Miracle-dz/UniFAR-FTUs huggingface dataset:
GENII: The Hanford Environmental Radiation Dosimetry Software System: Volume 2, Users' manual: Hanford Environmental Dosimetry Upgrade Project

The Hanford Environmental Dosimetry Upgrade Project was undertaken to incorporate the internal dosimetry models recommended by the International Commission on Radiological Protection (ICRP) in updated versions of the environmental pathway analysis models used at Hanford. The resulting second generation of Hanford environmental dosimetry computer codes is compiled in the Hanford Environmental Dosimetry System (Generation II, or GENII). The purpose of this coupled system of computer codes is to analyze environmental contamination of, air, water, or soil. This is accomplished by calculating radiation doses to individuals or populations. GENII is described in three volumes of documentation. This second volume is a Users' Manual, providing code structure, users' instructions, required system configurations, and QA-related topics. The first volume describes the theoretical considerations of the system. The third volume is a Code Maintenance Manual for the user who requires knowledge of code detail. It includes logic diagrams, global dictionary, worksheets, example hand calculations, and listings of the code and its associated data libraries. 27 refs., 17 figs., 23 tabs.
Localization of Amplitude-Panned Virtual Sources I: Stereophonic Panning

The localization of amplitude-panned virtual sources is investigated in a stereophonic setup with listening tests and with a model of directional hearing. The interaural time difference (ITD) cue is found to be consistent at low frequencies, which is in agreement with earlier studies. It is also shown that the high-frequency interaural level difference (ILD) cues roughly propose the same directions as low-frequency ITD cues. However, the ITD and ILD cues suggest different directions at most frequencies, and both cues deviate from general behavior near 1700 Hz.
Extreme Low-Power Mixed Signal IC Design: Subthreshold Source-Coupled Circuits

Design exibility and power consumption in addition to the cost, have always been the most important issues in design of integrated circuits (ICs), and are the main concerns of this research, as well. Energy Consumptions: Power dissipation (P ) and energy consumption are - diss pecially importantwhen there is a limited amountof power budgetor limited source of energy. Very common examples are portable systems where the battery life time depends on system power consumption. Many different techniques have been - veloped to reduce or manage the circuit power consumption in this type of systems. Ultra-low power (ULP) applications are another examples where power dissipation is the primary design issue. In such applications, the power budget is so restricted that very special circuit and system level design techniquesare needed to satisfy the requirements. Circuits employed in applications such as wireless sensor networks (WSN), wearable battery powered systems [1], and implantable circuits for biol- ical applications need to consume very low amount of power such that the entire system can survive for a very long time without the need for changingor recharging battery[24]. Using newpowersupplytechniquessuchas energyharvesting[5]and printable batteries [6], is another reason for reducing power dissipation. Devel- ing special design techniques for implementing low power circuits [79], as well as dynamic power management (DPM) schemes [10] are the two main approaches to control the system power consumption. Design Flexibility: Design exibility is the other important issue in modern in- grated systems.
Modelling, stability and biomechanical implications of three DOF passive bipedal gait

Passive dynamic walkers can achieve a steady gait down an inclined plane simply by the influence of gravity. This article presents the modelling of a 3 DOF passive bipedal walker, searching for a relationship between gait characteristics, the robot's physical properties and the slope of the plane. The proposed adimensional dynamical model’s equations are also given, implementing and modelling the dynamics is described and the main results are presented. Limits on robotic parameters leading to establishing stable limit cycles are also analysed as periodic doubling bifurcations appear to be natural in passive gait. Interesting results arose when comparing natural passive walking with human bipedal locomotion.
A 25 Gb/s Silicon Photonics Platform

Silicon has attracted attention as an inexpensive and scalable material system for photonic-electronic, system-on-chip development. For this, a platform with both photodetectors and modulators working at high speeds, with excellent cross-wafer uniformity, is needed. We demonstrate an optical-lithography, wafer-scale photonics platform with 25 Gb/s operation. We also demonstrate modulation with an ultra-low drive voltage of 1 Vpp at 25 Gb/s. We demonstrate attractive cross-wafer uniformity, and provide detailed information about the device geometry. Our platform is available to the community as part of a photonics shuttle service.
An Improved Mechanism for SDN Flow Space to Control Oriented Authentication NAA Network

The Open Daylight platform with its power by working with IEEE 802.1X port level authentication for wired and wireless networks has been very supportive because of the massive deployments at mean charge for main design considerations. Within the current marketplace, 802.1X has flourished the ground works for wireless, wire stability, LAN stability and authentication methods. EAP (Extensible Authentication Protocol) supports long time protection of the supplicant and the authentication software till the end condition of the RADIUS (Remote Authentication Dial-In User Service) server is met. This paper is focused on the RAR (RADIUS Access Request) unique identification about the users on the network with SAA (Supplicant, Authenticator and Authentication server) system which records on the attribute cost of RFC 2865 according to the forwarding server. NAA (Non-Adaptive Algorithm) using FlowVisor based virtualization packages drive inward the network timescales or statistics, dynamically controlling the flow space of switches to control the speed and results in scaling of networks. NAA is an application level protocol that contains authentication and configuration information between a Network Access Server and a shared authentication server. It avoids the attacker from listening for requests and responses from the server and calculates the improved MD5 client secret key of the response.
Multi-organizational Emergency Response Management - A Framework for Further Development

This doctoral thesis suggests a framework for how multi-organizational emergency response management can be understood. A method for collecting and analyzing data on individuals and their interactions has been developed and tested. The method is rooted in social network theory and facilitates further exploration of the complexity associated with responses to emergencies in which various resources from different segments of the society are engaged. Furthermore, in order to build a framework for understanding, the concepts of command and control, coordination, emergence, and trust are elucidated and related to empirical analyses. A synthesis of empirical analyses and literature studies is presented as a model to show how multi-organizational emergency response management can be better understood by studying interactions between individuals. Interactions are prerequisites for coordination of activities. Such activities can be both planned and emergent. Both the manifestation of an interaction and the actual coordination activity are influenced by normative ideals and interpersonal trust. The system designers and emergency response managers should acknowledge this complexity and develop strategies to harmonize the local adaptive behavior of a multi-organizational emergency response system. (Less)
P- and S-phase data from local earthquakes in Southern California for 1966 to 1975

The purpose of this note is to describe a card-image computer tape now available with earthquake epicenter and P- and S-phase data for local earthquakes in Southern California during the 10-year period of 1966 through 1975. The tape is readable on an IBM 370/158 computer using standard FORTRAN READ statements. The tape is currently being used for several research projects including event relocation, velocity, P-delay, and magnitude studies. This research resource is being made available to all scientific investigators.
Calibration of a Circular Loop Antenna

The calibration of a measuring loop antenna means assigning an antenna factor K for each frequency in the entire measurement band. This factor can be found either by calculating the impedance of the loop or by using a well-defined standard magnetic field of a transmitting antenna. For both methods, it is necessary to obtain an accurate relation between the magnetic field and the geometric dimensions of the loops. Generally, a manufactured loop has a complex geometric shape with complex electrical behavior so that its impedance cannot be accurately determined analytically. In such cases, the standard magnetic field method remains as the only alternative for calibration. The formulas needed for implementation of the method, which takes into account the dimensions of the loops with finite conductor radii as well as the current distribution along the loop, are given. With the procedure presented here, the calibration is reduced to an accurate measurement of attenuation. Keywords: Calibration of circular loop antennas; circular loops with finite conductor radii; electrical properties of circular loops; impedance of a circular loop; loop antenna; antenna factor
Effect of Gender and Physical Activity Level on Sit-to-Stand Test Performance Among Young Adults

Bulgular: Kadın ve erkek katılımcılar arasında 5 tekrarlı OKT, 10 sn OKT, 30 sn OKT ve 60 sn OKT skorlarında istatistiksel olarak anlamlı farklılık tespit edildi (sırasıyla, p=0,004; p=0,002; p=0,000; p=0,000). OKT sonundaki yorgunluk seviyelerinde ise anlamlı bir fark bulunmadı (sırasıyla, p=0,636; p=0,295; p=0,888; p=0,150). Tüm katılımcıların haftalık enerji tüketimi değerleri 5 tekrarlı OKT skoru dışında tüm testlerle pozitif olarak ilişkili bulundu (sırasıyla, r=-0,458, p=0,000; r=0,427, p=0,001; r=0,606, p=0,000; r=0,545, p=0,000). Orta ve yüksek fiziksel aktivite seviyesine sahip katılımcıların OKT skorları karşılaştırıldığında istatistiksel olarak anlamlı farklar saptandı (sırasıyla, p=0,016; p=0,007; p=0,000; p=0,000).
Motor learning in practice : a constraints-led approach

Motor Learning in Practice explores the fundamental processes of motor learning and skill acquisition in sport, and explains how a constraints-led approach can be used to design more effective learning environments for sports practice and performance. Drawing on ecological psychology, the book examines the interaction of personal, environmental and task-specific constraints in the development of motor skills, and then demonstrates how an understanding of those constraints can be applied in a wide range of specific sports and physical activities.
A Literature Review of Financing Constraints of SMEs

SMEs are one of the important driving forces for China's market economy development, but SMEs are also generally faced with the constraints of financing constraints. Based on the systematic analysis of corporate finance theory, this paper analyzes the core reasons for SME financing constraints, as well as the mechanisms and advantages of relational financing, Internet finance and supply chain finance in alleviating the financing dilemma of SMEs, and finally proposes relevant policy recommendations.
Characterizing Human Explanation Strategies to Inform the Design of Explainable AI for Building Damage Assessment

Explainable AI (XAI) is a promising means of supporting human-AI collaborations for high-stakes visual detection tasks, such as damage detection tasks from satellite imageries, as fully-automated approaches are unlikely to be perfectly safe and reliable. However, most existing XAI techniques are not informed by the understandings of task-specific needs of humans for explanations. Thus, we took a first step toward understanding what forms of XAI humans require in damage detection tasks. We conducted an online crowdsourced study to understand how people explain their own assessments, when evaluating the severity of building damage based on satellite imagery. Through the study with 60 crowdworkers, we surfaced six major strategies that humans utilize to explain their visual damage assessments. We present implications of our findings for the design of XAI methods for such visual detection contexts, and discuss opportunities for future research.
Medicines Question Answering System, MeQA

In this paper we present the first system in Spanish capable of answering questions about medicines for human use, called MeQA (Medicines Question Answering), a project created by the Spanish Agency for Medicines and Health Products (AEMPS, for its acronym in Spanish). Online services that offer medical help have proliferated considerably, mainly due to the current pandemic situation due to COVID-19. For example, websites such as Doctoralia, Savia, or SaludOnNet, offer Doctor Answers type consultations, in which patients or users can send questions to doctors and specialists, and receive an answer in less than 24 hours. Many of the questions received are related to medicines for human use, and most can be answered through the leaflets. Therefore, a system such as MeQA capable of answering these types of questions automatically could alleviate the burden on these websites, and it would be of great use to such patients.
Adversarial GLUE: A Multi-Task Benchmark for Robustness Evaluation of Language Models

Large-scale pre-trained language models have achieved tremendous success across a wide range of natural language understanding (NLU) tasks, even surpassing human performance. However, recent studies reveal that the robustness of these models can be challenged by carefully crafted textual adversarial examples. While several individual datasets have been proposed to evaluate model robustness, a principled and comprehensive benchmark is still missing. In this paper, we present Adversarial GLUE (AdvGLUE), a new multi-task benchmark to quantitatively and thoroughly explore and evaluate the vulnerabilities of modern large-scale language models under various types of adversarial attacks. In particular, we systematically apply 14 textual adversarial attack methods to GLUE tasks to construct AdvGLUE, which is further validated by humans for reliable annotations. Our findings are summarized as follows. (i) Most existing adversarial attack algorithms are prone to generating invalid or ambiguous adversarial examples, with around 90% of them either changing the original semantic meanings or misleading human annotators as well. Therefore, we perform a careful filtering process to curate a high-quality benchmark. (ii) All the language models and robust training methods we tested perform poorly on AdvGLUE, with scores lagging far behind the benign accuracy. We hope our work will motivate the development of new adversarial attacks that are more stealthy and semantic-preserving, as well as new robust language models against sophisticated adversarial attacks. AdvGLUE is available at https://adversarialglue.github. io.
Engaging Politically Diverse Audiences on Social Media

We study how political polarization is reflected in the social media posts used by media outlets to promote their content online. In particular, we track the Twitter posts of several media outlets over the course of more than three years (566K tweets), and the engagement with these tweets from other users (104M retweets), modeling the relationship between the tweet text and the political diversity of the audience. We build a tool that integrates our model and helps journalists craft tweets that are engaging to a politically diverse audience, guided by the model predictions. To test the real-world impact of the tool, we partner with the PBS documentary series Frontline and run a series of advertising experiments on Twitter. We find that in seven out of the ten experiments, the tweets selected by our model were indeed engaging to a more politically diverse audience, reducing the gap in engagement between left- and right-leaning users by 20.3%, on average, and illustrating the effectiveness of our approach.
Establishment of ELISpot technique for detection of cellular immunity against PRRSV

The porcine reproductive and respiratory syndrome, has a high mortality and morbidity. The vaccination of PRRS is still an important means to control the epidemic disease. The purpose of this paper is to set up an effective method to evaluate cellular immunity against PRRSV. Because the GP5 protein of PRRSV is the largest structure protein and the M protein is the most conserved protein in PRRSV, we selected GP5 protein and M protein to be screened for finding the effective epitope in stimulating T cell response against PRRSV infection. The epitope of GP5 protein and M protein was predicted by using Net-MHC4 server polypeptide MHC I molecules with Artificial Neural Network (ANN). The ELISpot technology was established to detect IFN-γ secreting T lymphocyte, which provides an effective method for evaluation of the cellular immunity in PRRS. The results showed that the polypeptide pool, prepared by mixing multiple polypeptides from GP5 and M protein of PRRSV, was better than any single polypeptide in stimulating T lymphocyte to produce IFN-γ, and the total IFN-γ level in the supernatant of cell culture detected by ELISA was consistent with the result of ELISpot. The ELISpot technique to detect the T cell-mediated immunity of PRRS will pave the way to understand the pathogenesis of PRRS and evaluate the cellular immunity against PRRSV after PRRS vaccination.
Rational activation functions in neural networks with uniform based loss functions and its application in classification

In this paper, we demonstrate the application of generalised rational uniform (Chebyshev) approximation in neural networks. In particular, our activation functions are one degree rational functions and the loss function is based on the uniform norm. In this setting, when the coefficients of the rational activation function are fixed, the overall optimisation problem of the neural network forms a generalised rational uniform approximation problem where the weights and the bias of the network are the decision variables. To optimise the decision variables, we suggest using two prominent methods: the bisection method and the differential correction algorithm. We perform numerical experiments on classification problems with two classes and report the classification accuracy obtained by the network using the bisection method, differential correction algorithm along with the standard MATLAB toolbox which uses the least square loss function. We show that the choice of the uniform norm based loss function with rational activation function and the bisection method lead to better classification accuracy when the training dataset is either very small or if the classes are imbalanced.
Spectra of neutron wave functions in Earth’s gravitational field

Abstract The time evolution of a quantum wave packet in the linear gravity potential is known as Quantum Bouncing Ball. The qBounce collaboration recently observed such a system by dropping wave packets of ultracold neutrons by a height of roughly 30 microns. In this article, space and momentum spectra as well as Wigner functions of the neutron wave functions in the gravitational field of the Earth are analyzed. We investigate the quantum states in the “preparation region”, into which they transition after exiting a narrow double-mirror system and where we would expect to observe free fall and bounces in classical physics. For this, we start from the stationary solutions and eigenvalues of the Schrödinger equation in terms of Airy functions and their zeros. Subsequently, we examine space and momentum distributions as well as Wigner functions in phase space for pure and mixed quantum states. The possible influence of Yukawa-like forces for small distances of several micrometers from the mirror is included through first order perturbation calculations. Those allow us to study the resulting modifications of space and momentum distributions, and phase space functions.
Online Estimation for Functional Data

Abstract Functional data analysis has attracted considerable interest and is facing new challenges, one of which is the increasingly available data in a streaming manner. In this article we develop an online nonparametric method to dynamically update the estimates of mean and covariance functions for functional data. The kernel-type estimates can be decomposed into two sufficient statistics depending on the data-driven bandwidths. We propose to approximate the future optimal bandwidths by a sequence of dynamically changing candidates and combine the corresponding statistics across blocks to form the updated estimation. The proposed online method is easy to compute based on the stored sufficient statistics and the current data block. We derive the asymptotic normality and, more importantly, the relative efficiency lower bounds of the online estimates of mean and covariance functions. This provides insight into the relationship between estimation accuracy and computational cost driven by the length of candidate bandwidth sequence. Simulations and real data examples are provided to support such findings. Supplementary materials for this article are available online.
A System for General In-Hand Object Re-Orientation

In-hand object reorientation has been a challenging problem in robotics due to high dimensional actuation space and the frequent change in contact state between the fingers and the objects. We present a simple model-free framework that can learn to reorient objects with both the hand facing upwards and downwards. We demonstrate the capability of reorienting over 2000 geometrically different objects in both cases. The learned policies show strong zero-shot transfer performance on new objects. We provide evidence that these policies are amenable to real-world operation by distilling them to use observations easily available in the real world. The videos of the learned policies are available at: https://taochenshh.github. io/projects/in-hand-reorientation.
Radio and γ-Ray Activity in the Jet of the Blazar S5 0716+714

We explore the connection between the γ-ray and radio emission in the jet of the blazar 0716+714 by using 15, 37, and 230 GHz radio and 0.1–200 GeV γ-ray light curves spanning 10.5 yr (2008–2019). We find significant positive and negative correlations between radio and γ-ray fluxes in different time ranges. The time delays between radio and γ-ray emission suggest that the observed γ-ray flares originated from multiple regions upstream of the radio core, within a few parsecs from the central engine. Using time-resolved 43 GHz Very Long Baseline Array maps we identified 14 jet components moving downstream along the jet. Their apparent speeds range from 6c to 26c, and they show notable variations in their position angles upstream from the stationary component (∼0.53 mas from the core). The brightness temperature declines as a function of distance from the core according to a power law that becomes shallower at the location of the stationary component. We also find that the periods at which significant correlations between radio and γ-ray emission occur overlap with the times when the jet was oriented to the north. Our results indicate that the passage of a propagating disturbance (or shock) through the radio core and the orientation of the jet might be responsible for the observed correlation between the radio and γ-ray variability. We present a scenario that connects the positive correlation and the unusual anticorrelation by combining the production of a flare and a dip at γ-rays by a strong moving shock at different distances from the jet apex.