank test, and Cox proportional hazards model were used. MAIN RESEARCH VARIABLES Days requiring total parenteral nutrition (TPN), patient-controlled analgesia (PCA), incidence of mucositis, days with fevers, number of infections, transfers to pediatric intensive care unit (PICU), blood product infusions, and 100-day TRM, all for 30 days post-transplantation. FINDINGS When comparing pediatric patients undergoing RIC-AlloHSCT (n = 43) versus MAC-AlloHSCT (n = 43) in the first 30 days post-transplantation, a statistically significant decreased incidence was noted for mucositis, infections, transfers to PICU, days on TPN and PCA, and days with fever, as well as 100-day TRM. CONCLUSIONS For pediatric patients, RIC-AlloHSCT is associated with significantly lower acute post-transplantation toxicities and TRM than MAC-AlloHSCT. IMPLICATIONS FOR NURSING For nurses to correctly educate their patients and family members, and to aid nurses in anticipating patient's needs, an understanding of the potential different acute toxicities and supportive care between pediatric patients undergoing RIC- versus MAC-AlloHSCT is vital.
Simultaneous Machine Translation with Visual Context

Simultaneous Machine Translation (SiMT) is a branch of Natural Language Processing which tries to solve the task of translating streams of text from one source language to another target language in real-time. This is indeed different from the traditional machine translation system where the translator has the luxury of having complete information about a source text. Simultaneous Machine Translator, on the other hand has to make a decision at every time step, choosing either to get more context from the source or generate output prediction for the target. This incurs an interesting tradeoff between translation quality and latency, since waiting for more context from the source will potentially improve translation accuracy while incurring more waiting time. Recent works show that by incorporating visual information from images related to a source text, one is able to improve the translation quality of a plain SiMT system. This however, introduces extra latency from extracting image features, and combining both visual and linguistic context. Keeping these considerations in mind, the challenge for us is to build a SiMT system with visual context which has a fine balance between high quality and low latency. Finally, the aim of our project is to build a user interface that relies on a simultaneous machine translation model to provide a real-time translation service.
Virial stress–based model to simulate the silica glass densification with the discrete element method

The discrete element method (DEM) presents an alternative way to model complex mechanical problems of silica glass, such as brittle fracture. Since discontinuities are naturally considered by DEM, no complex transition procedure from continuum phase to discontinuum one is required. However, to ensure that DEM can properly reproduce the silica glass cracking mechanisms, it is necessary to correctly model the different features characterizing its mechanical behavior before fracture. Particularly, it is necessary to correctly model the densification process of this material, which is known to strongly influence the fracture mechanisms. The present paper proposes a new and very promising way to model such process, which is assumed to occur only under hydrostatic pressure. An accurate predictive‐corrective densification model is developed. This model shows a great flexibility to reproduce extremely complex densification features. Furthermore, it involves only one calibration parameter, which makes it very easy to apply. This new model represents a major step towards accurate modeling of materials permanent deformation with the discrete element method, which has long been a huge challenge in applying this method for continuum problems.
Neural network-based command filtered control for induction motors with input saturation

In this study, neural networks approximation-based command filtered adaptive control is studied for induction motors with input saturation. The neural networks are utilised to approximate the non-linearities, and the command filtering technology is used to deal with the ‘explosion of complexity’ problem caused by the derivative of virtual controllers in the conventional backstepping design. The compensating signals are further exploited to get rid of the drawback caused by the dynamics surface technology. It is verified that the adaptive neural controller guarantees that the tracking error can converge to a small neighbourhood of the origin. At last, the effectiveness and advantages of the proposed method are intuitively illustrated by simulation results.
The Kp - Bondage And Kp - Non Bondage Number Of Fuzzy Graphs And Graceful Graph

In this paper, we define the bondage bk(G) ,Co-bondage bkc(G), and Nonbondagebkn(G) number for any fuzzy graph and exact values for some standard graphs are found and some bounds are obtained. Moreover we also obtained relationships between b,bc,bn(G) and bkn . We define graph extendable to complete graph by using find extension under Co bondage arcs and we also discussed with fuzzy graceful graph.
Numerical simulation of bubble dynamics in the gravitational and uniform electric fields

ABSTRACT A coupled volume-of-fluid, level set, and smoothed physical parameter (VOF+LS+SPP) method based on FLUENT is used to simulate bubble dynamics in the gravitational and uniform electric fields. Both of the bubble and surrounding medium are assumed to be perfect dielectrics with constant but different permittivities. The effects of electric Bond number, permittivity ratio, Morton number, and Eotvos number on the deformation and rising motion of a single bubble are systematically investigated. Simulation results show that a vertical electric field elongates the bubble along the electric field direction and accelerates the bubble rising. The electric Bond number has a much greater effect on bubble deformation and rising velocity than the permittivity ratio. The bubble behaviors in the electric field are similar for different Morton numbers but totally different for various Eotvos numbers. The influence of electric field on bubble Reynolds number changes a little for different Morton numbers but decreases distinctly with the increase of Eotvos number.
Efficacy and safety of ipratropium bromide/salbutamol sulphate administered in a hydrofluoroalkane metered-dose inhaler for the treatment of COPD

Background: The use of chlorofluorocarbons (CFCs) has contributed to the depletion of the stratospheric ozone layer resulting in serious health concerns. Ipratropium bromide/salbutamol sulphate CFC-pressurized metered-dose inhalers (IB/SAL-CFC pMDI) have been in widespread use for many years without any apparent ill consequences. This combination has now been reformulated using the hydrofluoroalkane (HFA) propellant. This study sought to establish the clinical noninferiority of a new HFA-containing IB/SAL pMDI to the conventional IB/SAL-CFC pMDI in subjects with mild/moderate COPD. Methods: This was a randomized, double-blind, parallel-group, multicenter study in two consecutive periods: a 14-day run-in period followed by a 85-day treatment period. Eligible mild-to-moderate stable COPD subjects aged 40−75 years were enrolled into the study and entered the run-in period during which subjects withdrew all the bronchodilators, except for salbutamol as rescue medication. Subjects were randomized to 85 days treatment with either IB/SAL-HFA or IB/SAL-CFC, 20 μ g qid. Results: Of the 290 randomized patients, 249 completed the study. The primary efficacy variable was the change in forced expiratory volume in one second from predose to 60 minutes after dosing on day 85. At the end of the treatment period, the adjusted mean change in forced expiratory volume in one second at 60 minutes was 123 mL in the IB/SAL-HFA pMDI group and 115 mL in the IB/SAL-CFC pMDI group. Because the lower limit of the 95% confidence interval for the between-group difference ( - 62 mL) was well within the noninferiority margin ( - 100 mL), the HFA formulation was deemed clinically noninferior to the CFC formulation. This finding was supported by secondary efficacy assessments. Both formulations of IB/SAL were well tolerated during the prolonged multiple dosing. Conclusion: It is concluded that IB/SAL-HFA pMDI provides effective bronchodilation of similar degree to that achieved with IB/SAL-CFC pMDI. Therefore, IB/SAL-HFA pMDI is a valuable alternative to IB/SAL-CFC pMDI.
Mental models, team mental models, and performance: Process, development, and future directions

Since the 1940s, researchers have grappled with the notion of a mental model. The concept is eminently reasonable and somewhat seductive, but presents us with a number of difficulties regarding its incompleteness, multiplicity, and inconsistency. Not the least of these difficulties is the problem of “capturing” (measuring) mental models, and still more difficult, capturing a team mental model, an extension of the earlier term. Once captured, finding an appropriate analytic procedure to analyze team mental models has challenged researchers for a long time. Nonetheless, the literature suggests that the construct is well worth the trouble, with many applied benefits especially to industry. In the present work we set out to (a) review the notion of team mental models (TMM); (b) identify the key concepts and thinking behind their development; (c) demonstrate how they support teamworking performance; and (d) outline a three‐phase model of TMM development. Details on TMM measurement are given, before concluding with a discussion of the difficulties facing researchers who wish to study and utilize the notion, and some of the pressing research issues that need investigation. © 2004 Wiley Periodicals, Inc. Hum Factors Man 14: 331–352, 2004.
Encoded Prior Sliced Wasserstein AutoEncoder for learning latent manifold representations

While variational autoencoders have been successful in several tasks, the use of conventional priors are limited in their ability to encode the underlying structure of input data. We introduce an Encoded Prior Sliced Wasserstein AutoEncoder wherein an additional prior-encoder network learns an embedding of the data manifold which preserves topological and geometric properties of the data, thus improving the structure of latent space. The autoencoder and prior-encoder networks are iteratively trained using the Sliced Wasserstein distance. The effectiveness of the learned manifold encoding is explored by traversing latent space through interpolations along geodesics which generate samples that lie on the data manifold and hence are more realistic compared to Euclidean interpolation. To this end, we introduce a graph-based algorithm for exploring the data manifold and interpolating along network-geodesics in latent space by maximizing the density of samples along the path while minimizing total energy. We use the 3D-spiral data to show that the prior encodes the geometry underlying the data unlike conventional autoencoders, and to demonstrate the exploration of the embedded data manifold through the network algorithm. We apply our framework to benchmarked image datasets to demonstrate the advantages of learning data representations in outlier generation, latent structure, and geodesic interpolation.
Increased expression of Toll-like receptor 5 during progression of cervical neoplasia

The purpose of this study was to determine whether Toll-like receptor 5 (TLR5) expression was associated with disease progression in cervical neoplasia. TLR5 expression was evaluated by immunohistochemistry (IHC) in 55 formalin-fixed paraffin-embedded cervical tissues; 10 normal cervical specimens, 9 low-grade cervical intraepithelial neoplasias (CINs), 12 high-grade CINs, and 24 invasive squamous cell carcinomas (ISCCs). TLR5 expression was also evaluated at the RNA level, in fresh, frozen cervical carcinoma tissues by real-time quantitative RT-PCR. TLR5 expression, which was mainly observed as cytoplasmic staining, gradually increased in accordance with the histopathologic grade in the following order: low-grade CIN less than high-grade CIN less than ISCC (P< 0.001). Immunohistochemical staining showed that TLR5 expression was undetectable (80%) or weak (20%) in normal cervical squamous epithelial tissues. However, moderate expression was detected in 33.3% of low-grade CIN (3/9), 41.7% of high-grade CIN (5/12), and 45.8% of ISCC (11/24). Strong expression was detected in as much as 33.3% of high-grade CIN (4/12) and 50% of ISCC (12/24). Contrary to IHC results, real-time quantitative RT-PCR revealed that TLR5 expression in tumors was not statistically different compared to normal cervical tissues (P= 0.1452). The IHC result suggests that TLR5 may play a significant role in tumor progression of cervical neoplasia and may represent a useful marker for malignant transformation of cervical squamous cells.
Stress Estimation in Reservoirs by a Stochastic Inverse Approach

The aim of this study is to estimate the initial stress in reservoirs before production using 3D calibrated geomechanical models. We propose an inverse method for estimating stress. Wellbore data can be integrated in a Mechanical Earth Model in order to estimate stresses nearby wells. It yields a first rough estimation in the whole reservoir by a simple interpolation which is not in equilibrium with the external forces and boundary conditions. From this rough stress field, the inversion aims at finding a physically acceptable stress state (i.e.: in equilibrium with the external forces and boundary conditions) that fit the local stresses wells. The forward problem is ensured by a Finite Element Analysis which is able to take into account structures such as faults, which have a significant influence on the stress magnitude and orientation. Inverse loop stops when the stress computed near wells matches the one estimated using borehole data. The uncertainties on the boundary conditions, elastic parameters and the first stress estimation are taken into account with a stochastic approach. In this study, faults are built with a volumetric representation of the core and damage zone by introducing elastic parameters variations within. This representation is possible because only small deformations are expected.
Offline Meta-Reinforcement Learning with Advantage Weighting

Finn and Levine (2018) lay out conditions under which the MAML update procedure is universal, in the sense that it can approximate any function f(x,y,x∗) arbitrarily well (given enough capacity), where x and y are the support set inputs and labels, respectively, and x∗ is the test input. Universality in this sense is an attractive property because it implies that the update is expressive enough to approximate any update procedure; a method that does not possess the universality property might be limited in its asymptotic postadaptation performance because it cannot express (or closely approximate) the true optimal update procedure. In order for the MAML update procedure to be universal, several requirements of the network architecture, hyperparameters, and loss function must be satisfied. Most of these are not method-specific in that they stipulate minimum network depth, activation functions, and non-zero learning rate for any neural network. However, the condition placed on the loss function require more careful treatment. The requirement is described in Definition 1.
Overleaf Example

This paper considers the problem of managing single or multiple robots and proposes a cloud-based robot fleet manager, Adaptive Goal Management (AGM) System, for teams of unmanned mobile robots. The AGM system uses an adaptive goal execution approach and provides a restful API for communication between single or multiple robots, enabling real-time monitoring and control. The overarching goal of AGM is to coordinate single or multiple robots to productively complete tasks in an environment. There are some existing works that provide various solutions for managing single or multiple robots, but the proposed AGM system is designed to be adaptable and scalable, making it suitable for managing multiple heterogeneous robots in diverse environments with dynamic changes. The proposed AGM system presents a versatile and efficient solution for managing single or multiple robots across multiple industries, such as healthcare, agriculture, airports, manufacturing, and logistics. By enhancing the capabilities of these robots and enabling seamless task execution, the AGM system offers a powerful tool for facilitating complex operations. The effectiveness of the proposed AGM system is demonstrated through simulation experiments in diverse environments using ROS1 with Gazebo. The results show that the AGM system efficiently manages the allocated tasks and missions. Tests conducted in the manufacturing industry have shown promising results in task and mission management for both a single Mobile Industrial Robot and multiple Turtlebot3 robots. To provide further insights, a supplementary video showcasing the experiments can be found at https://github.com/mukmalone/ AdaptiveGoalManagement.