Miracle-dz/UniFAR-FTUs huggingface dataset:
Time allocation in Greenland high-arctic waders during summer

Abstract During the summer of 2000, a preliminary study on time allocation in four arctic wader species (Common Ringed Plover Charadrius hiaticula , Sanderling Calidris alba , Dunlin C. alpina , Ruddy Turnstone Arenaria inter-pres ) was conducted at Zackenberg Research Station in high-arctic Northeast Greenland. We scored behaviour of non-disturbed, but not individually recognisable birds in typical habitats. With few exceptions, non-incubating birds (i.e. birds not sitting on eggs) used more than half their daytime for feeding, and during the pre- and post-breeding periods, when waders build up body stores, as much as 75-92% of the daytime was spent feeding. The lowest scores on feeding were obtained at night and in single, non-incubating Ruddy Turnstones and Dunlins on territories (e.g. off-duty breeders), which fed for only 39% and 56% of their time, respectively. Feather care accounted for up to about 21% during breeding proper, but very little during pre- and post-breeding. Conversely, the birds hardly rested during their stay on the territories as opposite to a noticeable part (up to 17%) of the day especially during pre-breeding in most of the species. During young attendance (only studied in Dunlin), 75% of the time was used on resting, being alert, and preening. During post-breeding, much time was used flying, particularly in Dunlins (17%). Aggressive behaviour was not observed among pre-breeding birds and only occasionally during post-breeding, but territorial behaviour is common early in the breeding season. Soil and pitfall trap samples of invertebrates showed that spiders and dipteran imagos and larvae most likely made up the bulk of wader food on the tundra during the summer, and that spiders were unusually numerous during spring 2000. During post-breeding fattening on coastal mudflats, crustaceans may have been most important. 2000 was a year of little snow-cover in early June (54% on 10 June against about 80% in most years), and waders may not have been time-constrained in their feeding. This may be very different in years of much snow, when the pre-breeding period may pose a bottleneck in the annual cycle of arctic waders. During July and August, food for the adults seems to be plentiful.
Scene Labeling Through Knowledge-Based Rules Employing Constrained Integer Linear Programing

Scene labeling task is to segment the image into meaningful regions and categorize them into classes of objects which comprised the image. Commonly used methods typically find the local features for each segment and label them using classifiers. Afterward, labeling is smoothed in order to make sure that neighboring regions receive similar labels. However, they ignore expressive and non-local dependencies among regions due to expensive training and inference. In this paper, we propose to use high-level knowledge regarding rules in the inference to incorporate dependencies among regions in the image to improve scores of classification. Towards this aim, we extract these rules from data and transform them into constraints for Integer Programming to optimize the structured problem of assigning labels to super-pixels (consequently pixels) of an image. In addition, we propose to use soft-constraints in some scenarios, allowing violating the constraint by imposing a penalty, to make the model more flexible. We assessed our approach on three datasets and obtained promising results.
How Efficient is MPEG-7 for General Sound Recognition?

Our challenge is to analyze/classify video sound track content for indexing purposes. To this end we compare the performance of MPEG-7 Audio Spectrum Projection (ASP) features based on several basis decomposition algorithms vs. Mel-scale Frequency Cepstrum Coefficients (MFCC). For basis decomposition in the feature extraction we evaluate three approaches: Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Non-negative Matrix Factorization (NMF). Audio features are computed from these reduced vectors and are fed into a continuous hidden Markov model (CHMM) classifier. Our conclusion is that established MFCC features yield better performance compared to MPEG-7 ASP in the general sound recognition under practical constraints.
Effects of Nutrition on the Immunity of Dairy Calves

Dairy calves are extremely susceptible to gastrointestinal disease during the preweaned period. The risk for enteric disease decreases as the calf ages; therefore, it is important to break the pre-weaned period up into at least 2 distinct phases that likely need to be managed differently, early life (first couple weeks of life) and the remaining time the calf is fed milk or milk replacer. When a calf is born they have been exposed to very few if any microorganisms and some aspects of their gastrointestinal immune system are not fully developed. After birth, the calf is now in a microbial world and exposed to a greater quantity and diversity of microorganisms. This adaptation is abrupt and dramatic and is a major stressor to a newborn calf. The gastrointestinal tract of the calf is naïve and develops rapidly during the first few days to weeks of life. The cells that make up the gastrointestinal tract are the first line of defense of the immune system; therefore, until the cells are more adult-like the calf may be at an increased risk for developing gastrointestinal diseases. My laboratory recently tested the hypothesis that feeding greater quantities of milk solids during the first week of life would increase the percentage of dietary nutrients that were neither digested nor absorbed by the calf, which would increase the risk of scours. The data indicated that dairy calves during the first few weeks of life digest and absorb nutrients well, and when fed a greater plane of nutrition the additional nutrients were incorporated into tissue growth. However, the increased absorption of nutrients among calves fed greater quantities of milk replacer may increase the risk for enteric disease (Liang et
Accelerating GLA with an M-Tree

In this paper, we propose a novel improvement for the generalized Lloyd Algorithm (GLA). Our algorithm makes use of an M-tree index built on the codebook which makes it possible to reduce the number of distance computations when the nearest code words are searched. Our method does not impose the use of any specific distance function, but works with any metric distance, making it more general than many other fast GLA variants. Finally, we present the positive results of our performance experiments. Keywords—Clustering, GLA, M-Tree, Vector
Analysis of ITS-G5A V2X communications performance in autonomous cooperative driving experiments

In this paper the performance of ITS-G5A communications for an autonomous driving application is analyzed in a real high-density scenario. The data was collected during the cooperative platooning tests that took place in Helmond in the frame of the Grand Cooperative Driving Challenge 2016. In the competition, between 8–10 autonomous vehicles formed two platoons in different lanes and were required to merge into a predefined competition zone. The performance is characterized using CAM CCDFs which serves as a base for the evaluation of a Cooperative Adaptive Cruise Control application. Two important effects has been identified that affect to the reliability of the communications. Firstly, there is a degradation with the distance that appears to be stronger for cars and more gentle for trucks. This indicates that occlusions heavily affect the connectivity of ITS-G5A. Secondly, the reliability is below expectations and some of the vehicles perform consistently worse than others. Although further investigation is required, a possible explanation for this is that a highly congested channel is making some of the vehicles get stuck and are not able to regularly access the channel.
Total lake water resources of the planet

well known (Rudolf, Winnipeg, Nicoragua, Van, Venern, Athabasca, Edward, Dead Sea, Balkhash Alberta, Chad, Tana, Geneva, Sevan, Zaysan), contain 1.9 x 103 km3 of water. Small lakes contain much less water. The total amount of water in the small and smallest lakes is trifling despite the fact that they are so abundant and so large in area. This paper is an attempt to evaluate approximately the amounts of water using the data on Euras ia, and then to give an approximate evaluation for the lake water resources on the Earth as a whole. The total lake area of the Earth amounts to 2.7 x 106 km2; the 19 largest lakes account for about 1 X 106 km2, and all the other several millions of lakes for the remaining 1.7 x 106 km2. Excluding the 6 largest lakes (Caspian, T A B L E 1
Total Phenolic Contents and Antioxidant Capacities of Herbal and Tea Infusions

In order to supply new information on the antioxidant function of selected beverages for nutritionists and the general public, total phenolic contents of 51 kinds of herbal and tea infusions made in China were measured by the Folin-Ciocalteu method, and their antioxidant capacities were evaluated using ferric reducing antioxidant power (FRAP) and Trolox equivalent antioxidant capacity (TEAC) assays. A significant correlation between FRAP and TEAC values suggested that antioxidant components in these beverages were capable of reducing oxidants and scavenging free radicals. The high correlation between antioxidant capacities and total phenolic contents indicated that phenolic compounds could be one of the main components responsible for antioxidant activities of these beverages. Generally, these beverages had high antioxidant capacities and total phenolic contents, and could be important dietary sources of antioxidant phenolics for prevention of diseases caused by oxidative stress.
Vibrational imaging of lipid droplets in live fibroblast cells with coherent anti-Stokes Raman scattering microscopy Published, JLR Papers in Press, August 16, 2003. DOI 10.1194/jlr.D300022-JLR200

A new vibrational imaging method based on coherent anti-Stokes Raman scattering (CARS) has been used for high-speed, selective imaging of neutral lipid droplets (LDs) in unstained live fibroblast cells. LDs have a high density of C-H bonds and show a high contrast in laser-scanning CARS images taken at 2,845 cm−1, the frequency for aliphatic C-H vibrations. The contrast from LDs was confirmed by comparing CARS and Oil Red O (ORO)-stained fluorescence images. The fluorescent labeling processes were examined with CARS microscopy. It was found that ORO staining of fixed cells caused aggregation of LDs, whereas fixing with formaldehyde or staining with Nile Red did not affect LDs. CARS microscopy was also used to monitor the 3T3-L1 cell differentiation process, revealing that there was an obvious clearance of LDs at the early stage of differentiation. After that, the cells started to differentiate and reaccumulate LDs in the cytoplasm in a largely unsynchronized manner. Differentiated cells formed small colonies surrounded by undifferentiated cells that were devoid of LDs. These observations demonstrate that CARS microscopy can follow dynamic changes in live cells with chemical selectivity and noninvasiveness. CARS microscopy, in tandem with other techniques, provides exciting possibilities for studying LD dynamics under physiological conditions without perturbation of cell functions.
A NEW SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM KARAGIANNIS

A new primal simplex type algorithm for the Minimum Cost Network Flow Problem (MCNFP) is presented. The proposed algorithm belongs to a special “exterior simplex type” category. Contrary to the network primal simplex algorithm, the new algorithm computes two flows. One flow is basic but not always feasible and the other is feasible but not basic. The pseudo code and analytical description of the pivot procedure is given. Furthermore, the necessary steps are analytically shown through an illustrative example.
Machine Translation with Inferred Stochastic Finite-State Transducers

Finite-state transducers are models that are being used in different areas of pattern recognition and computational linguistics. One of these areas is machine translation, in which the approaches that are based on building models automatically from training examples are becoming more and more attractive. Finite-state transducers are very adequate for use in constrained tasks in which training samples of pairs of sentences are available. A technique for inferring finite-state transducers is proposed in this article. This technique is based on formal relations between finite-state transducers and rational grammars. Given a training corpus of source-target pairs of sentences, the proposed approach uses statistical alignment methods to produce a set of conventional strings from which a stochastic rational grammar (e.g., an n-gram) is inferred. This grammar is finally converted into a finite-state transducer. The proposed methods are assessed through a series of machine translation experiments within the framework of the E u Trans project.
Leading NoSQL models for handling Big Data: a brief review

Today, in data science, the large, complex, structured or unstructured, and heterogeneous data has gained significant attention. The data is being generated at a very rapid pace through various disparate potential resources and sensors, scientific instruments, and internet, especially the social media, are just to name a few. The considerable velocity of the volume expansion of the data possesses the serious challenges for the existing data processing systems. In this paper, we review some of the modern data models that claim to process the extremely large data such as Big Data of petabyte size in reliable and efficient way and are the leading contributors in NoSQL largely being translated as 'not only SQL' era.
EEG auditory steady state responses classification for the novel BCI

An auditory modality brain computer interface (BCI) is a novel and interesting paradigm in neurotechnology applications. The paper presents a concept of auditory steady state responses (ASSR) utilization for the novel BCI paradigm. Two EEG feature extraction approaches based on a bandpass filtering and an AR spectrum estimation are tested together with two classification schemes in order to validate the proposed auditory BCI paradigm. The resulting good classification scores of users intentional choices, of attending or not to the presented stimuli, support the hypothesis of the ASSR stimuli validity for a solid BCI paradigm.
Forging links between rural health service providers : the mechanics of a spectacular success

This paper examines the decision to appoint a CIO to the South West Alliance of Rural Hospitals with responsibility for ICT initiatives within the region and the impact this had on the ICT strategy that emerged. Since there was no formal ICT infrastructure in place that was shared by the independent service providers in the region it was felt from the outset that the provision of shared services would provide the key to establishing regional cooperation. The paper briefly describes the communications network that emerged between 1999 and 2002, it pays some attention to the implementation challenge but rather than dwell on the implementation problems the paper examines the implications of the approach taken. The emergence of the truly virtual health care network in Victoria’s South West holds a number of useful lessons for the delivery of rural, regional and remote health care. Background to the case The continued growth in the availability and power of information technologies empowered by a parallel explosion in communications technologies has resulted in the radical reshaping of business strategy and the shape of organisations addressing these new strategies. Mindful of this in 1997 the Health Department of Victoria (DHS) felt that some action was needed to ensure the Acute Health sector was appropriately structured and making appropriate use of ICT. KPMG was engaged to prepare an ICT strategic plan, which had the prime objective of identifying if a significant investment in ICT could reduce the costs of delivering Health services. The KPMG ICT plan as presented to the Victorian State Government in 1997 proposed a capital injection of $400 million with the aim of saving 3.5% of the Healthcare Budget per year within four years. The strategy split Victoria into 14 health regions (5 Rural and 9 metropolitan). Each region would have a CIO appointed with a clear charter to implement the strategy in that region. In practice only $100 million was made available over the four years but immediate operating budgets were cut on average by 1.5% on the expectation of the planned savings. So this initiative was never fully funded, but it was locked in by the assumed operating savings factored into hospital budgets. This paper examines the approach taken by one of the 14 groups established, the South West Alliance of Rural Hospitals (SWARH). The model established in the south west is being adopted or examined closely by most of the other rural groups in Victoria and the SWARH model is also being examined by
Optimization of an Oil Production System using Neural Networks and Genetic Algorithms

This paper proposes an optimization strategy which is based on neural networks and genetic algorithms to calculate the optimal values of gas injection rate and oil rate for oil production system. Two cases are analyzed: a) A single well production system and b) A production system composed by two gaslifted wells. For both cases an objective function is maximized to reduce production cost. The proposed strategy shows the ability of the neural networks to approximate the behavior of an oil production system and the genetic algorithms to solve optimization problems when a mathematical model is not available. Keywords— Genetic algorithms, injection gaslift, neural network, optimization, oil production system, perceptron multilayer.
On the capacity of cellular systems with MIMO

It is shown that the mutual information of a single, isolated, multiple transmit and receive antenna array link is maximized by transmitting the maximum number of independent data streams for a flat Rayleigh fading channel with independent fading coefficients for each path. However, if such links mutually interfere, in some cases the overall system mutual information can be increased by transmitting fewer streams.
Eye Detection in Facial Image by Genetic Algorithm Driven Deformable Template Matching

Summary As face recognition and facial feature based human computer interaction have become the subjects of intense focus in recent decades, facial feature extraction has emerged as a challenging task in the field of computer vision. Eye is said to be the most salient feature on face because of its versatility of appearance and expression variety. Various eye detection schemes are proposed in the literature but most of them require massive mathematical processing which is a barrier against real-time implementation. A novel approach for eye detection is proposed in this paper which exploits the flexibility of deformable template and uses genetic algorithm to match the template for eye detection. Implementation of genetic algorithm reduces the time required for template matching than conventional template matching algorithm. Moreover the method does not require any prior knowledge about eye geometry or potential eye location tags on facial image. Experimental results show that the proposed scheme can easily be implemented in real-time as it can detect eye in few genetic epochs. The method was tested on ORL face image database which contains 400 images grouped into 40 persons having 10 different expressions each. The detection accuracy was 87.2%.
An enhanced first-order sigma-delta modulator with a controllable signal-to-noise ratio

This paper presents an enhanced first-order sigma-delta modulator. The proposed modulator, derived using the Al-Alaoui operator, outperforms the conventional modulator. A comparison is drawn showing that the conventional sigma-delta modulator is a special case of the enhanced sigma-delta modulator. The paper includes an analytical derivation as well as extensive simulations revealing the superiority of the proposed modulator reaching optimal performance
Techniques for grounding agent-based simulations in the real domain: a case study in experimental autoimmune encephalomyelitis

For computational agent-based simulation, to become a serious tool for investigating biological systems requires the implications of simulation-derived results to be appreciated in terms of the original system. However, epistemic uncertainty regarding the exact nature of biological systems can complicate the calibration of models and simulations that attempt to capture their structure and behaviour, and can obscure the interpretation of simulation-derived experimental results with respect to the real domain. We present an approach to the calibration of an agent-based model of experimental autoimmune encephalomyelitis (EAE), a mouse proxy for multiple sclerosis (MS), which harnesses interaction between a modeller and domain expert in mitigating uncertainty in the data derived from the real domain. A novel uncertainty analysis technique is presented that, in conjunction with a latin hypercube-based global sensitivity analysis, can indicate the implications of epistemic uncertainty in the real domain. These analyses may be considered in the context of domain-specific knowledge to qualify the certainty placed on the results of in silico experimentation.
Transcriptional Homeostasis of a Mangrove Species, Ceriops tagal, in Saline Environments, as Revealed by Microarray Analysis

Background Differential responses to the environmental stresses at the level of transcription play a critical role in adaptation. Mangrove species compose a dominant community in intertidal zones and form dense forests at the sea-land interface, and although the anatomical and physiological features associated with their salt-tolerant lifestyles have been well characterized, little is known about the impact of transcriptional phenotypes on their adaptation to these saline environments. Methodology and Principal findings We report the time-course transcript profiles in the roots of a true mangrove species, Ceriops tagal, as revealed by a series of microarray experiments. The expression of a total of 432 transcripts changed significantly in the roots of C. tagal under salt shock, of which 83 had a more than 2-fold change and were further assembled into 59 unigenes. Global transcription was stable at the early stage of salt stress and then was gradually dysregulated with the increased duration of the stress. Importantly, a pair-wise comparison of predicted homologous gene pairs revealed that the transcriptional regulations of most of the differentially expressed genes were highly divergent in C. tagal from that in salt-sensitive species, Arabidopsis thaliana. Conclusions/Significance This work suggests that transcriptional homeostasis and specific transcriptional regulation are major events in the roots of C. tagal when subjected to salt shock, which could contribute to the establishment of adaptation to saline environments and, thus, facilitate the salt-tolerant lifestyle of this mangrove species. Furthermore, the candidate genes underlying the adaptation were identified through comparative analyses. This study provides a foundation for dissecting the genetic basis of the adaptation of mangroves to intertidal environments.