Miracle-dz/UniFAR-FTUs huggingface dataset:
Calibration-free robots for cost-effective, dependable and robust automation

Robots that never need any calibration of their kinematics, their actuators or their sensors promise great advantages in terms of maintenance cost, robustness and dependability. Here we propose an approach for realizing such robots for calibration-free vision-based object manipulation. The underlying concepts are based on the utilization of laws of projective geometry that always apply, regardless of camera characteristics, and in some cases on learning by doing. No quantitative models of the robotpsilas kinematics, control characteristics or sensors are used. Consequently, even gross changes in those characteristics as they may be caused, e.g., by the aging of parts or by maintenance work, are tolerated, often without any degradation of the performance of the robot. The proposed approach is based on a vision system with an uncalibrated camera pair observing the robotpsilas work space as the main sensor and a strategy that lets the robot learn automatically the relationships between motor control commands and resulting sensor data. Real robots controlled on the basis of the approach have proved their effectiveness, adaptability and robustness in extensive real-world tests.
In vivo efficacy of sivelestat in combination with pazufloxacin against Legionella pneumonia

ABSTRACT It is important to regulate excessive inflammation when patients with severe infectious disease are treated. Sivelestat sodium hydrate (sivelestat), a neutrophil elastase inhibitor, is used in the treatment of lung injury but its effect on bacterial pneumonia is unknown. The authors examined the efficacy of sivelestat in combination with a fluoroquinolone in a Legionella pneumophila pneumonia mouse model. The combination therapy did not show a significant survival improvement compared to the treatment with fluoroquinolone alone, but reduced bacteria number and inflammatory cells in the early phase. The combination therapy can contribute to treatment of L. pneumophila pneumonia with protecting lungs.
Iron from haemoglobin and haemin modulates nucleotide hydrolysis in Trichomonas vaginalis

Extracellular ATP may act as a danger signalling molecule, inducing inflammation and immune responses in infection sites. The ectonucleotidases NTPDase and ecto-5’-nucleotidase are enzymes that modulate extracellular nucleotide levels; these enzymes have been previously characterised in Trichomonas vaginalis. Iron plays an important role in the complex trichomonal pathogenesis. Herein, the effects of iron on growth, nucleotide hydrolysis and NTPDase gene expression in T. vaginalis isolates from female and male patients were evaluated. Iron from different sources sustained T. vaginalis growth. Importantly, iron from haemoglobin (HB) and haemin (HM) enhanced NTPDase activity in isolates from female patients and conversely reduced the enzyme activity in isolates from male patients. Iron treatments could not alter the NTPDase transcript levels in T. vaginalis. Furthermore, our results reveal a distinct ATP, ADP and AMP hydrolysis profile between isolates from female and male patients influenced by iron from HB and HM. Our data indicate the participation of NTPDase and ecto-5’-nucleotidase in the establishment of trichomonas infection through ATP degradation and adenosine production influenced by iron.
Founding Family Ownership and the Agency Cost of Debt

We investigate the impact of founding family ownership structure on the agency cost of debt. We find that founding family ownership is common in large, publicly traded firms and is related, both statistically and economically, to a lower cost of debt financing. Our results are consistent with the idea that founding family firms have incentive structures that result in fewer agency conflicts between equity and debt claimants. This suggests that bond holders view founding family ownership as an organizational structure that better protects their interests.
The influence of political candidates’ facial appearance on older and younger adults’ voting choices and actual electoral success

Abstract Younger adults (YA) judgments of political candidates’ competence from facial appearance accurately predict electoral success. Whether this is true for older adults (OA) has not been investigated despite the fact that OA are more likely to vote than YA and may respond differently to particular facial qualities. We examined whether OA and YA ratings of competence, trustworthiness, attractiveness, and babyfaceness of opposing candidates in US Senate elections independently predicted their own vote choices and actual election outcomes. OA and YA ratings of attractiveness, competence, and trustworthiness positively predicted their choices, but the effect of competence was weaker for OA. Babyfaceness negatively predicted OA, but not YA, choices. OA and YA competence ratings equally predicted the actual election winners, while OA, but not YA, attractiveness ratings did so. Trustworthy and babyface ratings did not predict actual winners. These findings have implications for understanding age differences in candidate preferences and the prediction of election outcomes.
Entrepreneurship Capital: Determinants and Impact on Regional Economic Performance

We investigate what determines regions’ entrepreneurial behavior and the impact of it on regional economic performance. We argue that economic knowledge differs not only from traditional factors of production due to its public goods characteristic but it is also uncertain. In that perspective, the role of entrepreneurship is to take on the corresponding risk by starting up a new firm. This implies knowledge spillovers, hence a positive impact on economic performance. We test this hypothesis using a production function approach using data on German regions. We estimate a two-equation system that regresses on both variables, entrepreneurship and economic performance, simultaneously. We find significant impact of entrepreneurship capital on economic output. On the other hand, spatially specific entrepreneurship capital is shaped by regional-specific factors. The extent of these findings differs for knowledge based and non-knowledge based measures of entrepreneurship capital. JEL-Codes: M13, O32, O47
Empirical study on factors influencing user's willingness for participating in virtual communities

With the advancing of Internet and technology, virtual communities (VCs) have developed rapidly in China. User's willingness to participate becomes the key point for maintenance and development of VCs. Base on the viewpoint that VCs have the dual nature of technology and society, this paper uses structural equation model to carry out empirical study on factors influencing user's willingness for participating in VCs. The results show that perceived usability and perceived sociability have significant positive impact on user's willingness for participation; systemic stability and matching degree of knowledge have significant positive impact on perceived technicality; social interactivity and management suitability have significant positive impact on perceived sociability.
Practical Use of the Raw Electroencephalogram Waveform During General Anesthesia: The Art and Science

Quantitative electroencephalogram (qEEG) monitors are often used to estimate depth of anesthesia and intraoperative recall during general anesthesia. As with any monitor, the processed numerical output is often misleading and has to be interpreted within a clinical context. For the safe clinical use of these monitors, a clear mental picture of the expected raw electroencephalogram (EEG) patterns, as well as a knowledge of the common EEG artifacts, is absolutely necessary. This has provided the motivation to write this tutorial. We describe, and give examples of, the typical EEG features of adequate general anesthesia, effects of noxious stimulation, and adjunctive drugs. Artifacts are commonly encountered and may be classified as arising from outside the head, from the head but outside the brain (commonly frontal electromyogram), or from within the brain (atypical or pathologic). We include real examples of clinical problem-solving processes. In particular, it is important to realize that an artifactually high qEEG index is relatively common and may result in dangerous anesthetic drug overdose. The anesthesiologist must be certain that the qEEG number is consistent with the apparent state of the patient, the doses of various anesthetic drugs, and the degree of surgical stimulation, and that the qEEG number is consistent with the appearance of the raw EEG signal. Any discrepancy must be a stimulus for the immediate critical examination of the patient’s state using all the available information rather than reactive therapy to “treat” a number.
A Theoretical Model of Psychometric Effects of Faking on Assessment Procedures: Empirical Findings and Implications for Personality at Work

This article proposes a theoretical model for explaining the psychometric effects of faking on assessment procedures (e.g., biodata, interviews, assessment center, personality inventories, and self‐reported measures). The model hypothesizes that faking is a phenomenon of homogenization of scores, consisting of a double mechanism that increases the mean, on one hand, and decreases the standard deviation of distributions of scores, on the other. Subsequently, this affects the covariance, reliability, and validity of assessment procedures negatively. The model predicts that a mean ratio (faking ratio) greater than 1 and a coefficient of homogeneity u smaller than 1 characterizes faking. Meta‐analysis was used to test several predictions of the theoretical model in the case of the personality measures. A database of 46 independent studies was created. All the studies used the NEO‐PI‐R for assessing the Big Five and their facets. The general pattern of data fully supported the model predictions. Implications for personnel assessment and, particularly, for personality assessment are discussed.
Improving the Effective Potential Multi-Mass-Scale Case

Previously proposed procedure for improving the effective potential by using renormalization group equation (RGE) is generalized so as to be applicable to any system containing several different mass scales. If one knows L-loop effective potential and (L + 1)-loop RGE coefficient functions, this procedure gives an improved potential which satisfies the RGE and contains all of the leading, next-to-leading,. , and L-th-to-leading log terms. Our procedure here also clarifies how naturally the so-called effective field theory can be incorporated in the RGE in MS scheme
THE DETERMINANTS OF UNEMPLOYMENT ACROSS OECD COUNTRIES : REASSESSING THE ROLE OF POLICIES AND INSTITUTIONS

Introduction . 8 Direct effects of policies and institutions on unemployment: the baseline specification 9 Model specification and data . 9 Main results. 12 Sensitivity analysis. 15 Policy interactions. 17 Additional determinants of unemployment patterns . 25 Housing policy and home ownership . 25 Minimum wages. 27 Active labour market policies. 27 Interactions between institutions and shocks. 33 Unobserved shocks. 35 Observed shocks . 39 Disentangling amplification from persistence effects . 41 Conclusions. 45
Random walk in random environment in a two-dimensional stratified medium with orientations

We consider a model of random walk in ${\mathbb Z}^2$ with (fixed or random) orientation of the horizontal lines (layers) and with non constant iid probability to stay on these lines. We prove the transience of the walk for any fixed orientations under general hypotheses. This contrasts with the model of Campanino and Petritis, in which probabilities to stay on these lines are all equal. We also establish a result of convergence in distribution for this walk with suitable normalizations under more precise assumptions. In particular, our model proves to be, in many cases, even more superdiffusive than the random walks introduced by Campanino and Petritis.
Federal Reserve Bank of Minneapolis Research Department Staa Report 215 a Model of Commodity Money, with Applications to Gresham's Law and the Debasement Puzzle Federal Reserve Bank of Chicago I. the Basic Model Ii. Equilibrium and Gresham's Law

We develop a model of commodity money and use it to analyze the following two questions motivated by issues in monetary history: What are the conditions under which Gresham's Law holds? And, what are the mechanics of a debasement (lowering the metallic content of coins)? The model contains light and heavy coins, imperfect information, and prices determined via bilateral bargaining. There are equilibria with neither, both, or only one type of coin in circulation. When both circulate, coins may trade by weight or by tale. We discuss the extent to which Gresham's Law holds in the various cases. Following a debasement, the quantity of reminting depends on the incentives ooered by the sovereign. Equilibria exist with positive seigniorage and a mixture of old and new coins in circulation. The views expressed here are those of the authors and not necessarily those of the Federal Reserve Banks of Minneapolis or Chicago or the Federal Reserve System. This paper develops a model where metal coins are used as media of exchange, and uses the model to analyze two closely related questions in monetary economics: What are the conditions under which Gresham's Law holds? And, what are the mechanics of a debasement, an operation in which the metallic content of coins is lowered? Gresham's Law, as it is commonly stated, asserts that bad money drives out good money. This is usually taken to mean that when two similar commodity monies compete, and one is in some sense inferior to the other, the inferior money will circulate and the superior money will not, but will instead be hoarded or shipped abroad. It is invoked in a variety of contexts, such as, for example, competition between light and heavy coins of a given type, or between coins of diierent metals like gold and silver. Despite it being one of the most generally accepted and frequently cited propositions in economics, we think that existing theoretical analyses of Gresham's Law are lacking, for reasons discussed below. 1 Debasements have been observed for centuries and were actually quite common in medieval and modern European economies. The monetary system of that time consisted of metal coins (gold and silver) produced by mints under the direct control of sovereigns. Individuals could bring metal to the mint to be made into new coins of the same metal. This was costly, because the total metal content of the new coins returned was …
Errors in communication

I wish to bring to your notice a few errors in the meeting report by Anil Kumar 1. In the first and second columns of p. 1399 are described the oral presentations that were made by Caitlin O’Connell-Rodwellon seismic communication in elephants and of Andrea (not Andrew) M. Sim-mons on acoustic methods for studying frog choruses, two women scientists who have mysteriously undergone a gendertrans formation in Anil Kumar’s report! Not only in the interest of accuracy in scientific reporting but also as a woman scientist, I take strong exception to these errors.
Human action recognition via sum-rule fusion of fuzzy K-Nearest Neighbor classifiers

Shape and motion are two most distinct cues observed from human actions. Traditionally, K-Nearest Neighbor (K-NN) classifier is used to compute crisp votes from multiple cues separately. The votes are then combined using linear weighting scheme. Usually, the weights are determined in a brute-force or trial-and-error manner. In this study, we propose a new classification framework based on sum-rule fusion of fuzzy K-NN classifiers. Fuzzy K-NN classifier is capable of producing soft votes, also known as fuzzy membership values. Based on Bayes theorem, we show that the fuzzy membership values produced by the classifiers can be combined using sum-rule. In our experiment, the proposed framework consistently outperforms the conventional counterpart (K-NN with majority voting) for both Weizmann and KTH datasets. The improvement may attribute to the ability of the proposed framework to handle data ambiguity due to similar poses present in different action classes. We also show that the performance of our method compares favorably with the state-of-the-arts.
Multi-ASIP based parallel and scalable implementation of motion estimation kernel for high definition videos

Parallel implementations of motion estimation for high definition videos typically exploit various forms of parallelism (GOP, frame-, slice- and macroblock-level) to deliver real-time throughput. Although parallel implementations deliver real-time throughput, they often suffer from limited flexibility and scalability due to the form of parallelism and architecture used. In this work, we use Group Of MacroBlocks (GOMB) and Intra-MB (IMB) parallelism with a multi-ASIP (Application Specific Instruction set Processor) architecture to provide a flexible and scalable platform for motion estimation of high definition videos. Multiple GOMBs are processed by the ASIPs in parallel (GOMB-level) where each ASIP is equipped with custom instructions to process the pixels of an MB in parallel (IMB-level). The system is flexible and scalable as the number of ASIPs (number of GOMBs) and custom instructions are not fixed, and are determined through design space exploration. We evaluated the multi-ASIP architecture in Tensilica's commercial design environment with varying number of ASIPs (up to nine), and compared hand-coded and automatically generated custom instructions. The results illustrate that systems with three and seven ASIPs delivered real-time throughput of 30 and 60 fps respectively for “pedestrian”, “rush hour” and “tractor” HD1080p video sequences. In addition, the results indicate that the multi-ASIP platform can be extended for even higher resolutions such as Ultra High Definition (UHD) due to its flexibility and scalability.
Cell Type-Specific Synaptic Dynamics of Synchronized Bursting in the Juvenile CA3 Rat Hippocampus

Spontaneous synchronous bursting of the CA3 hippocampus in vitro is a widely studied model of physiological and pathological network synchronization. The role of inhibitory conductances during network bursting is not understood in detail, despite the fact that several antiepileptic drugs target GABAA receptors. Here, we show that the first manifestation of a burst event is a cell type-specific flurry of GABAA receptor-mediated inhibitory input to pyramidal cells, but not to stratum oriens horizontal interneurons. Moreover, GABAA receptor-mediated synaptic input is proportionally smaller in these interneurons compared with pyramidal cells. Computational models and dynamic-clamp studies using experimentally derived conductance waveforms indicate that both these factors modulate spike timing during synchronized activity. In particular, the different kinetics and the larger strength of GABAergic input to pyramidal cells defer action potential initiation and contribute to the observed delay of firing, so that the interneuronal activity leads the burst cycle. In contrast, excitatory inputs to both neuronal populations during a burst are kinetically similar, as required to maintain synchronicity. We also show that the natural pattern of activation of inhibitory and excitatory conductances during a synchronized burst cycle is different within the same neuronal population. In particular, GABAA receptor-mediated currents activate earlier and outlast the excitatory components driving the bursts. Thus, cell type-specific balance and timing of GABAA receptor-mediated input are critical to set the appropriate spike timing in pyramidal cells and interneurons and coordinate additional neurotransmitter release modulating burst strength and network frequency.
A Keck HIRES Investigation of the Metal Abundances and Kinematics of the Z = 2.46 Damped LY alpha System toward Q0201+365

We present high resolution ($\approx 8$ \kms) spectra of the QSO Q0201+365 obtained with HIRES, the echelle spectrograph on the 10m W.M. Keck Telescope. Although we identify over $80\%$ of the absorption features and analyze several of the more complex metal-line systems, we focus our analysis on the damped \Lya system at $z=2.462$. Ionization simulations suggest the hydrogen in this system is significantly neutral and all of the observed metals are predominantly singly ionized. We measure accurate abundances for Fe, Cr, Si, Ni and place a lower limit on the abundance of Zn: [Fe/H] = $-0.830 \pm 0.051$, [Cr/H] = $-0.902 \pm 0.064$, [Si/H] = $-0.376 \pm 0.052$, [Ni/H] = $-1.002 \pm 0.054$ and [Zn/H] $> -0.562 \pm 0.064$. We give evidence suggesting the actual Zn abundance is [Zn/H] $\approx -0.262$, implying the highest metallicity observed at a redshift $z \geq 2$. The relative abundances of these elements remains constant over essentially the entire system ($\approx 150$ \kms in velocity space), suggesting it is well mixed. Furthermore, we use the lack of abundance variations to infer properties of the dust responsible for element depletion. Finally, we discuss the kinematic characteristics of this damped \Lya system, comparing and contrasting it with other systems. The low-ion line profiles span $\approx 200$ \kms in velocity space and have an asymmetric shape with the strongest feature on the red edge. These kinematic characteristics are consistent with a rotating disk model.
Integrating Microarray and Proteomics Data to Predict the Response of Cetuximab in Patients with Rectal Cancer

To investigate the combination of cetuximab, capecitabine and radiotherapy in the preoperative treatment of patients with rectal cancer, fourty tumour samples were gathered before treatment (T0), after one dose of cetuximab but before radiotherapy with capecitabine (T1) and at moment of surgery (T2). The tumour and plasma samples were subjected at all timepoints to Affymetrix microarray and Luminex proteomics analysis, respectively. At surgery, the Rectal Cancer Regression Grade (RCRG) was registered. We used a kernel-based method with Least Squares Support Vector Machines to predict RCRG based on the integration of microarray and proteomics data on To and T1. We demonstrated that combining multiple data sources improves the predictive power. The best model was based on 5 genes and 10 proteins at T0 and T1 and could predict the RCRG with an accuracy of 91.7%, sensitivity of 96.2% and specificity of 80%.
“The devil destroyed us”: Satanism and gender violence in South Africa

Abstract In October 2011, a young South African woman named Kirsty Theologo was set on fire and left for dead by a group of her high school contemporaries in Linmeyer, Johannesburg. The killing was defined as a “Satanist murder,” leading to media, judicial, and religious interventions aimed at countering the apparent Satanic threat. This article examines press material surrounding Kirsty Theologo’s death and the subsequent arrest and trial of her killers. It argues that the ongoing moral panic around Satanism in contemporary South Africa has obscured the often gendered nature of so-called satanic violence, showing the way in which the murder was instead placed within a familiar framework of Satanic panic in an act of collective displacement that elided the structural and historical contexts of acts of extreme violence perpetrated by young South African men on the bodies of young South African women.