Miracle-dz/UniFAR-FTUs huggingface dataset:
Data-driven clustering of rain events: microphysics information derived from macro-scale observations

Abstract. Rain time series records are generally studied using rainfall rate or accumulation parameters, which are estimated for a fixed duration (typically 1 min, 1 h or 1 day). In this study we use the concept of rain events . The aim of the first part of this paper is to establish a parsimonious characterization of rain events, using a minimal set of variables selected among those normally used for the characterization of these events. A methodology is proposed, based on the combined use of a genetic algorithm (GA) and self-organizing maps (SOMs). It can be advantageous to use an SOM, since it allows a high-dimensional data space to be mapped onto a two-dimensional space while preserving, in an unsupervised manner, most of the information contained in the initial space topology. The 2-D maps obtained in this way allow the relationships between variables to be determined and redundant variables to be removed, thus leading to a minimal subset of variables. We verify that such 2-D maps make it possible to determine the characteristics of all events, on the basis of only five features (the event duration, the peak rain rate, the rain event depth, the standard deviation of the rain rate event and the absolute rain rate variation of the order of 0.5). From this minimal subset of variables, hierarchical cluster analyses were carried out. We show that clustering into two classes allows the conventional convective and stratiform classes to be determined, whereas classification into five classes allows this convective–stratiform classification to be further refined. Finally, our study made it possible to reveal the presence of some specific relationships between these five classes and the microphysics of their associated rain events.
Energy and Delay Optimization of Heterogeneous Multicore Wireless Multimedia Sensor Nodes by Adaptive Genetic-Simulated Annealing Algorithm

Energy efficiency and delay optimization are significant for the proliferation of wireless multimedia sensor network (WMSN). In this article, an energy-efficient, delay-efficient, hardware and software cooptimization platform is researched to minimize the energy cost while guaranteeing the deadline of the real-time WMSN tasks. First, a multicore reconfigurable WMSN hardware platform is designed and implemented. This platform uses both the heterogeneous multicore architecture and the dynamic voltage and frequency scaling (DVFS) technique. By this means, the nodes can adjust the hardware characteristics dynamically in terms of the software run-time contexts. Consequently, the software can be executed more efficiently with less energy cost and shorter execution time. Then, based on this hardware platform, an energy and delay multiobjective optimization algorithm and a DVFS adaption algorithm are investigated. These algorithms aim to search out the global energy optimization solution within the acceptable calculation time and strip the time redundancy in the task executing process. Thus, the energy efficiency of the WMSN node can be improved significantly even under strict constraint of the execution time. Simulation and real-world experiments proved that the proposed approaches can decrease the energy cost by more than 29% compared to the traditional single-core WMSN node. Moreover, the node can react quickly to the time-sensitive events.
The accuracy of pulse rate estimation from the sequence of face images

The goal of this paper is to analyze the accuracy of pulse rate estimation from the sequence of face images. Simulated and real signals were used to evaluate two pulse rate estimators; one for frequency domain and the second one for time domain using the autocorrelation function. The results show that the mean difference between the reference measurements and estimated pulse rate values are about 2bpm. In the analysis of short signals the estimator working in time domain has better accuracy since it is not limited by spectral leakage observed in the analysis of spectrum for short length signals.
Characterization of Human Influenza Virus Variants Selected In Vitro in the Presence of the Neuraminidase Inhibitor GS 4071

ABSTRACT An oral prodrug of GS 4071, a potent and selective inhibitor of influenza neuraminidases, is currently under clinical development for the treatment and prophylaxis of influenza virus infections in humans. To investigate the potential development of resistance during the clinical use of this compound, variants of the human influenza A/Victoria/3/75 (H3N2) virus with reduced susceptibility to the neuraminidase inhibitor GS 4071 were selected in vitro by passaging the virus in MDCK cells in the presence of inhibitor. After eight passages, variants containing two amino acid substitutions in the hemagglutinin (A28T in HA1 and R124M in HA2) but no changes in the neuraminidase were isolated. These variants exhibited a 10-fold reduction in susceptibility to GS 4071 and zanamivir (GG167) in an in vitro plaque reduction assay. After 12 passages, a second variant containing these hemagglutinin mutations and a Lys substitution for the conserved Arg292 of the neuraminidase was isolated. The mutant neuraminidase enzyme exhibited high-level (30,000-fold) resistance to GS 4071, but only moderate (30-fold) resistance to zanamivir and 4-amino-Neu5Ac2en, the amino analog of zanamivir. The mutant enzyme had weaker affinity for the fluorogenic substrate 2′-(4-methylumbelliferyl)-α-d- N -acetylneuraminic acid and lower enzymatic activity compared to the wild-type enzyme. The viral variant containing the mutant neuraminidase did not replicate as well as the wild-type virus in culture and was 10,000-fold less infectious than the wild-type virus in a mouse model. These results suggest that although the R292K neuraminidase mutation confers high-level resistance to GS 4071 in vitro, its effect on viral virulence is likely to render this mutation of limited clinical significance.
External Openness and Economic Growth in Developing Countries

This paper investigates empirically the relationship between two channels of external openness: international trade, foreign direct investment (FDI), and the rate of economic growth implied by the leader–follower model. The predictions of the theory are tested for the group of 97 developing countries in the period of 1974–2006 using static and dynamic panel data estimation methods. The estimation results show that both international trade and FDI positively contribute to growth.
On limits of constructive interference in backscatter systems

Backscatter communication reduces the energy consumption of resource-constrained sensors and actuators by several orders of magnitude as it avoids the resource-consuming need to generate a radio wave. Many backscatter systems and applications suffer from low communication range. By exploiting the collective power of several tags that transmit the same data simultaneously, constructive interference may help to remedy this problem and increase the communication range. When several tags backscatter the same signal simultaneously it is not necessarily true that constructive interference occurs. As our theoretical results and previous work indicate the interference might also be destructive. Our experimental results on real hardware suggest that exploiting constructive interference to increase the communication range requires careful coordination which is difficult in decentralized settings.
Open-label, uncontrolled, multicenter phase II study to evaluate the efficacy and toxicity of cetuximab as a single agent in patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck who failed to respond to platinum-based therapy.

PURPOSE To evaluate the efficacy and safety of the epidermal growth factor receptor-directed monoclonal antibody cetuximab administered as a single agent in patients with recurrent and/or metastatic squamous cell carcinoma of the head and neck (SCCHN) who experience disease progression on platinum therapy. PATIENTS AND METHODS An open-label multicenter study in which patients with disease progression on two to six cycles of platinum therapy received single-agent cetuximab (initial dose 400 mg/m2 followed by subsequent weekly doses of 250 mg/m2) for > or = 6 weeks (single-agent phase). Patients who experienced disease progression could receive salvage therapy with cetuximab plus platinum (combination-therapy phase). From June 2001 to December 2002, 103 patients were enrolled and treated with cetuximab, 53 of whom subsequently received combination therapy. RESULTS In the single-agent phase, response rate was 13%, disease control rate (complete response/partial response/stable disease) was 46%, and median time to progression (TTP) was 70 days. During the combination-therapy phase, the objective response rate was zero, disease control rate was 26%, and TTP was 50 days. Median overall survival was 178 days. Treatment was well tolerated. The most common cetuximab-related adverse events in the single-agent phase were skin reactions, particularly rash (49% of patients, mainly grade 1 or 2). There was one treatment-related death due to an infusion-related reaction. CONCLUSION Single-agent cetuximab was active and generally well tolerated in the treatment of recurrent and/or metastatic SCCHN that progressed on platinum therapy. Response was comparable to that seen with cetuximab plus platinum combination regimens in the same setting.
Social Capital in Central and Eastern Europe: A Critical Assessment and Literature Review

Ever since the 1990s, social capital has attracted attention from social science researchers. With its focus on the importance of intangible resources such as trust, social capital appeared to supplement existing theories of social and economic change. For its early proponents such as Bourdieu, Coleman and more famously, Putnam, social capital could be understood as a critical component in social reproduction, educational achievement and administrative efficiency. Social capital seems especially relevant in Central and Eastern Europe and the countries of the former Soviet Union. Not only does it direct attention to informal networks as ways of getting things done, it also explores how strong ties of personal trust co-exist with low levels of general trust and how this can affect economic and political reform. In terms of its actual policy implications, the conclusions of social capital research have not always been clear and it may be fair to say that expectations have been scaled down since the World Bank declared that social capital to be the missing link. This study offers a critical review of over seventy studies that have applied social capital to developments in Central and Eastern Europe and the former Soviet Union. The author draws from a variety of social science disciplines as well as including several reports from international organisations. The review investigates five principal fields in which social capital has been used to date and to provides a series of suggestions as to how such research can help encourage institutional and policy innovation.
Determinants of Audit Fees: Evidence from the Companies Listed in Bahrain

Many studies have been conducted on the market for audit services in Anglo-Saxon countries, but, to-date, none of them have focused on the Middle Eastern countries. This paper examines the audit fee structure in Bahrain for 38 companies listed on the Bahrain Stock Exchange (BSE). By analyzing the data concerning a number of variables representing size, risk, complexity, timing of audit, and profitability, a model is developed of the determinants of audit fees. The study strongly confirms that most of the previous research findings are also applicable to the Bahrain market, and that audit fees are significantly associated with the size, risk, profitability and complexity of the client operations. The study also suggests that other important issues be considered, such as non-audit services, the extent of market concentration, and audit services in the unregulated market.
Distributed torque estimation toward low-latency variable stiffness control for gear-driven torque sensorless humanoid

This paper explains low-latency joint torque feedback control based on torque estimation on each joint for gear-driven humanoid robots with harmonic drives. Force control of gear-driven robots has an advantage in its fully variable stiffness in comparison with elastic robots. However, feedback latency makes gear-driven robots vulnerable to impact rising in several milliseconds. It would be resolved by low-latency torque feedback loop in a single joint, but torque sensors are too large for life-sized humanoid robots. We estimate joint torque from motor current and rotation observed in each joint, and give artificial elasticity to joints using compliance control and shock absorption control. Our controller performance is demonstrated by landing experiments.
Hedge Fund Attrition, Survivorship Bias, and Performance: Perspectives from the Global Financial Crisis

The impact of the global financial crisis since 2007 has been deep and broad, blanketing the financial and economic landscape and hammering the hedge fund industry. Using both active and inactive hedge fund return data from the CISDM database from January of 1994 to March of 2009, we measure survivorship bias, account for attrition rates, estimate a multi-factor model to explain hedge fund performance, and conduct a cross-sectional probit analysis to predict hedge fund attrition during the crisis. Following prior research, we surprisingly do not find survivorship bias to be prevalent during the global financial crisis. Moving a step beyond the literature, however, we identify a hidden survivorship bias attributed to the lack of reporting during the final months of the eventual demise of a fund. We also find unprecedented attrition rates, along with record declines in assets under management and fund closures during the crisis. Using a multi-factor model with both linear and nonlinear risk factors, we find four structural breaks in the data: October of 1998, April of 2000, March of 2003, and February of 2007. Estimating the model for each of the five sub-periods and for the entire period, we find that hedge fund returns can be explained by the linear risk factors (such as the three factors of Fama and French model, the change in credit spread, and the term structure spread) and the non-linear trend-following risk factors of Fung and Hsieh (2001). The evidence also indicates that the average hedge fund manager did not deliver a significantly positive alpha during the crisis. In addition, the cross-sectional probit results reveal that the more seasoned the fund, the higher its pre-crisis return performance, and the more regularly audited its books, the lower was its probability of attrition during the crisis.
Long-Term Instrumental and Reconstructed Temperature Records Contradict Anthropogenic Global Warming

This paper analyses the monthly instrumental temperature records from 5 stations in the northern hemisphere, each of which are reliable, local and well over 200 years in length, as well as two reconstructed long-range yearly records – from a stalagmite near Innsbruck and from tree rings in the northern hemisphere that are about 2000 years long. In the instrumental records, the steepest fall in 100-year linear regression lines happened in the 19th century and the steepest rise in the 20th century, both events being of about the same magnitude. Evaluation by fluctuation analysis (FA) and detrended fluctuation analysis (DFA) revealed that both the 19th century fall and the 20th century rise have very small natural probabilities and must therefore be trends caused by external forcings. In contrast to this, the reconstructed records show far steeper 100-year rises and falls as quite common during the last 2000 years. Consequently, their DFA evaluation revealed far greater Hurst exponents. These results contradict the hypothesis of an unusual (anthropogenic) global warming during the 20th century. The cause of the different Hurst exponents for the instrumental and the reconstructed temperature records is not known. As a speculative hypothesis, the sun's magnetic field, which is correlated with sunspot numbers, could be put forward as an explanation. The long-term low-frequency fluctuations in sunspot numbers are not detectable by FA/DFA in the monthly instrumental records, resulting in low Hurst exponents. The same does not hold true for the 2000-year-long reconstructed records, which explains both their higher Hurst exponents and the higher probabilities of strong 100-year temperature fluctuations being quite common. A long-term synthetic record that embodies the reconstructed sunspot number fluctuations includes the different Hurst exponents of both the instrumental and the reconstructed records and, therefore, corroborates the conjecture.
Ultra Low Power Deep-Learning-powered Autonomous Nano Drones

Flying in dynamic, urban, highly-populated environments represents an open problem in robotics. State-of-the-art (SoA) autonomous Unmanned Aerial Vehicles (UAVs) employ advanced computer vision techniques based on computationally expensive algorithms, such as Simultaneous Localization and Mapping (SLAM) or Convolutional Neural Networks (CNNs) to navigate in such environments. In the Internet-of-Things (IoT) era, nano-size UAVs capable of autonomous navigation would be extremely desirable as self-aware mobile IoT nodes. However, autonomous flight is considered unaffordable in the context of nano-scale UAVs, where the ultra-constrained power envelopes of tiny rotor-crafts limit the on-board computational capabilities to low-power microcontrollers. In this work, we present the first vertically integrated system for fully autonomous deep neural network-based navigation on nano-size UAVs. Our system is based on GAP8, a novel parallel ultra-low-power computing platform, and deployed on a 27 g commercial, open-source CrazyFlie 2.0 nano-quadrotor. We discuss a methodology and software mapping tools that enable the SoA CNN presented in [1] to be fully executed on-board within a strict 12 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 94 mW on average - 1% of the power envelope of the deployed nano-aircraft.
Radiation measurement accuracy of Z-dynamic hohlraums

As calculational capabilities mature the data accuracy requirements become more stringent. Typical Z-pinch power measurements use multiple sets of filtered X-Ray Diodes1 (XRD) to provide temporally and spectrally resolved information on the pinch performance within a +/− 12% error bar. Integrated power measurements are provided by Ni-foil bolometers2 with +/− 10% accuracy
Learning Feature Engineering for Classification

Feature engineering is the task of improving predictive modelling performance on a dataset by transforming its feature space. Existing approaches to automate this process rely on either transformed feature space exploration through evaluation-guided search, or explicit expansion of datasets with all transformed features followed by feature selection. Such approaches incur high computational costs in runtime and/or memory. We present a novel technique, called Learning Feature Engineering (LFE), for automating feature engineering in classification tasks. LFE is based on learning the effectiveness of applying a transformation (e.g., arithmetic or aggregate operators) on numerical features, from past feature engineering experiences. Given a new dataset, LFE recommends a set of useful transformations to be applied on features without relying on model evaluation or explicit feature expansion and selection. Using a collection of datasets, we train a set of neural networks, which aim at predicting the transformation that impacts classification performance positively. Our empirical results show that LFE outperforms other feature engineering approaches for an overwhelming majority (89%) of the datasets from various sources while incurring a substantially lower computational cost.
Testes empíricos sobre o comportamento assimétrico dos custos nas empresas brasileiras

Este estudo testa e confirma a hipotese de que os custos das empresas brasileiras apresentam elasticidade assimetrica em relacao a variacoes nas receitas, ou seja, que os custos aumentam com maior intensidade quando a receita aumenta do que no sentido oposto, conforme evidencias empiricas recentes com empresas norte-americanas. Ao contrario da evidencia, no entanto, essa assimetria nao parece diminuir quando se consideram periodos maiores do que um exercicio. A confirmacao de uma possivel reversao parcial da assimetria quando se consideram periodos defasados, observada em pesquisas anteriores, e confirmada no estudo. A metodologia utilizada envolve diferentes tipos de regressao em panel data. O artigo pretende contribuir para o melhor conhecimento do comportamento dos custos das empresas brasileiras em relacao a variacoes no seu nivel de atividade, tema relevante para a sua administracao, para os contadores e para os analistas financeiros externos. Utilizando uma amostra de 198 empresas num periodo de 17 anos, constatou-se que os modelos de custos assimetricos propostos por Anderson, Banker e Janakiraman (2003) sao, parcialmente, aplicaveis ao Brasil.
Randomized trial of conventional balloon angioplasty versus cutting balloon for in-stent restenosis. Acute and 24-hour angiographic and intravascular ultrasound changes and long-term follow-up.

BACKGROUND The aim of this study was to investigate the angiographic and intravascular ultrasound (IVUS) changes following cutting balloon (CB) and percutaneous transluminal coronary angioplasty (PTCA) treatment in in-stent restenosis. METHODS Fifty consecutive patients with in-stent restenosis were randomized to treatment with CB (n = 25) or PTCA (n = 25). The size of the device was selected using IVUS according to a 1:1 device-to-stent ratio and balloons were inflated to a maximal pressure of 8 atm. Quantitative coronary angiography (QCA) and IVUS (both planar and volumetric) evaluations were carried out before and after treatment and 24 hours later. In case of suboptimal results at 24 hours (> or = 50% diameter stenosis at QCA and/or < or = 4.7 mm2 minimal lumen area [MLA] at IVUS), the patients were re-randomized to receive additional treatment (CB for PTCA and vice versa) or to follow-up. Measurements included the minimal lumen diameter and diameter stenosis for QCA and the external elastic membrane area (EEMA), stent area (SA), MLA, restenosis area (RA = SA - MLA) and plaque + media area (PMA = EEMA - SA) for IVUS. RESULTS A similar minimal lumen diameter increase (1.19 +/- 0.44 vs 1.37 +/- 0.55 mm) and diameter stenosis decrease (-37 +/- 14 vs -45 +/- 13%) was found after PTCA and CB. No significant difference was found in MLA increase (4.81 +/- 1.9 vs 5.45 +/- 2.0 mm2) and RA decrease (-3.8 +/- 1.3 vs -4.2 +/- 1.7 mm2) in PTCA and CB. SA, EEMA and PMA did not significantly change after treatment in either group. Of the total mean lumen enlargement after PTCA and CB, 20% was due to additional stent expansion and 80% was due to RA decrease. At 24 hours, a greater minimal lumen diameter increase (-0.23 +/- 0.34 vs -0.06 +/- 0.23 mm, p = 0.03) and MLA loss (-1.9 +/- 1.4 vs 0.37 +/- 0.8 mm2, p = 0.000) and RA increase (1.74 +/- 1.3 vs 0.37 +/- 0.52 mm2, p = 0.000) were detected in PTCA vs CB. Volumetric changes paralleled planar IVUS variations. A suboptimal result was more frequently found in PTCA as compared to CB (36 vs 4%, p < 0.01). At follow-up, PTCA had a higher target lesion revascularization as compared to CB (40 vs 12.5%, p < 0.05). CONCLUSIONS In in-stent restenosis, PTCA and CB share similar effects and mechanisms of lumen enlargement. In-stent tissue is mainly redistributed along a larger stent rather than being extruded out of the stent struts. At 24 hours, a significant lumen loss (instant restenosis) occurred more frequently in PTCA as compared to CB and may account for a higher target lesion revascularization in this group.