Miracle-dz/UniFAR-FTUs huggingface dataset:
Pseudo-Opinions in Online Surveys: Evidence to Recontextualize the Imputed Meaning Hypothesis

Pseudo-opinions refer to survey respondents giving answers to topics they are unfamiliar with. They are widespread but the reasons why respondents do not just admit they “don’t know” are not well-understood. We investigate the underlying mechanisms for pseudo-opinions in online surveys: do respondents satisfice and perform a “mental coin-flip,” or do they optimize and attempt to “impute a meaning” to the unknown question and answer accordingly? And can we reduce the prevalence of pseudo-opinions by expressing to respondents that it is okay not to have an opinion? To do so, we use fictitious issues. These are survey questions about nonex-istent topics and things. We use response latencies as an indicator for the mode of responding, on a continuum from automatic-spontaneous to controlled-deliberate, to investigate whether pseudo-opinions are the result of satisficing or optimizing. We also conduct a survey experiment in which the presence of an explicit “don’t know” category is randomly assigned. The sample ( n = 1288) consists of data collected in August 2019 from an online panel provider. The target population was defined as adults between 18-69 years old with internet access residing in Germany. Quotas were put in place for age and sex. We find pseudo-opinions are predicted by faster, automatic responses. This contradicts the widely-assumed imputed meaning model of pseudo-opinions. The presence of an explicit “don’t know” category reduces pseudo-opinions dramatically but does not moderate the e ff ect of deliberate or automatic responding on pseudo-opinions.
Robust Deep Learning via Layerwise Tilted Exponentials

State-of-the-art techniques for enhancing robustness of deep networks mostly rely on end-to-end training with suitable data augmentation. In this paper, we propose a complementary approach aimed at enhancing the “signal-to-noise ratio” at intermediate network layers, loosely motivated by the classical communication-theoretic model of signaling in Gaussian noise. We seek to learn neuronal weights which are “matched” to the layer inputs by supplementing end-to-end costs with a tilted exponential (TEXP) objective function which depends on the activations at the layer outputs. We show that TEXP learning can be interpreted as maximum likelihood estimation of “matched filters” under a Gaussian model for “data noise. ” TEXP inference is accomplished by re-placing batch norm by a tilted softmax enforcing competition across neurons, which can be interpreted as computation of posterior probabilities for the signaling hypotheses represented by each neuron. We show, by experimentation on standard image datasets, that TEXP learning and inference enhances robustness against noise, other common corruptions and mild adversarial perturbations, without requiring data augmentation. Further gains in robustness against this array of distortions can be obtained by appropriately combining TEXP with adversarial training.
On Assessing Trustworthy AI in Healthcare. Machine Learning as a Supportive Tool to Recognize Cardiac Arrest in Emergency Calls

Artificial Intelligence (AI) has the potential to greatly improve the delivery of healthcare and other services that advance population health and wellbeing. However, the use of AI in healthcare also brings potential risks that may cause unintended harm. To guide future developments in AI, the High-Level Expert Group on AI set up by the European Commission (EC), recently published ethics guidelines for what it terms “trustworthy” AI. These guidelines are aimed at a variety of stakeholders, especially guiding practitioners toward more ethical and more robust applications of AI. In line with efforts of the EC, AI ethics scholarship focuses increasingly on converting abstract principles into actionable recommendations. However, the interpretation, relevance, and implementation of trustworthy AI depend on the domain and the context in which the AI system is used. The main contribution of this paper is to demonstrate how to use the general AI HLEG trustworthy AI guidelines in practice in the healthcare domain. To this end, we present a best practice of assessing the use of machine learning as a supportive tool to recognize cardiac arrest in emergency calls. The AI system under assessment is currently in use in the city of Copenhagen in Denmark. The assessment is accomplished by an independent team composed of philosophers, policy makers, social scientists, technical, legal, and medical experts. By leveraging an interdisciplinary team, we aim to expose the complex trade-offs and the necessity for such thorough human review when tackling socio-technical applications of AI in healthcare. For the assessment, we use a process to assess trustworthy AI, called 1 Z-Inspection® to identify specific challenges and potential ethical trade-offs when we consider AI in practice.
Analysis of Melting Heat Transport in a Cross Flow Direction: A Comparative Study

An incompressible three-dimensional laminar flow in a cross flow direction is described in this work. The term of melting and viscous dissipation is incorporated in the mathematical modeling of present flow problem. The flow expressions are converted into dimensionless equations, which are solved with help of Runge-Kutta scheme. Impact of the emerging parameters on the non-dimensional velocities and temperature and friction-factors and local Nusselt number are examined. The convergence analysis is found for ϵ < 0 and 0 < ϵ ≤ 2 . Comparative analysis is made between the obtained results and published data for limiting case. It is explored at the surface that the melting parameter retards the liquid temperature while it enhances the fluid velocity.
A Hierarchical Scheme for Adapting Learned Quadruped Locomotion

The quadruped locomotion task is generally conditioned on a velocity command that is user-defined. However, certain features of the locomotion are not represented in this high-level definition of the task, e.g., swing feet height, step length and expended energy. Using reinforcement learning, many of these features can be determined by the reward function terms and scales that are often fixed. In this work, we propose a deep reinforcement learning (DRL) approach to learn control policies augmented with parameters that modify different aspects of the reward function and control setup which, in turn, result in variations of the locomotion. We can then define a hierarchical architecture where a high level policy infers the suitable parameters to complete a given task. We show that this setup makes it possible to learn more complex behaviours that can be adapted for different terrains and environments to ensure successful and efficient locomotion. We display our results by deploying the low-level parameterized policy on the MIT Mini-Cheetah quadruped.
Quantized Proximal Averaging Networks for Compressed Image Recovery

We solve the analysis sparse coding problem considering a combination of convex and non-convex sparsity promoting penalties. The multi-penalty formulation results in an iterative algorithm involving proximal-averaging. We then unfold the iterative algorithm into a trainable network that facilitates learning the sparsity prior. We also consider quantization of the network weights. Quantization makes neural networks efficient both in terms of memory and computation during inference, and also renders them compatible for low-precision hardware deployment. Our learning algorithm is based on a variant of the ADAM optimizer in which the quantizer is part of the forward pass and the gradients of the loss function are evaluated corresponding to the quantized weights while doing a book-keeping of the high-precision weights. We demonstrate applications to compressed image recovery and magnetic resonance image reconstruction. The proposed approach offers superior reconstruction accuracy and quality than state-of-the-art unfolding techniques and the performance degradation is minimal even when the weights are subjected to extreme quantization.
MobiCom 2010 Poster: Mobile TCP Usage Characteristics and the Feasibility of Network Migration without Infrastructure Support

In this poster we describe initial findings regarding Internet usage characteristics, in particular TCP flows from a field study with 27 iPhone 3GS users. We present details regarding their usage characteristics, and provide a solution for migrating flows between different networks and/or network interfaces without requiring infrastructure support or changes to current applications and protocols, with minimal impact to the user.
The Case of the Missing Productivity Growth: Or, Does Information Technology Explain Why Productivity Accelerated in the Us But Not the UK?

We argue that unmeasured investments in intangible organizational capital associated with the role of information and communications technology (ICT) as a general purpose technology' can explain the divergent U.S. and U.K. TFP performance after 1995. GPT stories suggest that measured TFP should rise in ICT-using sectors, perhaps with long lags. Contemporaneously, investments in ICT may in fact be associated with lower TFP as resources are diverted to reorganization and learning. In both the U.S. and U.K., we find a strong correlation between ICT use and industry TFP growth. The U.S. results, in particular, are consistent with GPT stories: the TFP acceleration was located primarily in ICT-using industries and is positively correlated with industry ICT capital growth from the 1980s and early 1990s. Indeed, as GPT stories suggest, controlling for past ICT growth, industry TFP growth appears negatively correlated with increases in ICT capital services in the late 1990s. A somewhat different picture emerges for the U.K. TFP growth does not appear correlated with lagged ICT capital growth. But TFP growth in the late 1990s is strongly and positively associated with the growth of ICT capital services, while being strongly and negatively associated with the growth of ICT investment.
Capital Structure and Corporate Performance of Nigerian Quoted Firms: A Panel Data Approach

This paper presents empirical findings on the impact of leverage (debt's ratio) on firms' performance. Empirical results based on 2003 to 2007 accounting and marketing data for 101 quoted firms in Nigeria lend some support to the pecking order and static tradeoff theories of capital structure. The study employed panel data analysis by using fixed-effect estimation, random-effect estimation and a pooled regression model. The usual identification tests and Hausman's Chi-square statistics for testing whether the fixed effects model estimator is an appropriate alternative to the random effects model were also computed for each model. A firm's leverage was found to have a significant negative impact on the firm's accounting performance measure (ROA). An interesting finding is that all the leverage measures have a positive and highly significant relationship with the market performance measure (Tobin's Q). The study further reveals a salient fact that Nigerian firms are either majorly financed by equity capital or a mix of equity capital and short-term financing. It is therefore suggested that Nigerian firms should try to match their high market performance with real activities that can help make the market performance reflect on their internal growth and accounting performance.
Structure et modélisation hydrodynamique des eaux souterraines : application à l'aquifère crayeux de la bordure nord du Bassin de Paris

Les structures geologiques influencent les circulations des eaux souterraines dans un milieu crayeux fissure. A partir d'observations de terrain et de mesures hydrologiques nous abordons une methodologie nouvelle pour mieux quantifier et relier les parametres geometriques aquifere et les reponses hydrodynamiques du massif crayeux. Nous avons elabore dans ce but un modele conceptuel structure-ecoulement souterrain qui a permis de bien mettre en valeur l'effet direct de la geometrie de l'aquifere sur les ecoulements. Nous avons analyse qualitativement et quantitativement les reponses piezometriques suite a la traversee des milieux non-satures et satures fissures sous l'incidence des pluies. Puis a ete abordee la liaison entre les parametres physico-chimiques des eaux et les variations de debit de plusieurs sources temoins de l'Artois. Afin de bien cerner l'hydrodynamisme des eaux souterraines a ete appliquee une methode originale par la combinaison du modele Hydrometeorologique a Reservoirs MMO8 et du modele des Reseaux de Neuronnes Artificiels (RNA). Ont ete mis en evidence : les parametres pertinents influencant les emergences de l'aquifere crayeux, une simulation ainsi qu'une prevision des debits et une variation des amplitudes de la piezometrie basees respectivement sur une validation de 72 heures et de 30 jours. Ces modeles permettent d'approcher les phenomenes hydrodynamiques naturels dans leur complexite et de maniere efficace proposer une prevision utile a la gestion des ressources naturelles en eau.
Journal of Economics and Business

Introduction: This study examines the effect of investment decisions and funding decisions on firm value with institutional ownership as a moderating variable. In this study, investment decisions are measured by Current Asset to Total Assets (CATA) and Fixed Assets to Total Assets (FATA) while funding decisions are measured by Debt Equity Ratio (DER), institutional ownership is measured by (INST) and company value is measured by EV / EBITDA. Purpose: Analyzing the influence of investment decisions and funding decisions on the company's value in the manufacturing sector listed on the Indonesia Stock Exchange in 2014-2017. Results: The results showed that there was a positive and significant effect between CATA and DER on EV / EBITDA, while FATA had no effect on EV / EBITDA. Conclusions: The study was conducted on companies listed on the Indonesia Stock Exchange in the period 2014 to 2017. This study used as many as 87 manufacturing companies that met the criteria of sampling. This study was analyzed using multiple regression analysis and interaction tests and study also found that INST can strengthen the relationship between CATA and EV / EBITDA, weaken the relationship of DER and EV / EBITDA, and INST does not moderate the relationship between FATA and EV / EBITDA. The results of this study can be used by investors as a material consideration in terms of investment decisions and funding decisions, especially in manufacturing companies in Indonesia. Investors can choose a company that has good financial decisions and an appropriate portion of institutional ownership.
Search for anomalous production of events with three or more leptons in pp collisions at ffiffi s p 1⁄4 8 TeV

The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Search for anomalous production of events with three or more leptons in pp collisions at ffiffi s p ¼ 8 TeV A search for physics beyond the standard model in events with at least three leptons is presented. The data sample, corresponding to an integrated luminosity of 19.5 fb −1 of proton-proton collisions with center-of-mass energy ffiffi ffi s p ¼ 8 TeV, was collected by the CMS experiment at the LHC during 2012. The data are divided into exclusive categories based on the number of leptons and their flavor, the presence or absence of an opposite-sign, same-flavor lepton pair (OSSF), the invariant mass of the OSSF pair, the presence or absence of a tagged bottom-quark jet, the number of identified hadronically decaying τ leptons, and the magnitude of the missing transverse energy and of the scalar sum of jet transverse momenta. The numbers of observed events are found to be consistent with the expected numbers from standard model processes, and limits are placed on new-physics scenarios that yield multilepton final states. In particular, scenarios that predict Higgs boson production in the context of supersymmetric decay chains are examined. We also place a 95% confidence level upper limit of 1.3% on the branching fraction for the decay of a top quark to a charm quark and a Higgs boson (t → cH), which translates to a bound on the left-and right-handed top-charm flavor-violating Higgs Yukawa couplings, λ H tc and λ H ct , respectively, of
Analysis of the Southern African development community national vulnerability assessment committees (SADC NVACs) : towards the establishment of an effective and efficient South African vulnerability assessment committee (SAVAC).

i DECLARATION. ii DEDICATION.iii ACKNOWLEDGEMENTS.iv TABLE OF CONTENTS.v LIST OF TABLES . viii LIST OF FIGURES. x ACRONYMS.xi CHAPTER 1: THE PROBLEM AND ITS SETTING.1 1.
Measurements of the Total and Differential Higgs Boson Production Cross Sections Combining the H → γγ and H → ZZ* → 4ℓ Decay Channels at √s = 8 TeV with the ATLAS Detector

sp ¼ 8 TeV and recorded by the ATLAS detector. Cross sections are obtained from measured H → γγ and H → ZZ � → 4l event yields, which are combined accounting for detector efficiencies, fiducial acceptances, and branching fractions. Differential cross sections are reported as a function of Higgs boson transverse momentum, Higgs boson rapidity, number of jets in the event, and transverse momentum of the leading jet. The total production cross section is determined to be σpp→H ¼ 33.0 � 5.3 ðstat Þ� 1.6 ðsystÞ pb. The measurements are compared to state-of-the-art predictions.
Pathophysiology of Peripheral Neuropathic Pain: Immune Cells and Molecules

Damage to the peripheral nervous system often leads to chronic neuropathic pain characterized by spontaneous pain and an exaggerated response to painful and/or innocuous stimuli. This pain condition is extremely debilitating and usually difficult to treat. Although inflammatory and neuropathic pain syndromes are often considered distinct entities, emerging evidence belies this strict dichotomy. Inflammation is a well-characterized phenomenon, which involves a cascade of different immune cell types, such as mast cells, neutrophils, macrophages, and T lymphocytes. In addition, these cells release numerous compounds that contribute to pain. Recent evidence suggests that immune cells play a role in neuropathic pain in the periphery. In this review we identify the different immune cell types that contribute to neuropathic pain in the periphery and release factors that are crucial in this particular condition.
The use of hematoxylin and eosin muscle staining and ImageJ as tools to assess the incidence and severity of white striping in chicken breast

The myopathy known as white striping (WS) increases deposits of fatty tissue in breasts (Pectoralis major) of high yielding broiler chickens. This condition threatens the poultry industry as it decreases consumers’ willingness to purchase. To compare macroscopic (visual scoring) and microscopic (histological staining) methods as tools to assess WS, samples were collected from a trial evaluating the effects of growth rate (fast or slow) and L-carnitine supplementation (0 or 100 mg/kg) on performance parameters of broilers. Chicken breasts (Pectoralis major; n=144) were biopsied on the left cranial ventral region. Histological slides were prepared and stained (hematoxylin-eosin; H&E), photographed, and analyzed using ImageJ software. Increased incidence and severity of WS was visually observed in fast growing birds (P<0.0001) and those supplemented with 100 mg/kg of L-carnitine (P=0.0348). Fast growth rates increased average cell area (P=0.0315) and percentage of adipose tissue (P=0.0007), while cell count was higher in slow growing birds (P=0.0171). A significant correlation (r=0.2375; P=0.0043) was found between visual assessment of adipose tissue and percentage determined microscopically. Although it was possible to determine presence and severity of WS by using H&E staining, this technique is labor intensive and costly relative to subjective visual assessment, which is comparatively more resource efficient.
Attitudes of students who study in different departments against body donation

Objective: As technology continues to advance, alternative methods of cadaver education have emerged in anatomy lessons. However, cadaver dissection remains a fundamental component of medical education curricula worldwide. Material and Methods: This research was conducted among students enrolled in health sciences and other disciplines at İzmir Bakırçay University. A total of five hundred and eighty-four students took part in the study. The survey aimed to gather information on students' sociodemographic attributes and their perspectives regarding the potential donation of their and their family members' bodies for use as cadavers after their passing. Resuts: The analysis of the study's data revealed that students in both groups expressed a reluctance to donate their own bodies or those of their family members. Nonetheless, a majority of students emphasized the significance of cadaveric education, indicating that the willingness to donate cadavers could potentially rise with increased exposure to informative advertisements and comprehensive awareness campaigns. Conclusion: Despite the prevalent Islamic faith in Turkish society, survey findings indicate that religious beliefs do not significantly impede body donation. The study reveals that the primary deterrent to body donation in Turkey is the perceived lack of professionalism within the institutions accepting such donations. To enhance body donation rates in the country, a promising strategy involves launching comprehensive body donation campaigns through mass media, effectively showcasing the competence and professionalism of the parties involved in these initiatives.
Treatment of osteoporosis with annual iv zoledronic acid: effects on hip fracture

Background: Several treatments for postmenopausal osteoporosis have been available in the past decade, but adherence to these treatments has been judged inadequate. The prevention of hip fracture by these medications is still modest. Methods: A literature search was performed for treatment with zoledronic acid for the prevention of hip fracture. Results: In the The Health Outcomes and Reduced Incidence with Zoledronic Acid Once Yearly (HORIZON) Pivotal Fracture Trial, involving 7765 postmenopausal women with low bone mineral density or with prevalent vertebral fracture, women taking zoledronic acid had a 41% relative risk reduction for hip fracture, at 3 years, compared to placebo. In the HORIZON Recurrent Fracture Trial, 2127 patients (76% were women) were randomized to receive either zoledronic acid or placebo after sustaining a ﬁ rst hip fracture. A reduction of 30% in the second hip fracture risk was observed, but it did not reach statistical signiﬁ cance. Zoledronic acid was generally safe in these trials, although a slightly increased rate of severe atrial ﬁ brillations was observed in the HORIZON Prevention Fracture Trial, but not in the HORIZON Recurrent Fracture Trial. Conclusion: Yearly zoledronic acid reduces the risk of hip fracture, both in postmenopausal osteoporotic women with and without prevalent vertebral fracture and in men and women with a recent ﬁ rst hip fracture.