Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical and Technical Quantitative Methods for Risk Assessment in Public Crisis Management

The article shows that in crisis management, risks can be effectively analysed and managed by rational use of mathematical and technical methods. It presents two quantitative methods for risk assessment and a procedure for transferring the results to logistical social networks (LSNs). The need to use social logistical networks, where modern techniques can be applied, including the Internet of Things (IoT) or Machine-to-Machine (M2M) communication, enabling the collection of any amount of data to logistical social networks, is indicated. The article stresses that research on public crisis management must be interdisciplinary in nature, taking into account all aspects of security management, including social, technical and economic issues. Modern methods of assessing the state and risk of a crisis situation of individual elements of the systems generate an increasing number of data, the collection, collection, processing and sharing of which requires ensuring information security and protecting the personal freedom of the individual.
Comparison of Unmanned Aerial Vehicle-LiDAR and Image-Based Mobile Mapping System for Assessing Road Geometry Parameters via Digital Terrain Models

Road condition analysis is an important research topic in many fields (such as intelligent transportation, road safety, road design analysis, and traffic analysis) and depends on road geometry parameters such as longitudinal profile and cross-slope. In this study, the extraction of road geometry parameters by unmanned aerial vehicle (UAV) with LiDAR and by a mobile photogrammetric system (MPS) designed by our research group was investigated. The purpose of this study was to obtain geometric parameters (such as road longitudinal profile and cross-slope) by using digital terrain model (DTM) surfaces derived from point cloud data acquired using UAV-LiDAR and MPS. For this purpose, a framework was developed for the extraction and comparison of longitudinal and cross-sectional profiles. First, the ground filtering approach was used to extract ground points and DTM surfaces generated from an appropriate interpolation algorithm by using ground points. Cross-sectional/longitudinal profiles of the road sections were extracted and compared with reference data. A comparison of the longitudinal profiles obtained from DTMs derived from the MPS and from UAV-LiDAR revealed root mean square error values of 1.8 cm and 2.3 cm, respectively. The average deviation of cross-slopes for both surfaces was 0.19% and 0.18%, respectively. These results show that road geometric parameters can be obtained from DTM surfaces with high accuracy. It can be concluded from the results of this study that MPS can be a favorable alternative for studies on road geometry parameters extraction.
Error exponents for optimum decoding of the degraded broadcast channel using moments of type class enumerators

The analysis of random coding error exponents pertaining to optimal decoding in a degraded broadcast with degraded message sets is revisited. Instead of using Jensens inequality as well as some other inequalities in the derivation, we demonstrate that, after an initial step, an exponentially tight analysis can be carried out by assessing the relevant moments of a certain type class enumerator.
Dilated Cardiomyopathy: Beware of Diet Drugs Slimming the Heart

There have been rare reports of dilated cardiomyopathy from chronic use of phentermine/topiramate, although very limited data are available. Phentermine is an atypical amphetamine analog that has been contraindicated in patients with a history of cardiovascular disease. We present a case of nonischemic dilated cardiomyopathy in the setting of chronic phentermine/topiramate use, which is the most likely cause of her dilated cardiomyopathy.
Urinary Biomarkers and Point-of-Care Urinalysis Devices for Early Diagnosis and Management of Disease: A Review

Biosensing and microfluidics technologies are transforming diagnostic medicine by accurately detecting biomolecules in biological samples. Urine is a promising biological fluid for diagnostics due to its noninvasive collection and wide range of diagnostic biomarkers. Point-of-care urinalysis, which integrates biosensing and microfluidics, has the potential to bring affordable and rapid diagnostics into the home to continuing monitoring, but challenges still remain. As such, this review aims to provide an overview of biomarkers that are or could be used to diagnose and monitor diseases, including cancer, cardiovascular diseases, kidney diseases, and neurodegenerative disorders, such as Alzheimer’s disease. Additionally, the different materials and techniques for the fabrication of microfluidic structures along with the biosensing technologies often used to detect and quantify biological molecules and organisms are reviewed. Ultimately, this review discusses the current state of point-of-care urinalysis devices and highlights the potential of these technologies to improve patient outcomes. Traditional point-of-care urinalysis devices require the manual collection of urine, which may be unpleasant, cumbersome, or prone to errors. To overcome this issue, the toilet itself can be used as an alternative specimen collection and urinalysis device. This review then presents several smart toilet systems and incorporated sanitary devices for this purpose.
[O II]and Continuum Structure in Radio-Loud QSOs to Z = 0.9

Images have been obtained in R band and redshifted 100A band [O II] with the High Resolution Camera of the Canada-France-Hawaii Telescope. Ten quasi-stellar objects were observed, with redshifts from 0.36 to 0.91, with radio structures ranging from unresolved to large double-lobed. The images have a mean full width at half maximum 0.64 arcsec, and a spread from 0.45 to 0.80. Extended emission line structure is seen in all cases, with a variety of properties. In particular, in four of the six large radio sources, the emission line gas appears to be associated with the radio structure
Phase dynamics of freely swimming foils

Abstract A two-dimensional D-shaped cylinder and heaving foil were mounted in tandem and used to simulate the main body and tail, respectively, of a natural swimmer. Thrust/drag measurements of the force on the foil and particle image velocimetry measurements of the flow downstream of the swimming system were conducted at a Reynolds number of about $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}10^4$ in a water channel with a constant free stream current speed. Two main sets of measurements were conducted: one set with the swimming system locked at a fixed streamwise location in the water channel as the heave frequency of the foil was varied; the other set with the system freely swimming to a desired set-point position from different upstream and downstream locations. When the freely swimming system reached and maintained its set-point position, so that its swimming speed matched that of the current, the oscillation frequency of the heaving foil corresponded to a Strouhal number of 0.36. Phase portraits of the measured thrust/drag forces reveal limit cycle oscillations for all swimming cases studied, which suggests that self-regulation drives the selection of this Strouhal number. No coupling was observed between the vortices shed by the D-shaped cylinder and the self-selected frequency of the heaving foil during free swimming. An examination of the ratio of the phase-locking indices for the input heaving motion of the foil and the coupled fluidic thrust/drag response reveals that it approaches a value of 0.5 over time when the freely swimming system is released from rest and allowed to achieve steady-state cruising. The jet produced by the freely swimming foil was inclined at an angle of approximately $4^\circ $ with respect to the direction of the mean flow.
GeoDanceHive: An Operational Hive for Honeybees Dances Recording

Simple Summary Honeybees are known for their ability to communicate about resources in their environment. They inform the other foragers by performing specific dance sequences according to the spatial characteristics of the resource. The purpose of our study is to provide a new tool for honeybees dances recording, usable in the field, in a practical and fully automated way, without condemning the harvest of honey. We designed and equipped an outdoor prototype hive, later called “GeoDanceHive”, allowing the continuous recording of honeybees’ dances and their analysis. The use of the GeoDanceHive is designed for a wide range of users, who can meet different objectives, such as researchers or professional beekeepers. Thus, our hive is a powerful tool for honeybees studies in the field and could highly contribute to facilitating new research approaches and better understanding landscape ecology of key pollinators. Abstract Honeybees are known for their ability to communicate about resources in their environment. They inform the other foragers by performing specific dance sequences according to the spatial characteristics of the resource. The purpose of our study is to provide a new tool for honeybees dances recording, usable in the field, in a practical and fully automated way, without condemning the harvest of honey. We designed and equipped an outdoor prototype of a production hive, later called “GeoDanceHive”, allowing the continuous recording of honeybees’ behavior such as dances and their analysis. The GeoDanceHive is divided into two sections, one for the colony and the other serving as a recording studio. The time record of dances can be set up from minutes to several months. To validate the encoding and sampling quality, we used an artificial feeder and visual decoding to generate maps with the vector endpoints deduced from the dance information. The use of the GeoDanceHive is designed for a wide range of users, who can meet different objectives, such as researchers or professional beekeepers. Thus, our hive is a powerful tool for honeybees studies in the field and could highly contribute to facilitating new research approaches and a better understanding landscape ecology of key pollinators.
Research on the main elements of mimic platforms

Cyber Mimic Defense (CMD) is a new generation of active defense technology after firewall, intrusion and other traditional defense technology. It aims to deal with uncertain threats in the network environment with visual uncertainty. This paper briefly introduces the architecture and principle of CMD and defines four main elements of the current simulation platform: system architecture, heterogeneous policy, scheduling policy and voting policy. Combined with examples, the four elements are respectively summarized. The system architecture is divided into C mode and D mode, and the heterogeneous strategy includes implementation mode, implementation method and synchronization mode. Scheduling policies are classified into offline policies and online policies. Voting policies include voting algorithms, voting levels, and delay control.
The Gemini-Monoceros X-ray enhancement - A giant X-ray ring

A 1/sup 0/. 5 spatial resolution map of the 1/4 keV diffuse X-ray background enhancement in the Gemini and Monoceros constellations shows a striking, circular, ring-shaped emission feature with a diameter of about 20/sup 0/. At a distance of 300 pc, the region has a radius of 50 pc and, for a spectral temperature of 3 x 10/sup 6/ K, an emitting electron density of 0.01 cm/sup -3/. We discuss this feature and, also, the possible X-ray contribution from the Mon OB1 association and neighboring supernova remnants.
[3+3]-Annulation of Cyclic Nitronates with Vinyl Diazoacetates: Diastereoselective Synthesis of Partially Saturated [1,2]Oxazino[2,3-b][1,2]oxazines and Their Base-Promoted Ring Contraction to Pyrrolo[1,2-b][1,2]oxazine Derivatives

A rhodium(II)-catalyzed reaction of cyclic nitronates (5,6-dihydro-4H-1,2-oxazine N-oxides) with vinyl diazoacetates proceeds as a [3+3]-annulation producing bicyclic unsaturated nitroso acetals (4a,5,6,7-tetrahydro-2H-[1,2]oxazino[2,3-b][1,2]oxazines). Optimization of reaction conditions revealed the use of Rh(II) octanoate as the preferred catalyst in THF at room temperature, which allows the preparation of target products in good yields and excellent diastereoselectivity. Under basic conditions, namely, the combined action of DBU and alcohol, these nitroso acetals undergo ring contraction of an unsaturated oxazine ring into the corresponding pyrrole. Both transformations can be performed in a one-pot fashion, thus constituting a quick approach to oxazine-annulated pyrroles from available starting materials, such as nitroalkenes, olefins, and diazo compounds.
Entity extraction based on the parts of speech attention mechanism

Entity extraction is an information extraction technique that aims to locate and classify named entities (e.g., organizations, locations, persons.), which is a very important and fundamental problem in natural language processing. On the research of entity extraction, numerous models ignore the learning of grammatical structure. Considering the shortcomings of previous models, this paper first proposes the PALC (POStag-Attention-LSTM-CRF) model, which adds POS (part of speech) features to entity extraction. Specially, PALC fuses POS features with other features through a multi-layer bidirectional LSTM network and attention mechanism to improve the effect of entity extraction. The experimental results show that the accuracy of the PALC model in this paper on the CONLL03 dataset can be 90.65%, on the CONLL03 dataset can be 84.86%, and on OntoNote 5.0 English dataset can be 86.99%.
Comportamiento singular de las amplitudes de scattering en el límite colineal

Actualmente los grandes aceleradores de particulas permiten obtener resultados experimentales muy certeros. Como maximo ejemplo tenemos el LHC, que recientemente descubrio una nueva particula con propiedades compatibles con las correspondientes al boson de Higgs. Para poder comprender mejor la naturaleza de dicha particula, asi como tambien otros fenomenos en el [. ]
Image Acquisition, Preprocessing and Pill Segmentation for the Pilled Fabric Based on Light Projection

A new objective method based on light projection and image analysis techniques for assessing fabric pilling is presented in this paper. A series of images were captured with a CCD camera and the method of light projecting on the cross section of the pilled fabric at first. Then with proper edge detection and linear interpolation for each of the cross section images, its profile line can be extracted. Combining all profile lines, a three dimensional profile which reflects the protruding pills on the fabric surface was obtained and then preprocessed. And finally pills can be effectively segmented by adaptive threshold. The experimental results show that the method presented for recognizing the pills was satisfied.
A stable and robust ICA algorithm based on t-distribution and generalized Gaussian distribution models

We propose a novel independent component analysis (ICA) algorithm which enables one to separate mixtures of sub-Gaussian, super-Gaussian and Gaussian primary source signals. Alternative activation functions in the algorithm are derived by using parameterized t-distribution and generalized Gaussian distribution density models. The functions are self-adaptive based on estimating the high-order moments of extracted signals. Moreover, a stability condition of the proposed algorithm for separating the true solution is given. Simulation experiment results are presented to illustrate the effectiveness and performance of the proposed algorithm.
Complex permittivity and permeability of iron-based composite absorbers measured by cavity perturbation method in X-band frequency range

A cavity perturbation resonance technique is used to determine the complex permittivity and permeability of iron-based composite absorbers prepared by mixing various weight percentages of carbonyl iron powder with epoxy as the matrix. The complex permittivity (e′-je″) and permeability (μ′-jμ″) are measured around X-band (7–12.5 GHz for permittivity and 7.5–14 GHz for permeability) by the cavity perturbation resonance technique and the results are compared with those obtained by the transmission/reflection method. Experimental results show that the average differences of real parts of permittivity (e′) and real and imaginary parts of permeability (μ′ and μ″) measured by these two techniques are less than 10%. The differences in e″, however, is apparently higher than the others. As a general trend, the difference increases with increasing weight percentage of carbonyl iron.
Features of Crevice Corrosion of Different Grades of Duplex Stainless Steels

Duplex stainless steels (DSSs) are being increasingly employed in the oil and gas and chemical industries, which, despite their high alloying degree and high resistance to general corrosion, are subject to pitting and crevice corrosion. According to their resistance to pitting and crevice corrosion, steels are ranked according to the PREN. However, nowadays there are many grades of DSSs, in which the content of Cr, Mo and N varies in different quantities, therefore the selection of the grade must be carried out with great care, considering not only PREN, but also the production technology, operating conditions, and the geometry of products. The crevice corrosion behaviors of three grades of duplex stainless steels quenched from 1050, 1100 and 1200 °C were studied in FeCl3 solution at 50°C. It is shown that PREN allows to rank only different grades in terms of corrosion resistance. With a constant PREN value, but with different contents of ferrite and austenite in steel, completely different values of the corrosion rate can be obtained, therefore, PREN must be used with great care. It was found that in the studied steels, the optimal ferrite content, at which the lowest crevice corrosion rate is achieved, is at 65 vol.%.
A Min-Pooling Detection Method for Ship Targets in Noisy SAR Images

As the application of deep learning in general optical images becomes more and more widespread, the field of remote sensing images also begins to pay attention to the application of deep learning methods. Although deep learning detection algorithms have achieved better results than traditional detection algorithms, the detection results for poorly imaged SAR images still need improvement, and processing poorly imaged noisy SAR images is still a big challenge for existing algorithms. To address the problem of low precision and recall of existing algorithms for noisy SAR image detection, we propose a convolutional neural network detection algorithm based on min-pooling. First, we design a feature processing layer with min-pooling as the main structure to suppress the noise and then use a feature fusion layer to compensate for the missing information caused by pooling. To avoid problems such as redundancy in computation caused by the anchor-base algorithm, we choose the anchor-free algorithm as the main structure of ship detection. Finally, the model is evaluated using ordinary SAR image datasets and noisy SAR image datasets. Experiment results show that our proposed method has a better detection effect for noisy SAR images than other object detection models.
PCT theorem for fields with arbitrary high‐energy behavior

A neutral scalar field A(x) is considered that has to be smeared by Fourier transforms of C∞ functions with compact support but otherwise fulfills all the Wightman axioms, except strict local commutativity. It is shown to fulfill the PCT symmetry condition (where Ω denotes the vacuum state vector) 〈Ω‖A(x1) ⋅⋅⋅ A(xn)Ω〉 =〈Ω‖A(−xn) ⋅⋅⋅ A(−x1)Ω〉 if and only if 〈Ω‖A(x1) ⋅⋅⋅ A(xn)Ω〉 −〈Ω‖A(xn) ⋅⋅⋅ A(x1)Ω〉 can be represented, in a sense, as an infinite sum of derivatives of measures with supports containing no Jost points.
A Newton-Type Globally Convergent Interior-Point Method to Solve Multi-Objective Optimization Problems

This paper proposes an interior-point technique for detecting the nondominated points of multi-objective optimization problems using the direction-based cone method. Cone method decomposes the multi-objective optimization problems into a set of single-objective optimization problems. For this set of problems, parametric perturbed KKT conditions are derived. Subsequently, an interior point technique is developed to solve the parametric perturbed KKT conditions. A diﬀerentiable merit function is also proposed whose stationary point satisﬁes the KKT conditions. Under some mild assumptions, the proposed algorithm is shown to be globally convergent. Numerical results of unconstrained and constrained multi-objective optimization test problems are presented. Also, three performance metrics (modiﬁed generational distance, hypervolume, inverted generational distance) are used on some test problems to investigate the eﬃciency of the proposed algorithm. We also compare the results of the proposed algorithm with the results of some other existing popular methods.
A Trial of Adding Lung Protective Strategies to Existing Enhanced Recovery After Surgery Protocols and Its Effect on Improving Postoperative Lung Function

Background With this rising popularization of enhanced recovery after surgery (ERAS) protocols, it is important to ask if the current and developing pathways are fully comprehensive for the patient’s perioperative experience. Many current pathways discuss aspects of care including fluid management, pain management, and anti-emetic medication regiments, but few delineate recommendations for lung protective strategies. The hypothesis was that intraoperative lung protective strategies would results in improved postoperative lung function. Methods One hundred patients at the Medical University of South Carolina undergoing hepatobiliary and colorectal surgeries were randomized to receive intraoperative lung protective techniques or a standard intraoperative ventilation management. Three maximum vital capacity breaths were recorded preoperatively, and postoperatively 30 min, 1 h, and 2 h after anesthesia stop time. Average maximum capacity breaths from all four data collection interactions were analyzed between both study and control cohorts. Results There was no significant difference in the preoperative inspiratory capacity between the control and the ERAS group (2,043.3 ± 628.4 mL vs. 2,012.2 ± 895.2 mL; P = 0.84). Additional data analysis showed no statistically significant difference between ERAS and control groups: total average of the inspiratory capacity volumes (1,253.5 ± 593.7 mL vs. 1,390.4 ± 964.9 mL; P = 0.47), preoperative oxygen saturation (97.76±2.3% vs. 98.04±1.7%; P = 0.50), the postoperative oxygen saturation (98.51±1.4% vs. 96.83±14.2%; P = 0.40), and change in inspiratory capacity (95% confidence interval (CI) (-211.2 - 366.6); P = 0.60). Conclusions No statistically significant difference in postoperative inspiratory capacities were seen after the implementation of intraoperative lung protective strategies. The addition of other indicators of postoperative lung function like pneumonia incidence or length of inpatient stay while receiving oxygen treatment could provide a fuller picture in future studies, but a higher power will be needed.
The influence of vegetation on the development and structure of mountain waves

Abstract The influence of vegetative cover on the development of mountain waves is analyzed using a two-dimensional meso-β model. The model includes a detailed representation of surface fluxes and friction that evolve in time as the incoming solar radiation interacts with the soil and vegetation. Simulations of a zonal flow over a north-south-oriented ridge covered by different types of vegetation are presented and examined. The intensity of downslope winds and turbulent kinetic energy structure appear to be especially sensitive to the presence and type of vegetation. Model-predicted rainfall is also examined, indicating an enhancement when mountainous areas are covered by conifer forest.