Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating Infrared Radiometric Satellite Sea Surface Temperature Retrieval Cold Biases in the Tropics due to Unscreened Optically Thin Cirrus Clouds

AbstractPassive longwave infrared radiometric satellite–based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically thin cirrus (OTC) clouds [cloud optical depth (COD) ≤ 0.3]. Level 2 nonlinear SST (NLSST) retrievals over tropical oceans (30°S–30°N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument. OTC clouds are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level 2 data, representing over 99% of all contaminating cirrus found. Cold-biased NLSST (MODIS, AVHRR, and VIIRS) and triple-window (AVHRR and VIIRS only) SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5-km-thick OTC cloud placed incrementally from 10.0 to 18.0 km above mean sea level.
Multi-Scale Depth from Slope with Weights

We describe a robust method to recover the depth coordinate from a normal or slope map of a scene, obtained e.g. through photometric stereo or interferometry. The key feature of our method is the fast solution of the Poisson-like integration equations by a multi-scale iterative technique. The method accepts a weight map that can be used to exclude regions where the slope information is missing or untrusted, and to allow the integration of height maps with linear discontinuities (such as along object silhouettes) which are not recorded in the slope maps. Except for pathological cases, the memory and time costs of our method are typically proportional to the number of pixels N. Tests show that our method is as accurate as the best weighted slope integrators, but substantially more efficient in time and space.
Class-based delta-encoding for high-speed train data stream

Railway transportation plays an important role in both economic and social development. The requirements of the railway traffic increase in recent decades. In order to meet the growing demand, a new generation control system of railway transportation emerges. It consists of collection, transmission, analysis and scheduling module. In such a context, an information transmission system is built to connect trains and scheduling center. However, the infrastructure of the railway system cannot provide enough bandwidth for such amount of data. As a result, the efficiency of data transmission cannot be ensured. In this paper, we focus on the compression algorithm that reduce the amount of transmitted data and improve the system performance. Based on the analysis of the common algorithms, an efficient compression algorithm, named delta-encoding, is proposed. It consists of two steps: preprocessing and compression. Delta-encoding utilizes a class-based difference model, which reduces the data redundancy, to realize a preprocessing algorithm. With the combination of preprocessing algorithm and a regular compression algorithm, delta-encoding has better performance on compression ratio, and becomes a universal hybrid algorithm for structured data in IoT system rather than a specific algorithm in high-speed train system. Finally, several experiments are provided to prove that delta-encoding have advantages in both compression ratio and compression time.
Redundancy in network traffic: findings and implications

A large amount of popular content is transferred repeatedly across network links in the Internet. In recent years, protocol-independent redundancy elimination, which can remove duplicate strings from within arbitrary network flows, has emerged as a powerful technique to improve the efficiency of network links in the face of repeated data. Many vendors offer such redundancy elimination middleboxes to improve the effective bandwidth of enterprise, data center and ISP links alike. In this paper, we conduct a large scale trace-driven study of protocol independent redundancy elimination mechanisms, driven by several terabytes of packet payload traces collected at 12 distinct network locations, including the access link of a large US-based university and of 11 enterprise networks of different sizes. Based on extensive analysis, we present a number of findings on the benefits and fundamental design issues in redundancy elimination systems. Two of our key findings are (1) A new redundancy elimination algorithm based on Winnowing that outperforms the widely-used Rabin fingerprint-based algorithm by 5-10% on most traces and by as much as 35% in some traces. (2) A surprising finding that 75-90% of middlebox's bandwidth savings in our enterprise traces is due to redundant byte-strings from within each client's traffic, implying that pushing redundancy elimination capability to the end hosts, i.e. an end-to-end redundancy elimination solution, could obtain most of the middlebox's bandwidth savings.
WCET-aware Register Allocation Based on Integer-Linear Programming

Current compilers lack precise timing models guiding their built-in optimizations. Hence, compilers apply ad-hoc heuristics during optimization to improve code quality. One of the most important optimizations is register allocation. Many compilers heuristically decide when and where to spill a register to memory, without having a clear understanding of the impact of such spill code on a program's runtime. This paper presents an integer-linear programming (ILP) based register allocator that uses precise worst-case execution time (WCET) models. Using this WCET timing data, the compiler avoids spill code generation along the critical path defining a program's WCET. To the best of our knowledge, this paper is the first one to present a WCET-aware ILP-based register allocator. Our results underline the effectiveness of the proposed techniques. For a total of 55 realistic benchmarks, we reduced WCETs by 20.2% on average and ACETs by 14%, compared to a standard graph coloring allocator. Furthermore, our ILP-based register allocator outperforms a WCET-aware graph coloring allocator by more than a factor of two for the considered benchmarks, while requiring less runtime.
Lessons From Genetically Engineered Animal Models V. Knocking out genes to study liver regeneration: present and future *

Lessons From Genetically Engineered Animal Models. V. Knocking out genes to study liver regeneration: present and future. Am. J. Physiol. 277 ( Gastrointest. Liver Physiol. 40): G917–G921, 1999. —Studies utilizing knockout mice have contributed important new knowledge about the mechanisms that initiate liver regeneration. New mouse lines need to be established to address major questions about these mechanisms, targeting genes for which there is experimental evidence of their involvement in important pathways. Development of conditional, liver-speciﬁc knockout mice would be of great value for these studies.
Fast volumetric deformation on general purpose hardware

High performance deformation of volumetric objects is a common problem in computer graphics that has not yet been handled sufficiently. As a supplement to 3D texture based volume rendering, a novel approach is presented, which adaptively subdivides the volume into piecewise linear patches. An appropriate mathematical model based on tri-linear interpolation and its approximations is proposed. New optimizations are introduced in this paper which are especially tailored to an efficient implementation using general purpose rasterization hardware, including new technologies, such as vertex programs and pixel shaders. Additionally, a high performance model for local illumination calculation is introduced, which meets the aesthetic requirements of visual arts and entertainment. The results demonstrate the significant performance benefit and allow for time-critical applications, such as computer assisted surgery.
Novelty detector for reinforcement learning based on forecasting

The paper proposes a novelty detector based on an artificial neural network forecaster. It shows how such forecaster can be constructed and as a novelty detector. Two variations of the forecaster are presented - one is based on backpropagation, and the other on Rprop. It is shown how the detector can be used to approach the exploration vs. exploitation trade-off. Experimental results are presented for both versions of the detector along with a comparison with novelty detectors based on the concept of the habituated self-organising map (HSOM). It is shown that learning based on the proposed detector can outperform that using the HSOM-based detector. Finally, the paper identifies several lines along which future research may progress.
The Costs and Benefits of Calculation and Moral Rules

There has been a recent upsurge of research on moral judgment and decision making. One important issue with this body of work concerns the relative advantages of calculating costs and benefits versus adherence to moral rules. The general tenor of recent research suggests that adherence to moral rules is associated with systematic biases and that systematic cost-benefit analysis is a normatively superior decision strategy. This article queries both the merits of cost-benefit analyses and the shortcomings of moral rules. We argue that outside the very narrow domain in which consequences can be unambiguously anticipated, it is not at all clear that calculation processes optimize outcomes. In addition, there are good reasons to believe that following moral rules can lead to superior consequences in certain contexts. More generally, different modes of decision making can be seen as adaptations to particular environments.
Evaluation of nonlinear frequency compression for school-age children with moderate to moderately severe hearing loss.

BACKGROUND Previous research has indicated that children with moderate hearing loss experience difficulty with recognition of high-frequency speech sounds, such as fricatives and affricates. Conventional behind-the-ear (BTE) amplification typically does not provide ample output in the high frequencies (4000 Hz and beyond) to ensure optimal audibility for these sounds. PURPOSE To evaluate nonlinear frequency compression (NLFC) as a means to improve speech recognition for children with moderate to moderately severe hearing loss. RESEARCH DESIGN Within subject, crossover design with repeated measures across test conditions. STUDY SAMPLE Fifteen children, aged 5-13 yr, with moderate to moderately severe high-frequency sensorineural hearing loss were fitted with Phonak Nios, microsized, BTE hearing aids. These children were previous users of digital hearing aids and communicated via spoken language. Their speech and language abilities were age-appropriate. DATA COLLECTION AND ANALYSIS Aided thresholds and speech recognition in quiet and in noise were assessed after 6 wk of use with NLFC and 6 wk of use without NLFC. Participants were randomly assigned to counter-balanced groups so that eight participants began the first 6 wk trial with NLFC enabled and the other seven participants started with NLFC disabled. Then, the provision of NLFC was switched for the second 6 wk trial. Speech recognition in quiet was assessed via word recognition assessments with the University of Western Ontario (UWO) Plural Test and recognition of vowel-consonant-vowel nonsense syllables with the Phonak Logatome test. Speech recognition in noise was assessed by evaluating the signal-to-noise ratio in dB for 50% correct performance on the Bamford-Kowal-Bench Speech-in-Noise (BKB-SIN) test, an adaptive test of speech perception in a multitalker babble background. RESULTS Aided thresholds for high-frequency stimuli were significantly better when NLFC was enabled, and use of NLFC resulted in significantly better speech recognition in quiet for the UWO Plural Test and for the phonemes /d/ and /s/ on the Phonak Logatome test. There was not a statistically significant difference in performance on the BKB-SIN test between the NLFC enabled and disabled conditions. CONCLUSIONS These results indicate that NLFC improves audibility for and recognition of high-frequency speech sounds for children with moderate to moderately severe hearing loss in quiet listening situations.
MASER EMISSION FROM SiO ISOTOPOLOGUES TRACES THE INNERMOST 100 AU AROUND RADIO SOURCE I IN ORION BECKLIN–NEUGEBAUER/KLEINMANN-LOW

We have used the Very Large Array at 7 mm wavelength to image five rotational transitions (J = 1–0) from three SiO isotopologues toward Orion Becklin–Neugebauer/Kleinmann-Low (BN/KL): 28SiO v = 0, 1, 2; and 29SiO and 30SiO v = 0. For the first time, we have mapped the 29SiO and 30SiO J = 1–0 emission, established the maser nature of the emission, and confirmed association with the deeply embedded high-mass young stellar object commonly denoted radio Source I. The 28SiO v = 0 maser emission shows a bipolar structure that extends over ∼700 AU along a northeast–southwest axis, and we propose that it traces a bipolar outflow driven by Source I. The high-brightness isotopic SiO maser emission imaged with a ≲0. ″2 resolution has a more compact distribution, generally similar to that of the 28SiO v = 1, 2 emission, and it probably traces bulk gas flows in a region of diameter ≲100 AU centered on Source I. On small scales of ≲10 AU, however, compact 29SiO/30SiO v = 0 and 28SiO v = 1, 2 emission features may be offset from one another in position and line-of-sight velocity. From a radiative transfer analysis based on a large velocity gradient pumping model, we derive similar temperatures and densities for the optimum excitation of both 29SiO/30SiO v = 0 and 28SiO v = 1, 2 masers, significantly higher than required for 28SiO v = 0 maser excitation. In order to account for the small-scale differences among the isotopologues (v = 0) and the main species (v = 1, 2), follow-up radiative transfer modeling that incorporates nonlocal line overlap among transitions of all SiO isotopic species may be required.
Unit Mixed Interval Graphs

In this paper we extend the work of Rautenbach and Szwarcter [8] by giving a structural characterization of graphs that can be represented by the intersection of unit intervals that may or may not contain their endpoints. A characterization was proved independently by Joos in [6], however our approach provides an algorithm that produces such a representation, as well as a forbidden graph characterization.
Analysis of RFI Identification and Mitigation in CAROLS Radiometer Data Using a Hardware Spectrum Analyser

A method to identify and mitigate radio frequency interference (RFI) in microwave radiometry based on the use of a spectrum analyzer has been developed. This method has been tested with CAROLS L-band airborne radiometer data that are strongly corrupted by RFI. RFI is a major limiting factor in passive microwave remote sensing interpretation. Although the 1.400–1.427 GHz bandwidth is protected, RFI sources close to these frequencies are still capable of corrupting radiometric measurements. In order to reduce the detrimental effects of RFI on brightness temperature measurements, a new spectrum analyzer has been added to the CAROLS radiometer system. A post processing algorithm is proposed, based on selective filters within the useful bandwidth divided into sub-bands. Two discriminant analyses based on the computation of kurtosis and Euclidian distances have been compared evaluated and validated in order to accurately separate the RF interference from natural signals.
Smooth Operators

We develop a generic approach to form smooth versions of basic mathematical operations like multiplication, composition, change of measure, and conditional expectation, among others. Operations which result in functions outside the reproducing kernel Hilbert space (such as the product of two RKHS functions) are approximated via a natural cost function, such that the solution is guaranteed to be in the targeted RKHS. This approximation problem is reduced to a regression problem using an adjoint trick, and solved in a vector-valued RKHS, consisting of continuous, linear, smooth operators which map from an input, real-valued RKHS to the desired target RKHS. Important constraints, such as an almost everywhere positive density, can be enforced or approximated naturally in this framework, using convex constraints on the operators. Finally, smooth operators can be composed to accomplish more complex machine learning tasks, such as the sum rule and kernelized approximate Bayesian inference, where state-of-the-art convergence rates are obtained.
Use of remote sensing and a geographical information system in a national helminth control programme in Chad.

OBJECTIVE To design and implement a rapid and valid epidemiological assessment of helminths among schoolchildren in Chad using ecological zones defined by remote sensing satellite sensor data and to investigate the environmental limits of helminth distribution. METHODS Remote sensing proxy environmental data were used to define seven ecological zones in Chad. These were combined with population data in a geographical information system (GIS) in order to define a sampling protocol. On this basis, 20 schools were surveyed. Multilevel analysis, by means of generalized estimating equations to account for clustering at the school level, was used to investigate the relationship between infection patterns and key environmental variables. FINDINGS In a sample of 1023 schoolchildren, 22.5% were infected with Schistosoma haematobium and 32.7% with hookworm. None were infected with Ascaris lumbricoides or Trichuris trichiura. The prevalence of S. haematobium and hookworm showed marked geographical heterogeneity and the observed patterns showed a close association with the defined ecological zones and significant relationships with environmental variables. These results contribute towards defining the thermal limits of geohelminth species. Predictions of infection prevalence were made for each school surveyed with the aid of models previously developed for Cameroon. These models correctly predicted that A. lumbricoides and T. trichiura would not occur in Chad but the predictions for S. haematobium were less reliable at the school level. CONCLUSION GIS and remote sensing can play an important part in the rapid planning of helminth control programmes where little information on disease burden is available. Remote sensing prediction models can indicate patterns of geohelminth infection but can only identify potential areas of high risk for S. haematobium.
A Note on the Size of Denoising Neural Networks

Patch based denoising algorithms seek to approximate the conditional expectation of clean patches given their related noisy observations. In this note, we give a probabilistic account of how various algorithms approach this problem and in particular, we argue that small neural networks can denoise small-scale texture patterns almost as well as their large counterparts. The analysis further indicates that self-similarity and Bayesian approaches such as neural networks are complementary paradigms for patch denoising, which we illustrate with an algorithm that effectively complements BM3D with small neural networks, thereby outperforming BM3D with minor additional cost.
Burden of Influenza and Influenza-associated Pneumonia in the First Year of Life in a Prospective Cohort Study in Managua, Nicaragua

Background: Influenza is a major public health problem worldwide; however, relatively little is known about influenza in tropical regions, especially for infants. Additional information is required to inform public health policy making, in particular vaccination guidelines. Methods: Between September 2011 and July 2013, we enrolled newborns into the Nicaraguan Birth Cohort Study. Infants were provided primary medical care and actively followed for reverse-transcription polymerase chain reaction–confirmed influenza virus infection when presenting with influenza-like illness or undifferentiated fever. This report presents data pertaining to the first year of life. Results: Of the 518 children enrolled in the study, 441 participated throughout their first year of life, 71 were withdrawn, and 6 died. Overall, 13% of the participants experienced at least 1 laboratory-confirmed influenza virus infection. The overall incidence of influenza was 15.5 cases per 100 person-years [95% confidence interval (CI): 12.2–19.5]. Infants aged 6–11 months experienced significantly higher rates of laboratory-confirmed influenza than infants aged 0–5 months (incidence rate ratio: 2.1; 95% CI: 1.3–3.4). The overall incidence of pneumonia was 52.6 cases per 100 person-years (95% CI: 46.3–59.6). Three percent of the pneumonia cases were influenza associated, and the incidence of influenza-associated pneumonia and hospitalization was 1.7 (95% CI: 0.9–3.5) and 0.22 (95% CI: 0.03–1.55) cases per 100 person-years, respectively. Conclusions: We found a significant burden of influenza and influenza-associated severe respiratory outcomes in infants. Our results support the need to explore the potential value of vaccinating pregnant women and infants aged >6 months, as recommended by the World Health Organization in 2012.
UC3M\_13: Disambiguation of Person Names Based on the Composition of Simple Bags of Typed Terms

This paper describes a system designed to disambiguate person names in a set of Web pages. In our approach Web documents are represented as different sets of features or terms of different types (bag of words, URLs, names and numbers). We apply Agglomerative Vector Space clustering that uses the similarity between pairs of analogous feature sets. This system achieved a value of 66% for Fα=0.2 and a value of 48% for Fα=0.5 in the Web People Search Task at SemEval-2007 (Artiles et al., 2007).
Ultra-broadband tapered slot terahertz antennas on thin polymeric substrate

We developed a planar tapered slot antenna on a thin polymeric substrate with low dielectric constant for terahertz-wave applications. The efficiency and the gain of this antenna are not degraded even for higher frequencies. Due to the ultra-broadband features, we demonstrate multiband terahertz wireless error-free communications at 1.5 Gbits/s for both 120 and 300 GHz bands.