Miracle-dz/UniFAR-FTUs huggingface dataset:
Relative biodiversity trends of the Cenozoic Caribbean Region : investigations of possible causes and issues of scale using a biostratigraphic database of corals, echinoids, bivalves, and gastropods

The fossil record remains the primary tool to understand macro-evolutionary processes over time. Unfortunately, much debate has centered upon sampling biases that pervade the rock and fossil record. A relative metric is presented that reduces the effect of uneven distribution of fossils across time and space. The Diversity Index of Growth (DIG) metric measures relative change of biodiversity because it examines the four key parameters of biodiversity: New, Extinct, Stable and Total, as obtained from biostratigraphic data. In this study, DIG was utilized to examine biodiversity trends of a Cenozoic Caribbean database consisting of genus-level biostratigraphic occurrences of corals, echinoids, bivalves and gastropods. The results of this study indicate that the individual class-level trends observed from the database are consistent with previously interpreted trends of the four clades. Key features of the observed biodiversity trends of the Caribbean include three peaks of diversification, including increased biodiversity near the Paleocene-Eocene Thermal Maximum (PETM). Marine invertebrate biodiversity appears to be linked to a variety of environmental processes, including volcanism and climate change. The timing of biodiversity increases corresponds to increases in sea-level and three major volcanic episodes in the Caribbean. The trends of the total biodiversity follow sea-level change, especially when sea-level data are reduced to relative change and compiled into time increments equal to the fossil data. The positive relationship between sea-level increases and biodiversification is observed at several spatial-temporal scales, and indicates that relative biotic diversity
Back to the Future for Consistency-Based Trajectory Tracking

Given a model of a physical process and a sequence of commands and observations received over time, the task of an autonomous controller is to determine the likely states of the process and the actions required to move the process to a desired configuration. We introduce a representation and algorithms for incrementally generating approximate belief states for a restricted but relevant class of partially observable Markov decision processes with very large state spaces. The algorithm incrementally generates, rather than revises, an approximate belief state at any point by abstracting and summarizing segments of the likely trajectories of the process. This enables applications to efficiently maintain a partial belief state when it remains consistent with observations and revisit past assumptions about the process’s evolution when the belief state is ruled out. The system presented has been implemented and results on examples from the domain of spacecraft control are presented.
Water tracks intensify surface energy and mass exchange in the Antarctic McMurdo Dry Valleys

Abstract. The hydrologic cycle in the Antarctic McMurdo Dry Valleys (MDV) is mainly controlled by surface energy balance. Water tracks are channel-shaped high-moisture zones in the active layer of permafrost soils and are important solute and water pathways in the MDV. We evaluated the hypothesis that water tracks alter the surface energy balance in this dry, cold, and ice-sheet-free environment during summer warming and may therefore be an increasingly important hydrologic feature in the MDV in the face of landscape response to climate change. The surface energy balance was measured for one water track and two off-track reference locations in Taylor Valley over 26 d of the Antarctic summer of 2012–2013. Turbulent atmospheric fluxes of sensible heat and evaporation were observed using the eddy-covariance method in combination with flux footprint modeling, which was the first application of this technique in the MDV. Soil heat fluxes were analyzed by measuring the heat storage change in the thawed layer and approximating soil heat flux at ice table depth by surface energy balance residuals. For both water track and reference locations over 50 % of net radiation was transferred to sensible heat exchange, about 30 % to melting of the seasonally thawed layer, and the remainder to evaporation. The net energy flux in the thawed layer was zero. For the water track location, evaporation was increased by a factor of 3.0 relative to the reference locations, ground heat fluxes by 1.4, and net radiation by 1.1, while sensible heat fluxes were reduced down to 0.7. Expecting a positive snow and ground ice melt response to climate change in the MDV, we entertained a realistic climate change response scenario in which a doubling of the land cover fraction of water tracks increases the evaporation from soil surfaces in lower Taylor Valley in summer by 6 % to 0.36 mm d−1. Possible climate change pathways leading to this change in landscape are discussed. Considering our results, an expansion of water track area would make new soil habitats accessible, alter soil habitat suitability, and possibly increase biological activity in the MDV. In summary, we show that the surface energy balance of water tracks distinctly differs from that of the dominant dry soils in polar deserts. With an expected increase in area covered by water tracks, our findings have implications for hydrology and soil ecosystems across terrestrial Antarctica.
One year in Antarctica: Mucosal immunity at three Australian stations

The effect of a year's isolation in Antarctica on the human mucosal immune system was assessed during the winter of 1992 at three Australian Antarctic stations: Casey, Davis and Mawson. Saliva samples were collected from each expeditioner prior to their departure from Australia and during each month in Antarctica. The concentrations of salivary immunoglobulins IgA and IgG were significantly different between the three stations, but there were no differences for salivary IgM and albumin. The mean concentrations of IgA were higher at Mawson (P < 0.008), and the mean concentrations of IgG were lower at Davis (P < 0.001) compared with the other stations. Ranges of values observed at the stations over the 12–13 months were similar. The variability of values within individuals showed station differences for salivary IgM and IgG only. The study revealed significant changes in salivary immunoglobulin values over the period in Antarctica, with similar patterns at the three Australian stations. The salivary IgA and IgM levels were lower in the first 4 months in Antarctica (January–April) and increased to maximum values in July–August, before returning to mean levels when isolation was broken in October–November. The patterns of salivary IgA and IgM suggest that stressors due to isolation may play a role in alterations of mucosal immunity in expeditioners in Antarctica.
Association of C1q- and conglutinin-binding immune complexes with high consumption of alpha-2-macroglobulin in synovial fluids of patients with rheumatoid arthritis.

The consumption of alpha-2-macroglobulin (a2M) by proteinases in synovial fluids (SF) was indirectly measured by determining trypsin binding to solid-phase immunoadsorbed SF-a2M. In addition immune complexes (IC) were assessed by the solid-phase C1q-binding assay as well as the solid-phase conglutinin binding assay in rheumatoid (RA; n = 25) and osteoarthritic (OA; n = 9) SF. Elevated levels were found as follows: a2M X proteinase complexes (a2M X P) in 73.5% (RA, n = 20; OA, n = 5), solid-phase C1q-binding IC (C1q-IC) in 52% (13 out of 25 RA-SF) and bovine conglutinin binding IC (KgB-IC) in 54% (13 out of 24 RA-SF). All OA-SF were in either IC assay negative. Consumption of a2M in OA-SF and seronegative RA-SF was not more than 15% of total SF-a2M, showing a mean value of 19.5 and 13.5 micrograms a2M X P/ml SF. Seropositive RA-SF had an a2M X P mean value of 96.4 micrograms/ml SF, which differed significantly (p less than or equal to 0.05) from the former two groups. Similarly, RA-SF which were negative in either IC assay had a low a2M X P mean value (20.0 micrograms/ml SF). This contrasted sharply with the a2M X P means obtained in IC-positive RA-SF, which amounted to 131.5 micrograms a2M X P/ml SF in C1q-IC positive RA-SF and to 110.4 micrograms a2M X P/ml SF in KgB-IC positive RA-SF, respectively. (ABSTRACT TRUNCATED AT 250 WORDS)
Cost Sensitive Pushout Policy and Expelling Policy with Dynamic Threshold for Shared memory switches with Versatile Traffic

Almost all available literature on buffer management suggests to offer a worst treatment to the low priority packet to improve the performance of high priority packet. But with simulation results and analytical method we have found that merely offering worst treatment to the low priority packet will not help to improve the overall performance. On contrary, beyond a certain limit the worst treatment to low priority packet degrades the over all performance. This is more pronounced in the case of expelling class of buffer management. In the case of versatile traffic of diffserv. the situation gets worse if we treat the low priority packets in a very worst manner. To overcome these limitations we have presented here the reinvented pushout policy and expelling policy with dynamic threshold. We have found the limit up to, which a low priority packet can be dropped to save high priority packet. We have also investigated up to when loss probability of total weighted cost is optimum. A special expelling policy with dynamic threshold is introduced for maximum weighted throughput.
AIR POLLUTANTS MITIGATION BY USING VARIOUS FORMS OF PHOTOCATALYTIC CEMENTITIOUS COATINGS MATERIALS

Nitric oxide generated from various sources like car combustion is one of the most surrounding pollutants, which can be transferred from one form to another in the presence of sunlight. Titanium dioxide considered one of the most environmentally friendly active photocatalytics that can be used with building materials safely and effectively to react with nitric oxides. To study the possibility for the reduction of air pollutants like nitric oxides, two types of substrates coatings were prepared. First, mixing nano particles of TiO2 with cement paste in two percents 3% and 6%. Second, mortar substrates coated with nano TiO2 aqueous solution. Two coating methods have been used dip and spray. A laboratory test procedure was adopted to assess the performance of the prepared photoactive specimens. The specimens were subjected to NO gas and there efficiency in gas removal was monitored with time. Results showed the effectivity of coating building materials with titanium dioxide, the removal of gaseous pollutants like nitric oxide reached to 98.85% when spary and dip methods are used. Mixing nano titanium with a percent of 3% was also efficient in the removal of nitric oxides, the removal reached to 97%. It was concluded that spray method was more practical to be used.
Symbolic method for deriving policy in reinforcement learning

This paper addresses the problem of deriving a policy from the value function in the context of reinforcement learning in continuous state and input spaces. We propose a novel method based on genetic programming to construct a symbolic function, which serves as a proxy to the value function and from which a continuous policy is derived. The symbolic proxy function is constructed such that it maximizes the number of correct choices of the control input for a set of selected states. Maximization methods can then be used to derive a control policy that performs better than the policy derived from the original approximate value function. The method was experimentally evaluated on two control problems with continuous spaces, pendulum swing-up and magnetic manipulation, and compared to a standard policy derivation method using the value function approximation. The results show that the proposed method and its variants outperform the standard method.
ON BIOLOGICAL OXIDATIONS AS FUNCTION OF TEMPERATURE

1. The critical thermal increments are calculated for respiratory processes (O2 consumption, CO2 production) in various plants and animals. They are characteristically found to be of two, possibly three, types: µ = 11,500, and 16,100 or 16,700. The first is commonly encountered above 15°, the second below that temperature, but these relations may be reversed. (The value of µ may be significantly changed in inanition.) 2. For reduction of methylene blue by bacteria, through removal of H from succinic acid, µ = 16,700. This process (Quastel and Whetham, 1924) at constant temperature is a function of the hydroxyl ion concentration. The suggestive identity is pointed out of the critical increment for this reduction phenomenon with that deduced for biological respirations in which a dehydrogenation mechanism is supposed to be of widespread occurrence, and in connection with which Fe very likely has a catalytic rôle. The action of OH' is believed to be revealed in the value µ = 11,500, frequently obtained in connection with respiration. 3. A somewhat lower µ (16,140) is associated with the oxidation of Fe'', and may be compared with (1) that of respiration in sea urchin eggs, for which (Warburg) iron is catalyst, and (2) that for some simple reactions in which Fe is known to serve as catalyst; it is not found for oxidative reactions in which Fe is not involved. 4. The bearing of these findings is discussed in relation to the theory of functional analysis of concurrent catalyzed reactions in protoplasm. It is shown that for a number of activities in which the effects of respiration may safely be assumed, the values of the critical increments are consistent with those determined for processes of respiration. 5. The further development of these views may lead to an extremely important method of identifying controlling reactions in undisturbed living matter.
Instrument Equalizer for Query-by-Example Retrieval: Improving Sound Source Separation Based on Integrated Harmonic and Inharmonic Models

This paper describes a music remixing interface, called Instrument Equalizer, that allows users to control the volume of each instrument part within existing audio recordings in real time. Although query-by-example retrieval systems need a user to prepare favorite examples (songs) in general, our interface gives a user to generate examples from existing ones by cutting or boosting some instrument/vocal parts, resulting in a variety of retrieved results. To change the volume, all instrument parts are separated from the input sound mixture using the corresponding standard MIDI file. For the separation, we used an integrated tone (timbre) model consisting of harmonic and inharmonic models that are initialized with template sounds recorded from a MIDI sound generator. The remaining but critical problem here is to deal with various performance styles and instrument bodies that are not given in the template sounds. To solve this problem, we train probabilistic distributions of timbre features by using various sounds. By adding a new constraint of maximizing the likelihood of timbre features extracted from each tone model, we succeeded in estimating model parameters that better express actual timbre.
Heard It Through the Grapevine : The Effects of Online Word of Mouth on Music Sales

Word of mouth (WOM) has always been one of the most credible and influential sources of information for a consumer. With the advent of the Internet, new mediums of communication, such as blogs and social networking sites, have opened up, allowing more consumers to gather WOM information more easily than ever before. In this study, I examine the usefulness of online WOM, particularly from blogs and social networking sites, in predicting sales in the music industry. I track the changes in online WOM for a sample of 108 albums for four weeks before and after their release dates, and use a linear regression and regression tree to examine the relative significance of online WOM variables on their observation date in predicting album unit sales two weeks after that date. I find that the volume of blog posts about an album is the most consistently significant measure, with each additional blog post corresponding to higher album sales. In addition, I found that greater increases in an artist’s Myspace friends week over week and higher average consumer ratings also corresponded to higher sales. Although evidence supports my hypothesis that online word of mouth can be an important predictor of sales, my study also found that traditional factors are still relevant – albums released by major labels and albums with a number of reviews from mainstream sources like Rolling Stone also tended to have higher sales.
An evaluation of conflation accuracy using finite-state transducers

Purpose – To evaluate the accuracy of conflation methods based on finite‐state transducers (FSTs). Design/methodology/approach – Incorrectly lemmatized and stemmed forms may lead to the retrieval of inappropriate documents. Experimental studies to date have focused on retrieval performance, but very few on conflation performance. The process of normalization we used involved a linguistic toolbox that allowed us to construct, through graphic interfaces, electronic dictionaries represented internally by FSTs. The lexical resources developed were applied to a Spanish test corpus for merging term variants in canonical lemmatized forms. Conflation performance was evaluated in terms of an adaptation of recall and precision measures, based on accuracy and coverage, not actual retrieval. The results were compared with those obtained using a Spanish version of the Porter algorithm.Findings – The conclusion is that the main strength of lemmatization is its accuracy, whereas its main limitation is the underanalysis o.
Reduced Complexity Calculation of LMMSE Filter Coefficients for GFDM

A low-complexity algorithm for calculation of LMMSE filter coefficients for Generalized Frequency Division Multiplexing (GFDM) in a fading multipath environment is derived. The simplification is based on the block circularity of the involved matrices. The proposal reduces complexity from cubic to squared order. The proposed approach can be generalized to other waveforms with circular pulse shaping.
Transcranial Direct Current Stimulation (tDCS) of the Right Inferior Frontal Gyrus Attenuates Skin Conductance Responses to Unpredictable Threat Conditions

Patients with panic and post-traumatic stress disorders seem to show increased psychophysiological reactions to conditions of unpredictable (U) threat, which has been discussed as a neurobiological marker of elevated levels of sustained fear in these disorders. Interestingly, a recent study found that the right inferior frontal gyrus (rIFG) is correlated to the successful regulation of sustained fear during U threat. Therefore this study aimed to examine the potential use of non-invasive brain stimulation to foster the rIFG by means of anodal transcranial direct current stimulation (tDCS) in order to reduce psychophysiological reactions to U threat. Twenty six participants were randomly assigned into an anodal and sham stimulation group in a double-blinded manner. Anodal and cathodal electrodes (7 * 5 cm) were positioned right frontal to target the rIFG. Stimulation intensity was I = 2 mA applied for 20 min during a task including U threat conditions (NPU-task). The effects of the NPU paradigm were measured by assessing the emotional startle modulation and the skin conductance response (SCR) at the outset of the different conditions. We found a significant interaction effect of condition × tDCS for the SCR (F(2,48) = 6.3, p < 0.01) without main effects of condition and tDCS. Post hoc tests revealed that the increase in SCR from neutral (N) to U condition was significantly reduced in verum compared to the sham tDCS group (t(24) = 3.84, p < 0.001). Our results emphasize the causal role of rIFG for emotional regulation and the potential use of tDCS to reduce apprehension during U threat conditions and therefore as a treatment for anxiety disorders.
Identifying First Episodes of Psychosis in Psychiatric Patient Records using Machine Learning

Natural language processing is being pressed into use to facilitate the selection of cases for medical research in electronic health record databases, though study inclusion criteria may be complex, and the linguistic cues indicating eligibility may be subtle. Finding cases of first episode psychosis raised a number of problems for automated approaches, providing an opportunity to explore how machine learning technologies might be used to overcome them. A system was delivered that achieved an AUC of 0.85, enabling 95% of relevant cases to be identified whilst halving the work required in manually reviewing cases. The techniques that made this possible are presented.
Color Constancy by Deep Learning

Computational color constancy aims to estimate the color of the light source. The performance of many vision tasks, such as object detection and scene understanding, may benefit from color constancy by estimating the correct object colors. Since traditional color constancy methods are based on specific assumptions, none of those methods can be used as a universal predictor. Further, shallow learning schemes are used for training-based color constancy approaches, suffering from limited learning capacity. In this paper, we propose a framework using Deep Neural Networks (DNNs) to obtain an accurate light source estimator to achieve color constancy. We formulate color constancy as a DNN-based regression approach to estimate the color of the light source. The model is trained using datasets of more than a million images. Experiments show that the proposed algorithm outperforms the state-of-the-art by 9\%. Especially in cross dataset validation, reducing the median angular error by 35\%. Further, in our implementation, the algorithm operates at more than $100$ fps during
A bootstrap-based iterative selection for ensemble generation

We propose a bootstrap-based iterative method for generating classifier ensembles called Iterative Classifier Selection Bagging (ICS-Bagging). Each iteration of ICS-Bagging has two phases: i) bootstrap sampling to generate a pool of classifiers; and, ii) selection of the best classifier of the pool using a fitness function based on the ensemble accuracy and diversity. The selected classifier is added to the final ensemble. The bootstrap sampling runs on each iteration and updates the probability of sampling per class based on the class accuracy. This process is repeated until the number of classifiers in the final ensemble is reached. For the specific case of imbalanced datasets, we also propose the SMOTE-ICS-Bagging, a variation of the ICS-Bagging that runs SMOTE at the beginning of each iteration in order to reduce the class imbalance before data sampling. We compared the proposed techniques with Bagging, Random Subspace and SMOTEBagging, using 15 imbalanced datasets from KEEL. The results show the proposed techniques outperform all other techniques in accuracy. Ranking diagrams revealed that the proposed algorithms achieved the highest rankings in accuracy, outperforming SMOTEBagging, a renowned ensemble generation method for imbalanced datasets.