Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Fire Attack Utilizing Interior and Exterior Streams on Fireﬁghter Safety and Occupant Survival: Air Entrainment

As research continues into how fire department interventions affect fire dynamics in the modern fire environment, questions continue to arise on the impact and implications of interior versus exterior fire attack on both firefighter safety and occupant survivability. Previous research into various types of fire ground ventilation, flow paths, and exterior fire streams has provided the fire service with an increased understanding of fire dynamics. However, in some instances, the information from the studies did not support current, experience-based practices. This gap between the research to date and the fire ground suppression experience has driven the need for further study. This study will build upon the fire research conducted to date by analyzing how firefighting tactics, specifically different fire suppression tools and tactics, affect the thermal exposure and survivability of both firefighters and building occupants and affect fire behavior in structures. The purpose of this study is to improve firefighter safety, fire ground tactics, and the knowledge of fire dynamics by providing the fire service with scientific information, developed from water flow and full-scale fire testing, in representative single-family homes. This study will build and expand upon the fire research conducted to date by analyzing how firefighting tactics, specifically suppression methods, affect the thermal exposure and survivability of both firefighters and building occupants in addition to impacting fire behavior in structures. The purpose of this study is to improve firefighter safety, fireground tactics, and the knowledge of fire dynamics by providing the fire service with credible scientific information, developed from both water flow and full-scale fire testing, in representative single family homes. The project is comprised of 3 parts: • Part I: Water Distribution • Part II: Air Entrainment • Part III: Full-Scale Residential Fire Experiments This report details the results and analysis from the air entrainment testing. These tests were conducted without the presence of fire to gain a fundamental understanding of how hose streams entrain air. Each set of experiments was intended to add to the understanding of air entrainment and pressure from fire service hose streams by evaluating the differences caused by various application methods, hose stream types, nozzle movements, pressures/flow rates, manufacturers, and ventilation configurations.
Ultraviolet Nail Lamps and Squamous Cell Carcinoma: Cause and Effect, or Not?—A Case Report

Ultraviolet (UV) lamps are used in nail salons as part of standard gel nail manicures. While UV radiation is a known risk factor for the development of skin cancers, the risk from exposure to UV nail lamps is unclear. We present a case of a woman who developed squamous cell carcinoma in one finger after exposure to UV lamps. A discussion of the correlation between UV nail lamps and squamous cell carcinoma (SCC) is provided. Orthopedic surgeons frequently encounter skin cancers of the hand however the role of UV nail lamps has not yet been elucidated in the orthopedic literature. This manuscript aims to address that gap and facilitate patient counseling during such consultations.
A macro model in SMART SPICE to study the MOSFET degradations with CP technique

We have simulated the experimental charge pumping technique by the elaboration and the implementation of a macro model, in the electrical simular SMART SPICE on a personal computer. This macro model takes into account all the geometrical and electrical parameters of the studied transistor and gives their mathematical expressions. It also gives the different curves of the charge pumping current, which can be obtained experimentally by this technique versus different parameters, before or after different ageing stresses. The obtained results are compared to recent experimental results.
A nonreciprocal tunable waveguide directional filter using a turnstile open gyromagnetic resonator

The 4-port waveguide directional filter is a classic network in microwave engineering. The purpose of this paper is to describe one gyromagnetic version using an open gyromagnetic resonator in a dielectric-filled cavity. A property of the circuit is that it behaves as a 4-port circulator with one direction of circulation at one split frequency of the resonator and with the other direction for the other split frequency. An insertion loss between the coupled ports below 1.50 dB and an attenuation or isolation of typically 15 dB between the decoupled ports over most of the tuning range of the filter have been achieved. Its 3-dB bandwidth is typically 65 MHz. A typical tuning range of more than 1 GHz centered at about 10.5 GHz has been separately realized for each split branch. >
Blame mitigation: A less tidy take and its philosophical implications

ABSTRACT Why do we find agents less blameworthy when they face mitigating circumstances, and what does this show about philosophical theories of moral responsibility? We present novel evidence that the tendency to mitigate the blameworthiness of agents is driven both by the perception that they are less normatively competent – in particular, less able to know that what they are doing is wrong – and by the perception that their behavior is less attributable to their deep selves. Consequently, we argue that philosophers cannot rely on the case strategy to support the Normative Competence theory of moral responsibility over the Deep Self theory. However, we also outline ways in which further empirical and philosophical work would shift the debate, by showing that there is a significant departure between ordinary concepts and corresponding philosophical concepts, or by focusing on a different type of coherence with ordinary judgments.
Routing and permitting techniques of overweight vehicles

Overweight vehicles require permits to cross the highway bridges, which are designed for “design load vehicles” (prescribed in the national standards). A new, fast, and robust method is presented for the verification of bridges, which requires minimal input only: the axle loads, axle spacing, the bridge span(s), and the superstructure type. The bridge can be a single or a multispan girder, an arch bridge, a frame structure, or a box girder. The overweight vehicle may operate within regular traffic or it may cross the bridge at a given lane position while other traffic is prohibited on the bridge. The method is illustrated by numerical examples for deck-girder bridges and for a box girder.
Research on the Interaction of Genetic Algorithm in Assisted Composition

Computer-aided composition is an attempt to use a formalized process to minimize human (or composer) involvement in the creation of music using a computer. Exploring the problem of computer-aided composition can enable us to understand and simulate the thinking mode of composers in the special process of music creation, which is an important application of artificial intelligence in the field of art. Feature extraction on the MIDI files has been introduced in this paper. Based on the genetic algorithm in this paper, a platform of the sampling coding method to optimize the character representation has solved the traditional algorithmic music composition study. Music directly from the pitch and duration can be derived from the characteristics, respectively, in the form of a one-hot encoding independently said. Failure to the rhythm of the characterization of the pitch and duration are problems that lead to the inability of compositional networks to learn musical styles better. Rhythm is the combination of pitch and time values according to certain rules. The rhythm of music affects the overall style of music. By associating the pitch and time value coding, the rhythm style of music can be preserved better so that the composition network can learn the style characteristics of music more easily.
Accuracy of coupling computations and its application to DR filter design

Coupling of two circular cavities by a rectangular iris computed by the improved large aperture theory and by the full wave mode matching technique are compared. It is found that the improved large aperture approximation provides reasonable accuracy for a wide range of coupling values. The approximation is applied to design dielectric resonator (DR) filters in which rigorous computation of the couplings by the full wave mode matching method is quite difficult and time consuming. Excellent DR filter response is obtained with no adjustment of the coupling iris. <<ETX>>
ROTATING STEP BY STEP PIEZOMOTOR FOR NANOPOSITIONING & SPACE APPLICATIONS

Piezomotors are well known in various applications where high precision actuation is required like AFM or handling equipment for semiconductor production. Their specific low speed in direct drive and high torque characteristics combined with high holding torque in off power conditions make them very attractive for any positioning application and especially space mechanisms where low electrical consumption is always sought. A new concept of rotating stepping piezomotor has been developed in the frame of the LISA space project where the mechanism of the telescope orientation was addressed. A full space qualification campaign has been carried out on the piezomotor model. Both thermal behaviour on a [-25, 75]°C range, and a 5.10 5 cycles lifetime have been validated whereas the vibration test was partially successful. The motor characteristics unchanged after the lifetime test display a ±1° rotation angle and a 0.05 rpm speed at 50Hz driving and a positioning resolution measured around 200 nrad. These reliable and high motor performances can answer to demanding positioning requirement including moreover non magnetic specification.
Use of Radial Basis Function Type Artificial Neural Networks for Runoff Simulation

In this paper, the applicability of the radial basis function (RBF) type artificial neural networks (ANNs) approach for modeling a hydrologic system is investigated. The method differs from the more widely used multilayer perceptron (MLP) approach in that the nonlinearity of the model is embedded only in the hidden layer of the network. Search for optimal model parameters is carried out in two steps, each of which can be made to be more efficient and much faster than in MLP. This approach is applied to simulate runoff discharges in a small catchment. The results show that the models based on RBF networks can predict runoff with accuracy comparable with that with the MLP approach. An added advantage of RBF network‐based models is that they can be developed with relative ease and with much less time compared with their MLP counterparts.
High sensitivity and broad detection range flexible capacitive pressure sensor based on rGO cotton fiber for human motion detection

Recently, flexible pressure sensors have attracted considerable interest in electronic skins, wearable devices, intelligent robots and biomedical diagnostics. However, the design of high sensitivity flexible pressure sensors often relies on expensive materials and complex process technology, which greatly limit their popularity and applications. Even worse, chemical-based sensors are poorly biocompatible and harmful to the environment. Here, we developed a flexible capacitive pressure sensor based on reduced graphene oxide cotton fiber by a simple and low-cost preparation process. The environmentally friendly sensor exhibited a comprehensive performance with not only ultra-high sensitivity (up to 15.84 kPa−1) and a broad sensing range (0–500 kPa), but also excellent repeatability (over 400 cycles), low hysteresis (⩽11.6%), low detection limit (<0.1 kPa) and wide frequency availability (sensitivity from 19.71 to 11.24 kPa−1, frequency from 100 Hz to 10 kHz). Based on its superior performance, the proposed sensor can detect various external stimuli (vertical stress, bending and airflow) and has been successfully applied for facial expression recognition, breathing detection, joint movement and walking detection, showing great potential for application in artificial electronic skin and wearable healthcare devices.
Neural-network-based space-vector pulse-width modulation for capacitor voltage balancing of threephase three-level improved power quality converter

In this study, an artificial neural-network (ANN)-based space-vector pulse-width modulation (SVPWM) for capacitor voltage balancing of a three-phase three-level neutral-point clamped converter with improved power quality is presented. The neural-network-based controller offers the advantage of very fast implementation of the SVPWM algorithm. This makes it possible to use an application specific integrated circuit chip in place of a digital signal processor. The proposed scheme employs single layer feed-forward neural-networks at different stages along with a control algorithm using modified reference vector for capacitor voltage balancing of an improved power quality three-phase neutral-point clamped converter. In other words, the neural-network receives three-phase voltages and currents as input and generates symmetrical pulse-width modulation waves for three phases of the converter. A simulated digital signal processor (DSP)-based modulator generates the data which are used to train the network by a back-propagation algorithm in the MATLAB Neural Network Toolbox. The simulation of converter with ANN-based space-vector modulator shows excellent performance when compared with that of conventional DSP-based modulator.
A comparison of four methods for bubble size and void fraction measurements

We compare the performance of four different bubble-sensing techniques in a range of environment from the surf zone to the open ocean: a remote sensing method using high-frequency backscatter, two in situ methods using an acoustical resonator and a pulse propagation sensor, and a bulk method using electrical conductivity. Comparisons between the techniques show general consistency within the appropriate operational bubble density ranges, although spatial variability in bubble clouds introduces substantial variance. Each technique has its strengths and limitations. Our acoustical resonator is suitable for bubble concentrations with air fractions greater than approximately 10/sup -9/ and the pulse propagation sonar for air fractions from 10/sup -6/; the upper limit for both is constrained by attenuation and the validity of the Foldy scattering approximation. Both sensors can be implemented to encompass a wide frequency range with high resolution, corresponding to resonant bubble radii of 10/spl sim/1200 /spl mu/m. For air fractions higher than /spl sim/5/spl times/10/sup -4/, bulk measurement using electrical conductivity provides a measure of air fraction. Sufficient overlap in operational air-fraction range exists between in situ acoustical techniques and conductivity measurement to permit comparison and demonstrate consistency in the measurement. Single- and multi-frequency backscatter sonars may be used for low air fractions (<1/spl times/10/sup -5/) and provide a continuous vertical profile from a deployment beneath the active surface zone, but are subject to masking by dense bubble clouds and are unable to resolve high air fractions close to the surface. This study suggests that the best approach is to use a combination of sensors to probe the bubble field.
Diagnosis for Vibration Fault of Steam Turbine Based on Modified Particle Swarm Optimization Support Vector Machine

Due to the influence of artificial factor and slow convergence of particle swarm algorithm (PSO) during parameters selection of support vector machine (SVM), this paper proposes a modified particle swarm optimization support vector machine (MPSO-SVM). A Steam turbine vibration fault diagnosis model was established and the failure data was used in fault diagnosis. The results of application show the model can get automatic optimization about the related parameters of support vector machine and achieve the ideal optimal solution globally. MPSO-SVM strategy is feasible and effective compared with traditional particle swarm optimization support vector machine (PSO-SVM) and genetic algorithm support vector machine (GA-SVM).
A PLASTIC PACKAGE GaAs MESFET 5.8GHZ RECEIVER FRONT-END WITH ON-CHIP MATCHING FOR ETC SYSTEM

A plastic package GaAs MESFET receiver front-end monolithic microwave integrated circuit operating at 5.8 GHz is presented in this paper. It has a two-stage low-noise amplifier followed by a dual-gate mixer. Operating at 3 V and 8.3 mA, a conversion gain of 20.4 dB, noise figure of 4.1 dB, and high port-to-port isolations have been achieved. Total chip size of 1.0/spl times/0.9 mm/sup 2/ has been achieved through on-chip matching for both RF and local-oscillator ports and the use of simple two-element matching networks for all interstage matching. The 3-dB bandwidth of conversion gain is 1 GHz.
The Effect of a Mindfulness-Based Education Program on Brain Waves and the Autonomic Nervous System in University Students

Background: Mindfulness, defined as the awareness emerging from purposefully paying attention to the present moment, has been shown to be effective in reducing stress and, thus, promoting psychological well-being. This study investigated the effects of a mindfulness-based education program on mindfulness, brain waves, and the autonomic nervous system (ANS) in university students in Korea. Methods: This study is a quantitative and experimental research with a single-group pre-post design. Six sessions of mindfulness-based intervention were applied. In total, 42 students completed a mindfulness questionnaire before and after the intervention, and 28 among them completed pre-intervention and post-intervention measures of brain waves and ANS. Results: The level of mindfulness increased in the participants after intervention. Regarding brain waves, the alpha and theta waves increased, but the beta waves decreased. There was no significant difference in the ANS, presenting no change in heart rate variability. Conclusions: We identified the positive effects of the mindfulness-based education program for university students. The findings indicate that this program may help students not only relax, but also generate a mindfulness state in stressful situations, potentially leading to a successful university life. This study can be used as a basis for quality improvement and sustainability of mindfulness-based education programs for university students.
Capacitive Readout System for Micro Sensors and Actuators With Automatic Parasitic Cancellation

In this article, a capacitive readout system with automatic parasitic capacitance cancellation function is designed and implemented. The readout system is implemented with discrete components on a board level. The parasitic cancellation is realized by matching a digital programmable capacitor to the parasitic capacitance using a PI controller. The function of the readout system is verified by using standard ceramic capacitors and a MEMS micromirror device. Capacitance measurements up to 35 pF for ceramic capacitors are performed, the maximum error between the measurement results of the circuit and an LCR meter is 0.07 pF. For MEMS micromirror, the circuit cancels the parasitic capacitance of 32.63 pF and realizes a measurement error within 0.06 pF. The proposed system can be used as a proof-of-concept platform demonstrating the feasibility of the generic parasitic cancellation method for MEMS sensors and actuators.
The Relationship Between Summer Weather and Summer Loads - A Regression Analysis

When summer air conditioning contributes significantly to an electric utility's system peak load, it is useful, for load forecasting purposes, to separate total system load into two components: temperature-sensitive load and nontemperature-sensitive load. Examination of historical data indicates that temperature-sensitive loads depend not only upon coincident but also antecedent weather conditions. Regression analysis techniques using a digital computer have shown that the combined effect of these weather conditions can be expressed by one composite weather variable (WV). Total system load can then be expressed as Basic Load plus the product of WV times a coefficient of air-conditioning saturation. Results obtained by application of this method to historical data (1949-1964) of Public Service Electric and Gas Company are presented.
Energy savings potential by substituting driving with walking and cycling for short distance

Vehicles energy consumption produces several emissions such as carbon dioxide (CO2 ), nitrogen oxide (NOx ) and noise. This paper attempts to evaluate potential reduction in oil consumption and CO2 emissions if the obese and overweight conditions were eliminated from the adult population through the use of walking or cycling for transportation, and if individuals between the ages of 10 and 64 adopted recommended levels of daily exercise by walking or cycling instead of driving. Substantial co-benefits accompany widespread adoption of physical activity. The results found that the reductions in emissions from substituting driving with walking and cycling are significant enough to show a possible improvement of air quality. The highest reduction of CO2 emissions comes from the substitution of driving with exercising by cycling for 7 hours a week, which amounts to 2.38 Tg (Teragram) of reduction.Copyright © 2008 by ASME
A Unified Perspective for Disinformation Detection and Truth Discovery in Social Sensing: A Survey

With the proliferation of social sensing, large amounts of observation are contributed by people or devices. However, these observations contain disinformation. Disinformation can propagate across online social networks at a relatively low cost, but result in a series of major problems in our society. In this survey, we provide a comprehensive overview of disinformation and truth discovery in social sensing under a unified perspective, including basic concepts and the taxonomy of existing methodologies. Furthermore, we summarize the mechanism of disinformation from four different perspectives (i.e., text only, text with image/multi-modal, text with propagation, and fusion models). In addition, we review existing solutions based on these requirements and compare their pros and cons and give a sort of guide to usage based on a detailed lesson learned. To facilitate future studies in this field, we summarize related publicly accessible real-world data sets and open source codes. Last but the most important, we emphasize potential future research topics and challenges in this domain through a deep analysis of most recent methods.